Diversity in the scientific community 9780841232341, 0841232342, 9780841232365, 0841232369, 9780841232334

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Content: Volume 1. Quantifying diversity and formulating success --
volume 2. Perspectives and exemplary programs.

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Diversity in the Scientific Community Volume 1: Quantifying Diversity and Formulating Success

ACS SYMPOSIUM SERIES 1255

Diversity in the Scientific Community Volume 1: Quantifying Diversity and Formulating Success Donna J. Nelson, Editor University of Oklahoma Norman, Oklahoma

H. N. Cheng, Editor U.S. Department of Agriculture New Orleans, Louisiana

American Chemical Society, Washington, DC Distributed in print by Oxford University Press

Library of Congress Cataloging-in-Publication Data Names: Nelson, Donna J., editor. | Cheng, H. N., editor. Title: Diversity in the scientific community / Donna J. Nelson, editor (University of Oklahoma, Norman, Oklahoma), H.N. Cheng, editor (U.S. Department of Agriculture, New Orleans, Louisiana). Description: Washington, DC : American Chemical Society, [2017]- | Series: ACS symposium series ; 1255, 1256 | Includes bibliographical references and index. Identifiers: LCCN 2017045513 (print) | LCCN 2017050881 (ebook) | ISBN 9780841232334 (ebook) | ISBN 9780841232341 (v. 1) | ISBN 9780841232365 (v. 2) Subjects: LCSH: Science--Social aspects. | Diversity in the workplace. | Equality. Classification: LCC Q175.5 (ebook) | LCC Q175.5 D548 2017 (print) | DDC 306.4/5--dc23 LC record available at https://lccn.loc.gov/2017045513

The paper used in this publication meets the minimum requirements of American National Standard for Information Sciences—Permanence of Paper for Printed Library Materials, ANSI Z39.48n1984. Copyright © 2017 American Chemical Society Distributed in print by Oxford University Press All Rights Reserved. Reprographic copying beyond that permitted by Sections 107 or 108 of the U.S. Copyright Act is allowed for internal use only, provided that a per-chapter fee of $40.25 plus $0.75 per page is paid to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. Republication or reproduction for sale of pages in this book is permitted only under license from ACS. Direct these and other permission requests to ACS Copyright Office, Publications Division, 1155 16th Street, N.W., Washington, DC 20036. The citation of trade names and/or names of manufacturers in this publication is not to be construed as an endorsement or as approval by ACS of the commercial products or services referenced herein; nor should the mere reference herein to any drawing, specification, chemical process, or other data be regarded as a license or as a conveyance of any right or permission to the holder, reader, or any other person or corporation, to manufacture, reproduce, use, or sell any patented invention or copyrighted work that may in any way be related thereto. Registered names, trademarks, etc., used in this publication, even without specific indication thereof, are not to be considered unprotected by law. PRINTED IN THE UNITED STATES OF AMERICA

Foreword The ACS Symposium Series was first published in 1974 to provide a mechanism for publishing symposia quickly in book form. The purpose of the series is to publish timely, comprehensive books developed from the ACS sponsored symposia based on current scientific research. Occasionally, books are developed from symposia sponsored by other organizations when the topic is of keen interest to the chemistry audience. Before agreeing to publish a book, the proposed table of contents is reviewed for appropriate and comprehensive coverage and for interest to the audience. Some papers may be excluded to better focus the book; others may be added to provide comprehensiveness. When appropriate, overview or introductory chapters are added. Drafts of chapters are peer-reviewed prior to final acceptance or rejection, and manuscripts are prepared in camera-ready format. As a rule, only original research papers and original review papers are included in the volumes. Verbatim reproductions of previous published papers are not accepted.

ACS Books Department

Contents Preface .............................................................................................................................. ix 1.

Diversity in Science: An Overview ......................................................................... 1 Donna J. Nelson and H. N. Cheng

Using Data To Quantify the Problem, Formulate Solutions and Measure Success 2.

Diversity of Science and Engineering Faculty at Research Universities ........... 15 Donna J. Nelson

3.

Smashing the Glass Ceiling in Chemistry Remains a Long-Range Goal ......... 87 Valerie J. Kuck

4.

The Gender and URM Faculty Demographics Data Collected by OXIDE .... 101 Rigoberto Hernandez, Dontarie Stallings, and Srikant Iyer

Workplace Environment and Work Styles for Women 5.

Career Success of Women in the Chemical Industry, Part 1: Finding a Way through the Labyrinth ......................................................................................... 115 Penelope A. Asay, Jill D. Paquin, Julie R. Arseneau, Vanessa Downing, Melissa S. Roffman, Kelly D. Kettlewell, Tracey Berman, Heather M. Walton, and Ruth E. Fassinger

6.

Career Success of Women in the Chemical Industry, Part 2: Navigating Workplace Challenges ......................................................................................... 145 Julie R. Arseneau, Penelope A. Asay, Jill D. Paquin, Heather M. Walton, Vanessa Downing, Melissa S. Roffman, and Ruth E. Fassinger

7.

Career Success of Women in the Chemical Industry, Part 3: Getting on the Same Page ............................................................................................................. 173 Jill D. Paquin, Julie R. Arseneau, Penelope A. Asay, Vanessa Downing, Melissa S. Roffman, Heather M. Walton, and Ruth E. Fassinger

8.

Gender and Thought Diversity in Chemistry .................................................... 205 Gary J. Salton and Shannon Nelson

Editors’ Biographies .................................................................................................... 219

vii

Indexes Author Index ................................................................................................................ 223 Subject Index ................................................................................................................ 225

viii

Preface The two volumes of this book are partially based on three symposia held at the ACS Spring National Meeting in San Diego, March 2016. • • •

Diversity-Quantification-Success? How to Foster Diversity in the Chemical Sciences: Lessons Learned & Taught from the Stories of Recipients of the Stanley C. Israel Award My Experience with & Advice for Improving Diversity in Chemistry

These symposia were part of the 2016 ACS activities relating to Diversity, which represented one of 2016 ACS President Donna Nelson’s presidential themes. The symposium speakers included scientists reporting original research on various aspects of diversity in science, ACS leaders, accomplished professionals, and past winners of the Stanley Israel diversity awards. Data were presented which pertained to science, technology, engineering, and mathematics (STEM), with a particular emphasis on chemistry. The symposia were very well attended and the comments from the audience very positive. Many symposium participants felt that it would be exceedingly useful to compile the diversity-related data and case stories presented in the symposium in one book so that scholars and students interested in diversity can conveniently draw on the book for further research, self-study, class instructions, and reference. Thus, soon after the symposia, we invited the speakers to contribute chapters to this book. In addition, several diversity researchers and opinion leaders were also invited to participate. Contributors to this book included many representatives of ACS committees and divisions related to diversity, e.g., Committee on Minority Affairs (CMA), Senior Chemists Committee (SCC), Chemists with Disabilities Committee (CWD), International Activities Committee (IAC), and Division of Professional Relations (PROF). This book is aimed: 1) to assess the current status of diversity in the scientific community, 2) to gather ideas on how to improve diversity in science, 3) to document personal stories and perspectives relating to diversity, and 4) to make the information available to the public and to a broad spectrum of scientists, including chemists and chemical engineers. A goal is to increase awareness of the importance of diversity, the immediate need for change, and the changes which are possible and most practical to achieve the desired results. A total of 28 chapters are included in this book with contributions from most speakers in the three ACS symposia. For convenience, this book is divided into two volumes. This volume (Volume 1) has eight chapters divided into two sections: ix

1) Using Data to Quantify the Problem, Formulate Solutions and Measure Success 2) Workplace Environment and Work Styles for Women Chapter 1 in this volume is an overview that summarizes the contents of all other chapters and also provides the background and the framework for the themes delineated in the book. Section 1 in this volume provides data, which serve as benchmarks for universities, departments, and disciplines to compare their own representations of women and minorities versus that of their peers. This includes the 2012 Nelson Diversity Surveys, which many researchers have been awaiting. Complementing the first volume, Volume 2 of this book consists of 20 chapters divided into three sections: 1) Examples of Diversity Programs in Science, 2) Stories from Stanley Israel Awardees, 3) Perspectives on Diversity and Inclusivity. A major audience for the book will be working chemists and chemical engineers, graduate and undergraduate students, and chemistry teachers. Because the diversity data cover so many disciplines, this book should appeal to a wider audience than merely chemists. Scientists and engineers of all disciplines, and other related professions, such as medicine and law, may find the information useful. In addition to the data, the perspectives and the personal stories will inspire readers to support diversity and to champion diversity programs. All the chapters illustrate the importance of diversity and inclusivity in STEM. We appreciate the efforts of the authors who took time to prepare their manuscripts and our many reviewers for their cooperation during the peer review process. We also thank Arlene Furman, Tracey Glazener, Elizabeth Hernandez and their colleagues at ACS Books for their patient and effective handling of the manuscripts. It is the editors’ hope that the readers will find the information given in the two volumes of this book useful, and they will have long-term impact on the scientific enterprise.

Donna J. Nelson Department of Chemistry and Biochemistry University of Oklahoma 101 Stephenson Pkwy Norman, OK 73019-9704, USA

H. N. Cheng Southern Regional Research Center USDA – Agricultural Research Service 1100 Robert E. Lee Blvd. New Orleans, LA 70124, USA

x

Chapter 1

Diversity in Science: An Overview Donna J. Nelson*,1 and H. N. Cheng*,2 1Department

of Chemistry, University of Oklahoma, Norman, Oklahoma 73019-9704, United States 2USDA Agricultural Research Service, Southern Regional Research Center, New Orleans, Louisiana 70124, United States *E-mail: [email protected]; [email protected]

In the last decade or so, many chemical organizations have recognized the importance of diversity as a means to enhance recruitment and retention of talent, improve marketing of products or services, and broaden the scope and perspectives for new ideas. Despite this increasing recognition, there is still much work to be done in order to achieve a fair and equitable workplace, where workers can each achieve their full potential. In particular, there is noticeable disparity in academia in career advancement, compensation, and attitude toward members of underrepresented groups (URGs), especially pertaining to gender, race, and ethnicity. An overview is given in this article, highlighting some key findings. More details can be found in the individual chapters of this book.

Introduction Diversity is defined by the Business Dictionary as “feature of a mixed workforce that provides a wide range of abilities, experience, knowledge, and strengths due to its heterogeneity in age, background, ethnicity, physical abilities, political and religious beliefs, sex, and other attributes” (1). Whereas diversity is broadly desirable in the society at large, it is especially important in science, technology, engineering, and mathematics (STEM) in the U.S. because the population demographics in the U.S. in the next 50 years are projected to change significantly in terms of age, race, and ethnicity. Thus, the importance of diversity and achieving it are likely to increase in the future, so it is useful to

© 2017 American Chemical Society

understand the current status of diversity and to seek ways to optimize their roles and contributions to the society. Historically the concept of diversity has been increasingly prominent since the civil right movement and the passage of the Immigrant Act in the 1960s. Nonetheless, despite the efforts and the funds expended, diversity remains a major workplace issue in the STEM enterprise today (2–21). In the past decade or so, many STEM organizations have recognized the importance of diversity as a means to enhance recruitment and retention of talent, improve marketing of products, and broaden the scope and perspectives for new ideas (6–9). Yet, a number of studies have shown workplace inequities with respect to bias in hiring, promotion, attitudes, and recognition (10, 11).

Advantages Accompanying Diversity in Organizations McKinsey & Company has been studying diversity in the workplace for many years. In their latest report Diversity Matters, they examined proprietary data sets for 366 public companies across a range of industries in Canada, Latin America, the United Kingdom, and the United States. Some of their findings are given below (16): •

•

•

•

•

Companies in the top quartile for racial and ethnic diversity are 35 percent more likely to have financial returns above their respective national industry medians. Companies in the top quartile for gender diversity are 15 percent more likely to have financial returns above their respective national industry medians. In the U.S., there is a linear relationship between racial and ethnic diversity versus better financial performance: for every 10 percent increase in racial and ethnic diversity on the senior-executive team, earnings before interest and taxes (EBIT) rise 0.8 percent. Racial and ethnic diversity has a stronger impact on financial performance in the United States than gender diversity; a possible reason is because earlier efforts to increase women’s representation in the top levels of business have already yielded their positive results. The unequal performance of companies in the same industry and the same country, but which differ in their degrees of diversity, implies that diversity is a competitive differentiator shifting market share toward more diverse companies.

From research done by McKinsey (16) and others (2–9), diversity seems to have an overall positive impact on STEM organizations. In business and industry, diversity helps to increase the talent pool for recruitment, better gauge customers’ needs, enhance marketing understanding, and improve input and creativity of the workplace. Moreover, diversity can potentially lead to improved morale, increased productivity, broadened perspectives, and positive work environment. 2

In academia, increasing diversity at the professor level provides not only more talent at that level, but throughout the educational pipeline, due to the extensive effect of professors throughout the academic pipeline. Diversity among students allows students to work and study with classmates from a diverse range of backgrounds that can enrich their overall educational experience (12–14). In scientific research and development, diversity can be helpful in a number of specific ways (7–9), e.g., 1.

2.

3.

4.

Scientific advancement relies on the availability of a highly skilled workforce. In order for the workforce to be an adequate size, we must recruit talent from all social identities (e.g., gender, race, ethnicity, nationality, disability, and others). Innovation in science frequently requires novel ideas, problem-solving skills, and objective assessment of data without biases. These characteristics can be enhanced through diversity as each person contributes an individual background, opinions, and technical strengths to the advancement of a field. Many scientific problems today tend to be complex and often solved by teams. A team with diverse members can bring different perspectives and capabilities to bear on the problems and produce more effective solutions. With increasing globalization, researchers can facilitate their work through global connections for collaboration, use of equipment, or education exchange. An inclusive and globally oriented work environment can attract and retain talent from diverse and global populations.

Above all, the benefit of diversity has been demonstrated by the positive effects of diverse collaborations in scientific research. In a 2014 article, Smith et al (15) analyzed papers published between 1996 and 2012 in 8 disciplines and found the papers with authors from more countries fared better in journal placement and citation performance. In a 2015 article (17), Freeman et al examined the ethnic identity of authors in over 2.5 million scientific papers written by U.S.-based authors from 1985 to 2008 and found that publications coauthored by people of similar ethnicity tend to appear in lower-impact journals with fewer citations. In contrast, papers with authors in more locations and with longer reference lists were published in higher-impact journals and received more citations. These findings suggest that diversity via author ethnicity, location, and references leads to stronger contributions to science as measured by impact factors and citations.

Challenges of Diversity If diversity is so attractive, one may ask why it is not universally accepted and perpetuated. Many opposing factors have been cited, including inherent bias of people involved, ineffective communication, resistance to change, challenge in implementation, and the difficulty of managing diversity effectively (10, 11, 18–20). The data and research presented in several chapters of this book certainly 3

indicate the need for improvement in gender and racial diversity in academia (22–28). In a recent article (21), Dobbin and Kalev reported a study of 800 U.S. corporations, where many diversity programs were found to be ineffective. These companies were using older techniques, such as diversity training to reduce bias on the job, hiring tests and performance ratings to limit bias in recruitment and promotion, and grievance systems to give employees a way to challenge managers. These tactics seemed inadequate. Their research suggested that managers should be engaged in solving problems, increase their on-the-job contact with female and minority workers, and promote social accountability, including targeted college recruitment, mentoring, and self-managed teams and task forces. It is evident that diversity is a work in progress, which requires sustained effort. It is encouraging, therefore, that there are highly successful diversity programs ongoing in several institutions. Many of these programs are documented in the chapters of this book (29–48).

Measuring the Progress of STEM Diversity A number of studies have been carried out on diversity in academia over the years (10, 11). In this book, Nelson (22), Kuck (23), and Hernandez et al (24) provide new data on gender bias in academia. In all three studies, women are found to be significantly under-represented among STEM faculty. While some institutions have made substantial gains, most have achieved limited progress. When a survey captures a sample of a population, a statistical analysis of its results must be made, especially when dealing with small numbers. A number which is smaller than the error calculated for that number is meaningless. A representation of zero, which is often found in the cases of Native American faculty or minority female faculty, only has meaning when the survey captures the full population (100% participation). Using Native Americans as an example, if data are unavailable for just one survey respondent, even if no Native Americans are found in all other respondents’ data, then it cannot be concluded that the representation of Native Americans is zero, because Native Americans could be among the missing respondent’s data. Typically, the representation of women among STEM faculty is sufficiently large to survive the needed statistical analysis. However, the representation of Blacks, Hispanics, and Native Americans is each too low to give meaningful results, because the magnitudes of the representation is typically smaller than the errors. This is especially true when data are further disaggregated by rank and gender. Two ways to overcome this problem are (1) by combining the three URM races or (2) by collecting the whole population rather than a sample. The representations of under-represented minorities (URMs) is so low that the numbers do not survive the required statistical analysis In their surveys, Nelson (22) and Hernandez et al (24) each report disaggregated percentages of Blacks, of Hispanics, and of Native Americans in academia They each found the situation somewhat similar to that of women. The 4

Hernandez study reported samples and focused on chemistry (24), reporting the representation of URM professors over the past 15 years, disaggregated by race; there were no statistical analyses. The Nelson Diversity Surveys covered 15 science and engineering disciplines (22) and disaggregated the data by race, by rank, and by gender. Fully disaggregated URM data could be reported because these Surveys captured the full population in each discipline, each year they were carried out (FY2012, FY2007, FY2005, FY2002). URMs have achieved critical mass in no discipline studied, and the representations include Black, Hispanic, and Native American; these studies collected whole populations and therefore needed no statistical analyses. In each study, the representations of URMs among faculty lagged far behind the corresponding representations in the general population. The situation of women in industry was studied in detail in three papers by Fassinger et al (25–27). There was a wealth of information in those papers, including the following key findings: • •

• •

•

Company support, particularly as manifested by supervisors, was a critical factor in women’s success. Women exhibited both willingness and confidence to advance, and managerial women exhibited higher job satisfaction than non-managerial women A large percentage of women perceived themselves as having been passed over for advancement opportunities. Balancing home and work was a top work-related stressor. Women with a greater number of dependent children and more managerial responsibility indicated greater home-work conflict. Company-provided childcare was associated with reducing home-work conflict. Female mentors were more likely than males to provide support for managing the home-work interface.

In a different approach, Salton and Nelson (28) used an engineering-based methodology to analyze the root cause of gender imbalance in scientific employment. They grouped people in four strategic styles and found women, on the average, to have inherently different work styles than men. The different work style would have an impact on the execution of diversity programs. For example, the inclusion of women is desirable in order to mitigate the often cited “boys club” conditions in engineering. However, to be effective in limiting bias, the women included should be given positional power. If women were merely “given seats at the table” but told to be quiet, nothing would change.

Exemplary Diversity Programs Despite the challenges facing diversity, many organizations have successfully implemented diversity programs and made great strides. For example, since 1977, the Maximizing Access to Research Careers (MARC) program from National Institute of General Medical Sciences (NIGMS) has evolved to provide support 5

for URM college undergraduate students in the biomedical sciences in order to improve their preparation for high-caliber doctoral graduate training (29). A recent analysis of the educational outcomes of the program alumni indicates that this program is achieving its goals. Among recent MARC alumni, 29.2% earned a PhD, 11.7% M.D., and another 25.8% completed or are enrolled in other advanced degrees (29). One of the program’s that receives NIGMS funding is the University of Texas at San Antonio; their Research Initiative for Scientific Enhancement (RISE) program has been very successful in helping Hispanic undergraduate students enter doctoral training programs (30). In addition, many universities have designed and implemented successful academic program for minorities. These include Xavier University of Louisiana (31), Brandeis University (32), Purdue University (33), Southwestern College (35), University of California Berkeley (36), Queensborough Community College of the City University of New York (37), University at Buffalo (38), and Louisiana State University (40). We applaud their great efforts, which have significantly advanced the cause of diversity in STEM at different universities. At Rochester Institute of Technology, a successful program is ongoing to narrow graduation and employment gaps between students who are hearing impaired and those who are not (39). At Johns Hopkins University, the Open Chemistry Collaborative in Diversity Equity (OXIDE) program works with department heads and social scientists to enhance faculty diversity. In the chapter written by Stallings and Hernandez (34), they reported on their use of social media as a platform for disseminating qualitative and quantitative diversity information. Besides the successful programs noted above, Valdez and Lopez (41) reported on the Alliance for Diversity in Science and Engineering (ADSE) and its precursors, which support, organize, and oversee local, graduate student-run organizations to promote diversity. Varma-Nelson (42) pointed out that the graduate students’ leadership experiences have a positive impact on the students’ academic, personal and professional lives. Collins (43) provided several examples of successful scientists and women of color in both academia and industry as possible role models for others.

Diversity and Global Competence at ACS As noted earlier, many organizations have realized the importance of diversity in their future growth. The American Chemical Society (ACS) is an example of such an organization. ACS has issued a public statement on diversity as given below. “The American Chemical Society believes that to remain the premier chemical organization that promotes innovation and advances the chemical sciences requires the empowerment of a diverse and inclusive community of highly skilled chemical professionals regardless of race, gender, age, religion, ethnicity, nationality, sexual orientation, gender expression, gender identity, presence of disabilities, educational background, and other factors. Chemical scientists rely on the American Chemical Society to promote inclusion and diversity in the discipline.” 6

Thus, ACS has in place a strong culture in diversity and inclusivity. For many years ACS has convened several national committees that help to promote diversity and inclusion. These include Women Chemists Committee (WCC), Younger Chemists Committee (YCC), Committee on Minority Affairs (CMA), and Committee on Chemists with Disabilities (CWD). Moreover, an umbrella group for all diversity and inclusion groups was started in 2006 as Collaborative Working Group, which became Joint Subcommittee on Diversity in 2007, and is now called ACS Diversity & Inclusion Advisory Board (D&I). The current constituent members of D&I include WCC, YCC, CMA, CWD, as well as Senior Chemists Committee (SCC), Committee on Professional Training, (CPT), Committee on Technician Affairs (CTA), and Division on Professional Relations (PROF). In this book, several chapters were written by representatives of diversity groups within ACS. Thus, Bannochie traced the beginning of the LBGT inclusion and the progress he and his colleagues have made within ACS (44). Denio related his experience in the ACS Delaware Section’s ChemVet group and as a member of the ACS Senior Chemists Committee (45). Booksh discussed the important role that people with disabilities can contribute to the scientific and engineering fields (46). Neybert provided the viewpoints of teachers and students with disabilities and gave valuable advice and guidance (47). Finally, Contis, et al (48) pointed out the international aspect of the chemistry enterprise. Currently ACS has 17% international members, with broad diversities in nationalities, ethnicities, languages, religions, and other characteristics. ACS is welcoming of these diversities and seeks to build inclusion and strength through diversity.

Conclusions Diversity remains a major workplace issue in the chemistry enterprise today, although much time and research funding have been expended on the topic for decades. For example, demographics determined via research investigations reveal a very low representation of URMs among faculty at research universities and of women among full professors at research universities. In comparison with the general populations of these underrepresented groups, a drastic discrepancy exists between their representations in academia versus the general population. It seems that there is an urgent need to attract people into chemistry from diverse backgrounds. A positive trend is that many chemical organizations have recognized the importance of diversity as a means to enhance recruitment or retention of talent, improve marketing of products, and broaden the scope and the perspectives for new ideas. ACS is one of the organizations that have consistently supported diversity and inclusivity. Obviously, continued efforts are desirable in the future. The many excellent diversity programs reviewed in the present article (and described in detail in this book) give us hope that future progress can be made. We owe them our gratitude for these successful programs and acknowledge particularly the people involved for their efforts. Hopefully these programs serve as models for other institutions to emulate and to build upon in the future. 7

Acknowledgments The authors thank the authors of the book chapters for sharing their data and perspectives. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by ACS or the U.S. Department of Agriculture. ACS and USDA are equal opportunity providers and employers.

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12. Anon. Academic Diversity: A Look at Race, Ethnicity, and Gender in Higher Education. http://www.acs.org/content/acs/en/policy/acsonthehill/briefings/ academic-diversity.html (accessed May 10, 2017). 13. Gurin, P.; Nagda, B. A.; Lopez, G. E. The Benefits of Diversity in Education for Democratic Citizenship. J. Social Issues 2004, 60 (1), 17–34. 14. Does Diversity Make a Difference? Three Research Studies on Diversity in College Classrooms; American Council on Education and American Association of University Professors: Washington, DC, 2000. 15. Smith, M. J.; Winberger, C.; Bruna, E. M.; Allesina, S. The scientific impact of nations: Journal placement and citation performance. Plos One 2014, 9, 1–6. 16. Hunt, V.; Layton, D.; Prince, S. Diversity Matters. McKinsey & Company: 2015. http://www.diversitas.co.nz/Portals/25/Docs/Diversity%20Matters. pdf (accessed May 10, 2017). 17. Freeman, R. B.; Huang, W. Collaborating with people like me: Ethnic coauthorship within the United States. J. Labor Economics 2015, 33 (S1, July), S289–S318; doi: 10.1086/678973. 18. Holt, M. Challenges of Diversity Management. http://smallbusiness. chron.com/challenges-diversity-management-3044.html (accessed May 10, 2017). 19. Greenberg, J. Diversity in the Workplace: Benefits, Challenges and Solutions. http://www.multiculturaladvantage.com/recruit/diversity/ diversity-in-the-workplace-benefits-challenges-solutions.asp (accessed May 10, 2017). 20. Joplin, J. R. W.; Daus, C. S. Challenges of leading a diverse workforce. The Academy of Management Executive 1997, 11, 32–47. 21. Dobbin, F.; Kalev, A. Why diversity programs fail. Harvard Business Review 2016, 94 (7), 14. 22. Nelson, D. J. Diversity of Science and Engineering Faculty at Research Universities. Diversity in the Scientific Community Volume 1: Quantifying Diversity and Formulating Success; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1255; Chapter 2. 23. Kuck, V. J. Smashing the Glass Ceiling in Chemistry Remains a Long-Range Goal. Diversity in the Scientific Community Volume 1: Quantifying Diversity and Formulating Success; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1255; Chapter 3. 24. Hernandez, R.; Stallings, D.; Iyer, S. The Gender and URM Faculty Demographics Data Collected by OXIDE. Diversity in the Scientific Community Volume 1: Quantifying Diversity and Formulating Success; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1255; Chapter 4. 25. Asay, P. A.; Paquin, J. D.; Arseneau, J. R.; Downing, V.; Roffman, M. S.; Kettlewell, K. D.; Berman, T.; Walton, H. M.; Fassinger, R. E. Career Success of Women in the Chemical Industry, Part 1: Finding a Way Through the Labyrinth. Diversity in the Scientific Community Volume 1: Quantifying Diversity and Formulating Success; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1255; Chapter 5. 9

26. Arseneau, J. R.; Asay, P. A.; Paquin, J. D.; Walton, H. M.; Downing, V.; Roffman, M. S.; Fassinger, R. E. Career Success of Women in the Chemical Industry, Part 2: Navigating Workplace Challenges. Diversity in the Scientific Community Volume 1: Quantifying Diversity and Formulating Success; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1255; Chapter 6. 27. Paquin, J. D.; Arseneau, J. R.; Asay, P. A.; Downing, V.; Roffman, M. S.; Walton, H. M.; Fassinger, R. E. Career Success of Women in the Chemical Industry, Part 3: Getting on the Same Page. Diversity in the Scientific Community Volume 1: Quantifying Diversity and Formulating Success; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1255; Chapter 7. 28. Salton, G. J.; Nelson, S. Gender and Thought Diversity in Chemistry. Diversity in the Scientific Community Volume 1: Quantifying Diversity and Formulating Success; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1255; Chapter 8. 29. Hall, A. K. Educational Outcomes from MARC Undergraduate Student Research Training. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 1. 30. Taylor, G. P.; Cassill, J. A.; Barea-Rodriguez, E. J. The Undergraduate Research Initiative for Scientific Enhancement (RISE) Program at the University of Texas at San Antonio. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 2. 31. DiMaggio, S. Xavier University of Louisiana: Routinely beating the odds. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 3. 32. Kosinski-Collins, M. S.; Godsoe, K.; Epstein, I. R. The Brandeis Science Posse: Building a Cohort Model Program to Retain Underserved Students in the Sciences. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 4. 33. Chmielewski, J.; Adolph, C. M.; Betancourt, S. K.; Blade, R.; Pulliam, C. J. The Chemistry Diversity Initiative at Purdue University. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 5. 34. Stallings, D.; Hernandez, R. Accelerating Change: #DiversitySolutions On Social Media. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 6. 35. Brown, D. R. Diversifying the STEM professional workforce by building capacity at a two-year college on the U.S.-Mexico border. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; 10

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ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 7. Lester, W. Diversity Efforts: University of California Berkeley and Other. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 8. Svoronos, P. From Introductory Chemistry at the Community College Level to post-Undergraduate Success: Strategies at Queensborough Community College that Secure the Success of Ethnically Diverse STEM Students. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 9. Colon, L. Increasing Diversity in the Chemical Sciences: Experiences and Lessons. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 10. Pagano, T. Making education and careers in chemistry accessible and successful for Deaf and Hard-of-Hearing students. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 11. Thomas, G.; Wilson-Kennedy, Z. Wanted! Diverse STEM professionals seek like-minded mentors, coaches, sponsors and advocates. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 12. Valdez, C.; Lopez, S. A. Taking charge of the lack of diversity in STEM from graduate school to the professoriate: Developing a national, non-profit organization. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 13. Varma-Nelson, P. Empowering effect of leadership roles in undergraduate education. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 14. Collins, S. N. Critical mass takes courage: Diversity in the chemical sciences. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 15. Bannochie, C. J. Alphabet Soup and the ACS: The History of LGBT Inclusion. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 16. Denio, A. A. Diversity: The ACS Senior Chemists Committee and Delaware’s ChemVets. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 17. 11

46. Booksh, K. Why are there so few Doctorates with Disabilities in Chemistry? Thoughts and Reflections. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 18. 47. Neybert, A. The Unconventional Chemist. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 19. 48. Contis, E. T.; McKlmon, R.; Miller, B. D. Energizing Global Thinking as a Dimension of ACS Diversity/Inclusion Efforts. Diversity in the Scientific Community Volume 2: Perspectives and Exemplary Programs; ACS Symposium Series; American Chemical Society: Washington, DC, 2017; Vol. 1256; Chapter 20.

12

Using Data To Quantify the Problem, Formulate Solutions and Measure Success

Chapter 2

Diversity of Science and Engineering Faculty at Research Universities Donna J. Nelson* Department of Chemistry, University of Oklahoma, Norman, Oklahoma 73019-9704, United States *E-mail: [email protected]

The most comprehensive demographic analysis of tenured and tenure track faculty in top 100 departments of science and engineering disciplines shows that women and minorities remain significantly underrepresented among faculty. There are still relatively few tenured and tenure-track female and minority faculty in these research university departments, even though a growing number and percentage of women and minorities are completing their PhDs in these fields. Qualified women and minorities are not becoming faculty in science and engineering disciplines in sufficient numbers. Although in some engineering disciplines, there is a better match between the representation of females among PhD recipients versus among faculty, these disciplines are the ones with very low percentages of females among PhD recipients. Generally, the percentage of women among science and engineering BS recipients has been fairly stagnant over the past few years, and undergraduate women are likely to find themselves without sufficient female faculty to serve as optimal role models and mentors. Underrepresented minorities (URMs) face many of the same issues as women do. In no discipline is there a critical mass of URMs, nor do the percentages of URM faculty approach the percentages of URMs in the general population. Furthermore, although the numbers of female URM faculty are generally increasing, those numbers still remain at or near zero in the top 50 departments of most STEM disciplines.

© 2017 American Chemical Society

Introduction For decades, many women, URMs, universities, and organizations, worked to increase the representation of women and URMs among faculty at top research universities. In spite of valiant efforts, progress and change were slow, although many options and potential solutions were attempted. From their surroundings, it was apparent to women and minorities that disparities and barriers existed. However, there was no way to measure the disparities nor the extent of success, if any, especially at higher levels. Data disaggregated by race and gender had long been available about STEM BS recipients and PhD recipients, since the 1960s and 1970s respectively, but there were none for corresponding faculty. This meant that demographics of the faculty hiring pool were established, but neither the numbers nor the exact representation of women nor URMs were available. With no complete faculty data, there was little understanding of the barriers to equality or steps needed to accomplish or approach it. A data-driven analysis of the barriers or steps in the “academic pipeline” beyond PhD recipients was impossible. Disparities for women and URM faculty obviously existed in each STEM discipline, but lack of data prevented comparison or pattern recognition; this caused each discipline to be analyzed and planned separately. In order to gather faculty data, survey samples were initially used, but statistics must be applied to samples, which invalidated results if the sample size was small. Other than data from survey samples, the only “data” available were from attendee observations at meetings and other gatherings. While there were sufficient women faculty to gather useful, but somewhat approximate, data via survey samples, there were insufficient URM faculty for this. For underrepresented minorities, faculty numbers were so small, especially when disaggregated by rank and gender, in order to have accurate numbers the only solution was to collect the whole population. In this way, statistics would not need to be applied to the data, because the number of all faculty would be merely counted. Many reasons were cited about the need for these data: (1) Comparing faculty data before versus after a program implementation would enable discerning the effect of the program. (2) The faculty demographics would provide benchmarks for universities and departments to compare against their own data. (3) If faculty demographics were collected over a number years, it would be possible to tell the progress or lack of progress over time, in each discipline. (4) Disciplines, departments, and universities would be able to compare data against each other and to measure and quantify their relative progress. Our first faculty survey was for chemistry and was carried out in FY2001. It provided the full population of tenured and tenure track faculty, disaggregated by race, by rank, and by gender, at the top 50 chemistry departments, as ranked by the National Science Foundation (NSF). Our survey provided the numbers that many women and URMs in chemistry had long desired and generated discussion and enabled research in diversity that was not possible previously. The NSF named our surveys “The Nelson Diversity Surveys.” Researchers in other STEM disciplines asked us to survey their disciplines similarly, which we did for 13 additional STEM disciplines in FY2002. 16

Nelson Diversity Surveys were carried out twice more, for 15 STEM disciplines, in FY2005 and FY2007. These three surveys each provided a snapshot of tenured and tenure track faculty demographics in one year, disaggregated by race, by rank, and by gender. In order to determine change over time of faculty demographics, it was desirable to have demographics for more than three points in time. Therefore, we decided to carry out a Nelson Diversity Survey for one additional year, and those data are reported herein for FY2012.

Methodology In order to investigate the race/ethnicity, rank, and gender of faculty, we surveyed top research departments of fifteen science and engineering disciplines. Our data were gathered by surveying the top 100 departments in each of fifteen science and engineering disciplines, as ranked by the NSF according to research funds expended (1). Each department chair was asked to provide the gender, race/ethnicity, and rank of each tenured or tenure track faculty member. Data received were entered into tables, which are provided in the Appendix. For each discipline, we selected all pertinent departments in each university that ranked in the top 100, according to the most recent National Science Foundation annual report on academic research expenditures available at the time of data collection. The top 100 universities were different for each discipline. Over 90% of the departments in our sample are also located in universities classified in either the Doctoral/Research Universities-Extensive category or the Doctoral/Research Universities—Intensive category of the Carnegie Classification of Institutions of Higher Education. For each of the top 100 departments in research expenditures, department chairs were asked to report the race/ethnicity (Asian, Black, White, Hispanic, and Native American), rank (assistant, associate, and professor) and the gender of tenured and tenure-track faculty for fiscal year 2012. In a limited number of instances, data were unavailable from department chairs and were collected instead from other sources, such as department websites and published directories. If a university had both a math department and a department of statistics or applied mathematics, then we included both departments in the Appendix math tables and noted these by #. These additional departments were sufficiently few that still gather data for the full population in math. In biological sciences and in earth sciences, we surveyed all pertinent departments of each university (sometimes over 15 departments per university). In each discipline, some departments did not respond or declined to participate; in these cases, we gathered the information from departmental websites, so that we had the full population, rather than a sample. Universities for which departmental data were gathered from a source other than the chair(s) or the(ir) designee(s) are marked in the Appendix tables by **. In cases in which the NSF listed fewer than 100 departments for a discipline, we surveyed all that were provided. For example, NSF ranked only 40 astronomy departments at the time of the first survey. Engineering disciplines and social sciences 17

disciplines each had been grouped by NSF, and the research expenditures of the group were used to rank the top 100 universities. This caused an occasional sub-disciplinary department to be included among the top 100, even though it had no research expenditures reported (or might not even exist). We omitted those departments. Therefore, although it was still possible to sort and rank research funding expenditures by sub-discipline, some sub-disciplines have fewer than 100 departments, as seen in the Appendix tables.

Women Table 1 contains a summary of data for female students and faculty in each of 15 science and engineering disciplines at the top 50 departments in the United States, as ranked by the National Science Foundation (NSF) (1). The right side of the table summarizes faculty data from Appendix tables, which each contain faculty data for 50 departments in one discipline, disaggregated by race, rank, and gender. In these Appendix survey data tables, numbers before the decimal point refer to the total number of faculty in that group, while the numbers after the decimal point refers to the women there. The data in the left side of the summary table pertain to BS and PhD attainment data from the NSF webCASPAR database (1).

BS and PhD Recipients The first indicator of women’s presence in academia comes from analysis of BS recipients. The first two columns in Table 1 reveal little change in the representation of women among BS recipients between 2010 and 2011—all disciplines except astronomy and physics showed less than 1% change in the percent of BS recipients who are women. Astronomy saw a significant increase (36.9% in 2010 compared to 38.3% in 2011), while physics had a significant decrease (20.6% to 18.9%). Of the 13 remaining disciplines with no significant change, seven (chemistry, math, computer science, chemical engineering, mechanical engineering, economics, and political science) had a slight decrease, four (civil engineering, sociology, biological sciences, and earth sciences) experienced an increase, and two (electrical engineering and psychology) remain the same. The percentage of women among BS recipients is important because BS recipients are the source of PhD candidates and, by extension, professors. A small source (less than 25% to 30%) represents the first stage in their underrepresentation and could be a factor working against women entering academia. Currently, computer science (16.8%), physics (18.9%), civil engineering (22.0%), electrical engineering (9.9%), and mechanical engineering (11.3%) all have a low representation of females among BS recipients, constituting a small source for females in the academic pipeline for these disciplines. 18

Table 1. Females Among Professors by Rank and Discipline at Top 50 Departments Discipline

Students

Professors FY2012

PhD8796

BS2010

BS2011

Chemistry

49.8%

49.0%

27.2%

Math

43.4%

43.1%

Computer Sci

16.9%

Astronomy

PhD9706

asst

assoc

prof

all

33.0%

25.5%

23.1%

13.1%

16.8%

23.0%

29.5%

26.5%

20.7%

9.6%

14.5%

16.8%

19.9%

21.7%

20.5%

18.9%

12.3%

15.7%

36.9%

38.3%

17.1%

23.8%

23.1%

25.0%

16.2%

19.2%

Physics

20.6%

18.9%

11.5%

14.7%

18.5%

15.7%

7.5%

10.3%

Chemical Engr

31.9%

31.0%

18.3%

24.2%

32.8%

23.8%

9.8%

16.9%

Civil Engr

21.5%

22.0%

13.5%

23.3%

32.5%

17.5%

10.0%

16.3%

Electrical Engr

9.9%

9.9%

9.2%

12.6%

17.9%

10.9%

7.7%

10.0%

Mechanical Engr

11.5%

11.3%

7.8%

12.4%

21.3%

14.5%

7.8%

12.0%

Economics

29.3%

28.9%

26.4%

31.2%

29.5%

18.3%

9.4%

16.1%

Political Science

50.9%

50.6%

33.3%

39.8%

40.4%

35.1%

22.3%

30.3%

Sociology

69.5%

69.8%

54.6%

61.6%

63.6%

54.2%

33.3%

45.4%

Psychology

77.0%

77.0%

60.7%

68.1%

50.3%

43.8%

32.7%

38.7%

Biological Sci

59.0%

59.5%

40.8%

47.1%

32.5%

31.2%

18.8%

24.8%

Earth Sciences

39.5%

40.0%

23.0%

32.6%

35.2%

28.4%

12.1%

20.2%

Women are making slow increases in PhD attainment, as seen by comparing the third and fourth columns of Table 1. The percentage of PhD recipients that are female increased significantly between 1987-1996 and 1997-2006 in every discipline. However, despite this general increase across decades, the percentage of women receiving PhDs is still low in many disciplines. Averaging across the second decade, between 1997 and 2006, women made up less than 25% of PhD recipients in computer science (21.7%), astronomy (23.8%), physics (14.7%), chemical engineering (24.2%), civil engineering (23.3%), electrical engineering (12.6%), and mechanical engineering (12.4%). While the increase in attainment shows improvement, the fact that seven of the fifteen disciplines still have such a small source shows that there is still much improvement needed. Another important comparison is that of BS recipients to PhD recipients (columns two and four of Table 1). This reveals the number of female BS recipients who go on receive a PhD and, conversely, the number who leave the academic pipeline at this point. In most disciplines the percentage of BS recipients 19

that are female is higher than that of PhD recipients; female BS recipients are underutilized. However, five disciplines over utilize female BS recipients—there are a higher percentage of women receiving PhDs than BSs; these are computer science (21.7% vs 16.8%, respectively), civil engineering (23.3% vs 22.0%), electrical engineering (12.6% vs 9.9%), mechanical engineering (12.4% vs 11.3%), and economics (31.2% vs 28.9%). The ten disciplines that underutilize female BS recipients are losing women disproportionately at this point, and should take note, if they are to retain them throughout the academic pipeline.

Critical Mass In order to facilitate women to achieve highest ranks, there must be sufficient women to make the necessary changes inside the disciplines. This makes the measure of critical mass—defined as the minimum proportion of individuals necessary to effect substantial change—of high importance (2). Generally, critical mass is deemed to be between 15% and 30%. In order to create changes that would make academic positions more desirable for women, and thus draw more women into the field, a critical mass of women professors, specifically at the highest ranks and positions, must be attained (2). Considering the representation of women among all ranks of professor combined (the final column in Table 1), it appears that critical mass has been attained generally. All disciplines examined in this study except math (14.5%), computer science (14.5%), physics (10.4%), electrical engineering (10.0%), and mechanical engineering (12.0%) have at least 15% females among professors. However, a problem at individual ranks becomes apparent. While all disciplines have attained a critical mass at the assistant professor level (column five), and all but electrical engineering (10.9%) and mechanical engineering (14.5%) have done so at the associate professor level (column six), there is a noticeable drop in the percentage of women who are “full” professors (column seven). Only five of the fifteen disciplines studied—astronomy (16.2%) political science (22.3%), sociology (33.3%), psychology (32.7%), and biological sciences (18.8%)—have attained a critical mass of women among tenured professors. Even among those disciplines that have reached a critical mass, none have come near the 51% that makes up the general population (3). In fact, the highest, sociology, only reaches 33.3%, nearly 20% away from matching the population of the United States as a whole. While female professors have generally attained critical mass, they are concentrated at the lowest ranks. Tenured “full” professors can more easily speak against discrimination or unfair practices, working to effect change, but there is greater risk for assistant and associate professors to do so. Thus, the underrepresentation of women as “full” professors perpetuates a cycle in which women are discouraged from academic careers, which in turn means that there are too few tenured professors to change the conditions that discourage the women in the first place. The loss of women between the ranks of assistant, associate, and full professor must be remedied in order to break this cycle and facilitate change. 20

Same-Gender Mentors Because most individuals are most comfortable in environments that include others who are similar to them, underrepresentation of women can impact the representation of women in the student body. Individuals tend to seek out role models and mentors that are similar to them. When there are insufficient mentors, female students may feel alienated or unsupported (4). Also, the mentor’s time and resources are spread too thinly amongst her various mentees, causing the quantity and quality of interactions to decline. Both outcomes will impact student success and retention adversely. These can lead to the feeling that women have no place in academia and that their needs will be ignored, leading to discouragement and driving students from the field (4). The data in Table 1 support this phenomenon for women in academia. The proportion of women seeking bachelor degrees is much greater than that of female professors, particularly higher-ranking professors. For example, despite making up nearly half (49.0%) of chemistry undergraduates, females account for only 16.8% of professors of all ranks in the top 50 chemistry departments, and 13.0% of full professors. A greater disparity exists in psychology, where females make up 77.0% of the undergraduate population, only 32.7% of professors are female. In two disciplines, chemistry (49.0% BS to 16.8% faculty) and math (43.1% and 14.5%) the percentage of female BS recipients is larger than the percentage of female professors of all ranks by a factor of almost three. In no discipline does the percentage of female full professors exceed that of female undergraduates, and the few that are close only are so only because the percentages of undergraduate females are so low. In electrical engineering, for example, there is only a 2.2% difference between the proportion of female undergraduate students and full professors. However, only 7.7% of full professors in that department are female (compared to 9.9% of undergraduates), so the low numbers are still a cause for concern. This trend is mirrored in the percentage of professors of all ranks. In all disciplines except mechanical and electrical engineering, female undergraduates account for a significantly higher proportion of their respective population than do female professors. When the proportions are close, this is due to a lack of female undergraduates, as opposed to an abundance of female professors. Hiring Pool Faculty are hired as assistant professors from a pool of candidates who have received PhDs. Comparing the percentage of female PhD recipients (Table 1, column four) versus the percentage of female assistant professors (column five) reveals how well disciplines utilize their hiring pools. If the representation of women is higher in PhD attainment versus that in assistant professors, then women PhDs are underutilized, signaling that women are leaving the academic pipeline faster than men are. This loss of representation is known as a “leaky pipeline” and suggests that conditions exist that prevent or deter women from becoming faculty, whether that be unfair hiring practices or non-ideal conditions in departments that students observe. 21

In 2012, seven disciplines underutilized their hiring pools. The greatest underutilization is in psychology (18.3% difference between the representation of women among PhD recipients versus assistant professors) and biological sciences (14.6%). Chemistry (7.6%), math (3.1%), economics (1.7%), computer science (1.2%), and astronomy (0.7%) also showed underutilization. Conversely, physics, chemical engineering, civil engineering, electrical engineering, mechanical engineering, political science, sociology, and earth sciences each had a higher percentage of female assistant professors than of female PhD recipients and were therefore over-utilizing their hiring pools. Disciplines characterized by hiring pool underutilization should make academia more appealing to female PhD recipients, in order to encourage women to enter that profession. They should also review hiring practices in order to retain women at this stage in the academic pipeline.

Summary of Deficiencies Disciplines with a larger number of deficiencies can be expected to have more problems for underrepresented groups and to take longer to remedy them. Such categorization can also help identify areas that each discipline needs to improve. Therefore, it is desirable to compare the relative number of deficiencies in disciplines. In order to facilitate this, in Tables 1-12 disciplines are grouped according to patterns in their deficiencies. Group 1: The disciplines in life sciences and social sciences have reasonably sized sources to their pipelines, women have attained critical mass in faculty, but their hiring pools are underutilized; these have one deficiency each and are grouped at the bottom of Tables 1-12. Group 2: Physics, astronomy, and engineering have small sources for their pipelines, no critical mass in faculty, but overutilization of their hiring pools, and they are in the middle of the tables. This group of disciplines shows characteristics opposite to life sciences and social sciences; each has two deficiencies, but overutilization of hiring pools. Group 3: Chemistry, math, and computer science have reasonably sized sources, underutilization of their hiring pools, barely critical mass among faculty, and they are at the top of the tables. Each discipline has two deficiencies, in spite of a reasonably sized source.

Analysis and Comparison of Lower-Ranking Departments Table 2 contains analogous faculty data for the next 50 departments (51-100) and the top 100 departments as a whole. This table shows that the percentage of females in academia is essentially the same in the top 50 departments as in the next 50, except for a few disciplines. In astronomy, mechanical engineering, and biological sciences, women have significantly higher representation among faculty of all ranks in the first 50 departments than in the second 50, while economics, psychology, and earth sciences follow the opposite trend. 22

Table 2. Females Among Professors by Rank and Discipline at Top 100 Departments Discipline

Departments 51 - 100

Departments 1 - 100

asst

assoc

prof

all

asst

assoc

prof

all

Chemistry

26.8%

19.4%

11.4%

16.2%

26.1%

21.3%

12.4%

16.6%

Math

29.9%

22.7%

9.6%

16.4%

27.9%

21.6%

9.6%

15.2%

Computer Sci

20.3%

13.6%

10.9%

13.6%

20.4%

16.5%

11.8%

14.8%

Astronomy

26.3%

15.7%

10.6%

14.8%

24.4%

21.6%

14.3%

17.7%

Physics

22.7%

17.5%

7.6%

12.4%

20.4%

16.5%

7.5%

11.2%

Chemical Engr

29.1%

17.4%

11.6%

16.7%

31.1%

20.7%

10.6%

16.8%

Civil Engr

25.0%

19.8%

6.5%

15.1%

29.3%

18.5%

8.8%

15.9%

Electrical Engr

15.3%

12.0%

8.4%

10.7%

16.9%

11.4%

7.9%

10.2%

Mechanical Engr

18.4%

6.6%

5.0%

8.5%

20.1%

11.4%

6.8%

10.7%

Economics

31.5%

22.9%

12.2%

19.4%

30.5%

20.5%

10.6%

17.6%

Political Science

42.7%

30.1%

18.6%

28.8%

41.5%

33.0%

20.8%

29.7%

Sociology

55.8%

54.6%

34.1%

46.0%

60.0%

54.4%

33.6%

45.7%

Psychology

56.1%

48.6%

33.9%

43.2%

53.3%

46.0%

33.2%

40.7%

Biological Sci

34.7%

29.5%

20.4%

26.1%

33.4%

30.5%

19.4%

25.3%

Earth Sciences

35.1%

28.6%

15.6%

22.7%

35.2%

28.5%

13.4%

21.3%

Underrepresented Minorities (URMs) The United States Census Bureau estimates that, in 2012, the representations of Blacks, Hispanics, and Native Americans (known collectively as underrepresented minorities or URMs) in the general US population were 12.6%, 17.2%, and 0.9%, respectively (3). However, those representations are not reflected in the percentages of URM professors. As seen in Tables 3, 5, and 7, URM professors at any rank have not attained a critical mass in any of the 15 disciplines studied. Nor have any of the percentages approached the percentages of URMs in the general population. Many of the same issues impacting female professors are observed for URMs, except to a greater degree. Blacks Table 3 contains data analogous to Table 1, but for Black students and professors. It reveals a severe underrepresentation of Black professors, 23

particularly full professors. In all but three disciplines (political science, sociology, and psychology) Blacks are less than 3% of professors of all ranks. In sociology, which has the highest percentage, Blacks account for only 7.7% of all professors and 6.7% of full professors. Five disciplines (math, computer science, physics, biological sciences, and earth sciences) Blacks have percentages of full professors that are less than 1%, ranging as low as 0.4% in computer science.

Table 3. Blacks Among Professors by Rank and Discipline at Top 50 Departments Discipline

Students

Professors FY2012

PhD8796

BS2010

BS2011

Chemistry

8.1%

8.0%

1.8%

Math

5.7%

5.3%

11.3%

Astronomy

PhD9706

asst

assoc

prof

all

3.4%

3.0%

2.8%

1.0%

1.6%

1.4%

2.8%

1.3%

1.5%

0.9%

1.1%

11.1%

1.3%

3.3%

2.8%

1.9%

0.4%

1.2%

2.1%

1.5%

0.7%

0.9%

2.6%

3.3%

1.6%

2.1%

Physics

3.3%

3.3%

1.1%

2.0%

0.7%

0.6%

0.9%

0.8%

Chemical Engr

4.4%

4.5%

2.0%

3.3%

2.7%

4.6%

2.1%

2.7%

Civil Engr

4.0%

3.8%

2.4%

3.6%

1.9%

2.6%

1.1%

1.6%

Electrical Engr

7.4%

7.1%

2.0%

4.0%

3.1%

2.2%

1.5%

1.9%

Mechanical Engr

3.2%

3.4%

1.3%

3.6%

5.2%

2.9%

1.5%

2.6%

Economics

5.9%

5.8%

4.1%

4.1%

1.3%

2.1%

1.1%

1.3%

Computer Sci

Political Science

10.6%

11.0%

7.6%

8.2%

5.8%

4.5%

3.7%

4.4%

Sociology

18.3%

19.4%

6.7%

9.8%

8.4%

9.0%

6.7%

7.7%

Psychology

12.4%

12.6%

4.0%

5.9%

7.0%

3.6%

2.0%

3.3%

Biological Sci

7.9%

7.8%

1.9%

3.1%

2.2%

2.1%

0.8%

1.4%

Earth Sciences

2.0%

1.9%

0.6%

1.2%

1.4%

2.1%

0.7%

1.2%

In all disciplines the percentage of Black undergraduate students is greater than the percentage of Black professors. For instance, in computer science, only 0.4% of full professors are Black, while 11.1% of BS recipients are. There are not enough Black professors to serve as mentors to the Black undergraduate population, which ultimately can cause Blacks to become discouraged and choose a new career path.

24

Table 4 reveals the percentage of Blacks among faculty members in the second 50 and top 100 departments. Data for the first and second 50 departments are essentially equal, with the exception of a 2.7% difference in astronomy.

Table 4. Blacks Among Professors by Rank and Discipline at Top 100 Departments Discipline

Departments 51 - 100

Departments 1 - 100

asst

assoc

prof

all

asst

assoc

prof

all

Chemistry

2.8%

4.5%

1.0%

2.1%

2.9%

3.7%

1.0%

1.8%

Math

2.4%

1.9%

1.8%

1.9%

1.8%

1.7%

1.2%

1.4%

Computer Science

3.9%

0.5%

0.6%

1.2%

3.3%

1.3%

0.4%

1.2%

Astronomy

2.6%

6.7%

4.8%

4.8%

2.6%

4.6%

2.7%

3.1%

Physics

0.8%

0.4%

0.3%

0.4%

0.8%

0.5%

0.6%

0.6%

Chemical Engr

3.4%

1.4%

1.6%

1.9%

3.0%

3.1%

1.9%

2.4%

Civil Engr

3.6%

2.8%

0.8%

2.1%

2.6%

2.7%

1.0%

1.8%

Electrical Engr

5.4%

2.7%

1.3%

2.4%

4.0%

2.4%

1.4%

2.1%

Mechanical Engr

5.1%

2.5%

2.2%

2.9%

5.1%

2.7%

1.7%

2.7%

Economics

1.4%

4.2%

1.8%

2.2%

1.4%

3.1%

1.4%

1.7%

Political Science

5.9%

6.8%

5.5%

6.0%

5.8%

5.5%

4.4%

5.1%

Sociology

10.6%

8.3%

5.0%

7.5%

9.4%

8.7%

6.1%

7.6%

Psychology

6.4%

4.4%

3.3%

4.3%

6.7%

4.0%

2.5%

3.7%

Biological Sci

2.9%

1.7%

1.4%

1.8%

2.5%

2.0%

1.0%

1.6%

Earth Sciences

1.5%

1.1%

1.6%

1.5%

1.5%

1.7%

1.1%

1.3%

Hispanics Table 5 summarizes the representation of Hispanics among students and faculty in the top 50 departments. It reveals that Hispanics are underrepresented at all levels of academia. The percentages of Hispanics increase at lower ranks, but the highest percentage of Hispanic professors is merely 9.7%, in psychology. This ranges down to 2.8% in computer science and in electrical engineering. Numbers are even lower for full professors. In computer science, Hispanics make up only 1.2% of full professors, and only 1.4% in earth sciences. Civil engineering has the highest percentage of Hispanic full professors - 5.0%, but this is still less than one-third of the representation of Hispanics in the US population. 25

Table 5. Hispanics Among Professors by Rank and Discipline at Top 50 Departments Discipline

Students

Professors FY2012

PhD8796

BS2010

BS2011

Chemistry

7.6%

8.1%

3.2%

Math

6.8%

7.4%

Computer Sci

8.8%

Astronomy

PhD9706

asst

assoc

prof

all

3.7%

3.6%

5.6%

3.1%

3.6%

2.2%

3.6%

3.3%

1.9%

2.9%

2.8%

9.3%

1.6%

2.7%

2.8%

1.9%

1.2%

1.7%

9.7%

8.0%

2.0%

2.9%

4.3%

3.3%

1.8%

2.5%

Physics

5.9%

6.1%

2.6%

2.8%

4.2%

2.2%

2.3%

2.6%

Chemical Engr

7.7%

7.5%

2.8%

4.0%

7.1%

5.3%

4.1%

4.9%

Civil Engr

10.9%

10.6%

3.5%

4.8%

7.1%

7.3%

5.0%

6.0%

Electrical Engr

10.0%

11.1%

2.3%

3.8%

2.8%

5.6%

2.6%

3.4%

Mechanical Engr

8.5%

8.7%

1.8%

3.5%

4.6%

3.7%

2.0%

2.9%

Economics

7.5%

7.5%

2.8%

4.6%

6.3%

4.3%

2.4%

3.7%

Political Science

11.2%

12.1%

3.4%

4.3%

7.6%

6.7%

2.2%

4.8%

Sociology

14.0%

14.9%

4.7%

6.3%

9.2%

7.1%

4.4%

6.1%

Psychology

11.6%

12.6%

4.2%

6.5%

9.7%

5.4%

2.7%

4.6%

Biological Sci

8.7%

9.1%

2.8%

4.5%

4.3%

4.2%

2.5%

3.3%

Earth Sciences

5.6%

5.6%

2.0%

3.1%

5.2%

3.0%

1.4%

2.5%

Hispanic undergraduates also lack same-race mentors. The percentage of Hispanic among B.S. recipients is higher among all disciplines than among professors at any rank, often twice as large or more. In psychology, with 12.6% of BS recipients Hispanic, only 2.7% of full professors and 4.6% of all professors are Hispanic. Table 6 compiles the percentage of Hispanics among faculty members in the second 50 and top 100 departments. There is no significant difference in any discipline between the representation of Hispanic professors of all ranks in the first and second 50 departments.

26

Table 6. Hispanics Among Professors by Rank and Discipline at Top 100 Departments Discipline

Departments 51 - 100

Departments 1 - 100

asst

assoc

prof

all

asst

assoc

prof

all

Chemistry

5.3%

4.1%

1.1%

2.6%

4.4%

4.9%

2.3%

3.1%

Math

2.7%

4.5%

3.0%

3.3%

3.1%

3.1%

3.0%

3.0%

Computer Sci

3.4%

1.3%

2.0%

2.0%

3.0%

1.6%

1.5%

1.8%

Astronomy

7.9%

1.1%

1.8%

2.8%

5.7%

2.5%

1.8%

2.6%

Physics

4.1%

4.4%

3.1%

3.6%

4.2%

3.1%

2.6%

3.0%

Chemical Engr

8.1%

5.6%

5.6%

6.1%

7.6%

5.4%

4.7%

5.4%

Civil Engr

5.6%

3.6%

3.3%

4.0%

6.5%

5.8%

4.4%

5.2%

Electrical Engr

0.5%

3.0%

1.3%

1.7%

1.9%

4.5%

2.2%

2.8%

Mechanical Engr

1.4%

2.1%

1.2%

1.5%

3.3%

3.1%

1.7%

2.4%

Economics

7.2%

3.7%

3.7%

4.6%

6.8%

4.0%

3.0%

4.1%

Political Science

6.9%

5.9%

2.5%

4.8%

7.3%

6.4%

2.3%

4.8%

Sociology

6.0%

7.5%

5.3%

6.2%

7.8%

7.3%

4.7%

6.2%

Psychology

4.9%

5.4%

2.4%

3.8%

7.2%

5.4%

2.6%

4.3%

Biological Sci

7.0%

5.4%

2.1%

4.1%

5.4%

4.7%

2.3%

3.6%

Earth Sciences

1.2%

3.4%

1.6%

1.9%

3.5%

3.1%

1.5%

2.2%

Native Americans Table 7 summarizes the representation of Native Americans among students and faculty in the top 50 departments. This table shows that, not only are Native Americans underrepresented among professors in all 15 disciplines, they are not represented at all, in any rank, in five disciplines—math, mechanical engineering, economics, political science, and sociology. Despite Native Americans being 1.2% of the U.S. population, in no professor rank do they surpass 1.0%. Although Native Americans do make up 1.0% of psychology assistant professors, there are no Native American full professors in the field. Only six fields—chemistry, computer science, astronomy, physics, biological sciences, and earth sciences—have any Native American full professors, with the highest percentage being 0.23% in astronomy.

27

Table 7. Native Americans Among Professors by Rank and Discipline at Top 50 Departments Discipline

Students

Professors FY2012

PhD8796

BS2010

BS2011

Chemistry

0.6%

0.8%

0.3%

Math

0.5%

0.8%

Computer Sci

0.7%

Astronomy

PhD9706

asst

assoc

prof

all

0.6%

-

-

0.09%

0.06%

0.2%

0.3%

-

-

-

0.00%

0.9%

0.3%

0.5%

-

0.21%

0.11%

0.13%

0.9%

0.3%

0.3%

0.4%

-

-

0.23%

0.14%

Physics

0.8%

0.8%

0.3%

0.3%

-

-

0.07%

0.05%

Chemical Engr

0.6%

0.5%

0.3%

0.5%

0.55%

-

-

0.11%

Civil Engr

0.6%

0.9%

0.4%

0.4%

0.75%

0.29%

-

0.22%

Electrical Engr

0.5%

0.6%

0.2%

0.4%

-

0.20%

-

0.05%

Mechanical Engr

0.5%

0.7%

0.2%

0.7%

-

-

-

0.00%

Economics

0.5%

0.7%

0.2%

0.3%

-

-

-

0.00%

Political Science

0.8%

1.0%

0.4%

0.6%

-

-

-

0.00%

Sociology

1.0%

1.2%

0.7%

0.9%

-

-

-

0.00%

Psychology

0.8%

0.9%

0.5%

0.8%

1.00%

0.68%

-

0.35%

Biological Sci

0.7%

0.9%

0.3%

0.6%

0.70%

0.18%

0.16%

0.28%

Earth Sciences

1.1%

0.9%

0.3%

0.9%

0.86%

0.23%

0.09%

0.27%

Having so many departments with no Native American professors poses a problem; in some fields there are no professors, in any of the top 50 research universities, to serve as role models for Native American students. Those students will not receive mentoring needed, and academia can seem unwelcoming to them. These numbers are sufficiently low that, even if a Native American professor in a student’s field exists, that professor may work at a different university, and it is likely that some students may never have contact with a professor in their fields. This may contribute to the low percentages of Native Americans among BS recipients, which range from 0.3% in astronomy to 1.2% in sociology. Table 8 reveals data on Native Americans among faculty members in the second 50 and top 100 departments. Once again, the representation of Native Americans among professors of all ranks in the top 50 departments is essentially equal to that of the representation in the second 50 departments.

28

Table 8. Native Americans Among Professors by Rank and Discipline at Top 100 Departments Discipline

Chemistry Math

Departments 51 - 100

Departments 1 - 100

asst

assoc

prof

all

asst

assoc

prof

all

-

-

0.28%

0.17%

-

-

0.16%

0.10%

-

0.71%

-

0.17%

-

0.32%

-

0.07%

0.48%

0.26%

-

0.18%

0.22%

0.23%

0.07%

0.15%

-

-

0.44%

0.26%

-

-

0.30%

0.18%

Physics

-

0.40%

-

0.08%

-

0.17%

0.05%

0.06%

Chemical Engr

-

0.69%

0.26%

0.30%

0.30%

0.34%

0.11%

0.19%

Civil Engr

-

0.40%

-

0.12%

0.43%

0.34%

-

0.19%

Electrical Engr

-

-

-

-

-

0.11%

-

0.03%

Mechanical Engr

-

0.41%

-

0.10%

-

0.16%

-

0.04%

Economics

-

-

-

-

-

-

-

-

Political Science

0.35%

0.29%

-

0.19%

0.16%

0.13%

-

0.08%

Sociology

0.50%

0.83%

0.30%

0.52%

0.23%

0.36%

0.11%

0.21%

Psychology

0.61%

0.26%

0.15%

0.29%

0.80%

0.48%

0.06%

0.32%

Biological Sci

0.14%

0.39%

0.13%

0.19%

0.46%

0.26%

0.15%

0.25%

Earth Sciences

0.77%

0.38%

0.15%

0.34%

0.82%

0.29%

0.11%

0.29%

Computer Science

Astronomy

Asians Table 9 summarizes the representation of Asians among students and faculty in the top 50 departments. Although Asians are a minority, just 5.1% of the population of the United States, they are not an underrepresented minority (URM). In each discipline studied, the percentage of Asian professors is higher than the percentage of Asians in the nation, except full professors in political science, sociology, and psychology. In those three fields, the percentages are close; Asians account for 4.2%, 4.9%, and 4.2%, respectively, of full professors in each of the disciplines.

29

Table 9. Asians Among Professors by Rank and Discipline at Top 50 Departments Discipline

Students

Professors FY2012

BS2010

BS2011

PhD8796

PhD9706

asst

assoc

prof

all

Chemistry

15.6%

15.3%

12.6%

11.7%

24.5%

18.3%

8.8%

13.1%

Math

11.1%

11.6%

15.4%

11.3%

31.0%

24.7%

15.9%

20.0%

Computer Sci

9.2%

9.9%

17.3%

19.2%

35.4%

32.3%

26.0%

29.4%

Astronomy

10.6%

6.2%

6.2%

7.2%

14.5%

12.5%

8.9%

10.6%

Physics

7.1%

7.4%

15.1%

11.7%

22.3%

16.6%

11.9%

14.2%

Chemical Engr

15.3%

14.0%

18.2%

17.5%

26.8%

22.5%

15.9%

19.2%

Civil Engr

8.9%

9.3%

19.6%

15.2%

26.5%

17.2%

14.6%

17.6%

Electrical Engr

17.5%

17.9%

26.3%

25.5%

37.9%

33.7%

25.1%

29.1%

Mechanical Engr

9.0%

9.0%

24.5%

18.3%

35.9%

24.5%

24.9%

27.0%

Economics

19.0%

18.2%

11.4%

13.3%

24.1%

11.1%

9.4%

13.4%

Political Science

7.1%

7.0%

5.4%

5.0%

11.2%

8.1%

4.2%

7.0%

Sociology

7.5%

6.7%

6.9%

6.0%

12.1%

5.0%

4.9%

6.4%

Psychology

7.0%

6.7%

2.5%

4.6%

12.0%

10.0%

4.2%

7.1%

Biological Sci

17.5%

17.1%

11.5%

13.9%

22.0%

14.5%

8.8%

13.1%

Earth Sciences

3.7%

3.2%

6.2%

5.9%

16.0%

13.9%

7.9%

10.8%

Asians have attained a critical mass in six disciplines—math, computer science, chemical engineering, civil engineering, electrical engineering, and mechanical engineering. In addition, they are close to attaining critical mass in chemistry, astronomy, physics, economics, biological sciences, and earth sciences. As with other races, the percentage of Asians decreases as rank increases. However, Asians constitute a higher percentage among professors than Hispanics and Native Americans at all ranks in all disciplines, and higher than Blacks in all disciplines except sociology. Furthermore, although Asians make up significantly less of the population than do women, their representation is higher than women in math, computer science, physics, chemical engineering, civil engineering, electrical engineering, and mechanical engineering. Despite Asian professors having achieved a critical mass in almost all disciplines at all ranks, Asian undergraduates only have a critical mass in four disciplines. This favorable ratio provides students better access to mentors 30

and role models, which in turn helps Asian undergraduates achieve successful academic careers. Table 10 shows the percentage of Asians among faculty members in the second 50 and top 100 departments. Representation of Asian professors at all ranks generally increases from the first 50 to the second 50 departments. The disciplines of chemistry, astronomy, physics, chemical engineering, civil engineering, mechanical engineering, sociology, and biological sciences all experience a significant increase in Asians among faculty, while only in earth sciences does their representation significantly decrease in the second 50 departments.

Table 10. Asians Among Professors by Rank and Discipline at Top 100 Departments Discipline

Departments 51 - 100 asst

assoc

Chemistry

28.5%

Math

35.6%

Computer Sci

Departments 1 - 100

prof

all

asst

assoc

prof

all

15.7%

11.3%

15.7%

26.3%

18.9%

16.7%

20.7%

32.9%

17.0%

9.8%

14.2%

22.1%

16.2%

20.3%

32.9%

35.9%

23.0%

29.3%

34.3%

33.9%

24.9%

29.4%

Astronomy

14.5%

20.2%

12.8%

14.8%

14.5%

15.4%

10.2%

12.1%

Physics

24.0%

15.5%

Chemical Engr

30.4%

20.8%

15.9%

17.4%

23.1%

16.3%

13.4%

15.4%

21.4%

23.3%

28.4%

21.7%

18.1%

21.0%

Civil Engr

29.1%

19.8%

21.8%

23.0%

27.6%

18.3%

17.0%

19.6%

Electrical Engr

43.6%

30.4%

27.6%

31.2%

40.1%

32.3%

25.9%

29.8%

Mechanical Engr

37.8%

32.6%

29.2%

32.0%

36.6%

27.7%

26.4%

28.9%

Economics

24.3%

15.0%

7.6%

13.4%

24.2%

12.9%

8.6%

13.4%

Political Science

10.8%

4.7%

3.0%

5.6%

11.0%

6.6%

3.8%

6.4%

Sociology

10.6%

12.5%

6.8%

9.5%

11.4%

8.2%

5.6%

7.7%

Psychology

11.9%

5.4%

2.5%

5.5%

11.9%

7.8%

3.5%

6.4%

Biological Sci

22.3%

18.7%

11.9%

16.0%

22.1%

16.2%

10.0%

14.2%

Earth Sciences

12.0%

9.8%

6.1%

8.2%

14.3%

12.3%

7.3%

9.8%

White Males Table 11 summarizes the representation of White males among students and faculty in the top 50 departments. The representation of White males stands in stark contrast to that of women, URMs, and even Asians. While the percentage 31

of other demographics falls as rank increases, the percentage of White male professors increase as rank increases in each discipline. While the highest concentration of other demographic groups generally is at the rank of assistant professor, White males reach their highest percentage at the rank of full professor. Furthermore, in all disciplines, the percentage of White male full professors is higher than their representation in the U.S. population (approximately 49%). This is also true at the rank of associate professor in all disciplines but psychology.

Table 11. White Males Among Professors by Rank and Discipline at Top 50 Departments Discipline

Students

Professors FY2012

PhD8796

BS2010

BS2011

Chemistry

36.4%

36.4%

60.9%

Math

42.9%

42.8%

Computer Sci

60.3%

Astronomy

PhD9706

asst

assoc

prof

all

55.7%

51.3%

55.8%

76.0%

68.5%

62.8%

59.1%

48.1%

58.1%

73.2%

66.3%

59.2%

63.6%

59.8%

47.6%

50.3%

62.4%

57.4%

49.9%

50.6%

75.9%

67.9%

59.0%

61.2%

73.7%

68.6%

Physics

66.0%

67.5%

73.0%

72.0%

58.9%

68.6%

79.0%

74.4%

Chemical Engr

51.5%

52.8%

63.1%

58.8%

43.7%

53.0%

70.2%

61.8%

Civil Engr

60.8%

60.2%

63.7%

58.5%

44.0%

60.1%

70.4%

62.6%

Electrical Engr

59.7%

58.1%

63.2%

59.4%

46.7%

52.6%

65.3%

59.4%

Mechanical Engr

70.5%

70.3%

66.5%

65.5%

42.6%

59.2%

66.0%

59.7%

Economics

50.2%

50.7%

59.0%

54.4%

49.5%

68.1%

78.9%

69.5%

Political Science

36.9%

36.5%

55.0%

50.3%

45.0%

52.3%

70.4%

59.2%

Sociology

18.7%

18.7%

36.0%

29.5%

26.4%

35.0%

55.9%

44.0%

Psychology

16.0%

15.8%

35.4%

27.0%

38.3%

47.6%

62.0%

54.2%

Biological Sci

27.7%

26.9%

49.9%

42.1%

46.9%

54.8%

71.7%

62.2%

Earth Sciences

54.3%

53.7%

69.8%

59.7%

48.7%

57.5%

78.8%

68.3%

In all fields but mechanical engineering, the percentage of White male full professors is higher than that of White male undergraduates. Even in mechanical engineering the gap is small—70.0% of full professors are White males, while 71.7% of students are White males. Therefore, there is an abundance of role models for these undergraduate White male students, giving these students an advantage over other students, who are unable to find same-gender or same-race mentors. 32

Table 12 contains data on White males among faculty members in the second 50 and top 100 departments. The representation of White male professors of all ranks in the top 50 departments is marginally larger than in the second 50, with math, physics, chemical engineering, economics, sociology, psychology, and biological sciences having a significantly larger percentage in the top 50 than in the second.

Table 12. White Males Among Professors by Rank and Discipline at Top 100 Departments Discipline

Departments 51 - 100

Departments 1 - 100

asst

assoc

prof

all

asst

assoc

prof

all

Chemistry

45.9%

61.6%

76.4%

67.1%

48.9%

58.6%

76.2%

67.9%

Math

41.4%

57.9%

71.4%

62.7%

45.3%

58.0%

72.6%

64.9%

Computer Sci

49.8%

54.7%

65.4%

58.7%

48.6%

52.3%

63.6%

57.3%

Astronomy

56.6%

60.7%

71.8%

66.3%

58.0%

61.0%

73.1%

67.8%

Physics

55.2%

66.1%

74.5%

69.4%

57.4%

67.5%

77.3%

72.5%

Chemical Engr

43.2%

58.3%

61.4%

56.8%

43.5%

55.6%

66.6%

59.7%

Civil Engr

48.0%

58.3%

68.9%

60.6%

45.7%

59.3%

69.9%

61.8%

Electrical Engr

41.1%

56.2%

64.5%

58.0%

44.5%

54.1%

65.0%

58.9%

Mechanical Engr

45.6%

57.9%

62.9%

57.7%

43.8%

58.7%

64.9%

59.0%

Economics

47.1%

60.7%

76.5%

65.7%

48.4%

64.6%

77.9%

67.8%

Political Science

45.1%

60.2%

73.2%

61.4%

45.1%

55.7%

71.5%

60.1%

Sociology

31.7%

30.8%

53.7%

41.0%

28.8%

33.2%

55.1%

42.8%

Psychology

36.0%

45.8%

60.8%

50.7%

37.1%

46.7%

61.5%

52.6%

Biological Sci

43.4%

50.5%

66.5%

57.1%

45.4%

53.0%

69.7%

60.1%

Earth Sciences

54.4%

61.7%

76.6%

68.5%

50.8%

59.2%

78.0%

68.3%

Changes in Representation Over Time The following bar graphs (Figures 1-12) analyze and compare data on the representations, by gender and race, among faculty in 15 science and engineering departments at the top 50 departments at four different points in time. They draw data from the 2002, 2005, 2007, and 2012 surveys. Tables 1-12 above and analogous tables from the three previous surveys, each provide a snapshot in time of current data. However, the bar graphs below reveal change in representation over time. 33

The bar graphs of professors (all ranks) reflect hiring and retention underrepresented by departments in each discipline. A relatively static set of bars indicates that neither hiring nor attrition of the pertinent group is occurring significantly. Poor retention has been cited as evidence of discrimination in the workplace that leads women and URMs to either leave the field or be let go (5). An increasing percentage shows that, new individuals are being hired and/or individuals on the tenure track are ultimately achieving tenure and promotion. Because conditions for women and URMs will not change rapidly, in order to reliably gauge the status of these demographics in academia, it is important to measure change over time. Data pertaining to all professors are presented in the graphs by increasing percentage from 2002 to 2012, so the discipline that has the greatest increase in diversity from 2002 to 2012 is on the right, while the discipline with the least increase (or greatest loss) is on the left. The change in representation of assistant professors reflects recent hiring of the pertinent groups, and change in representation of all professors combined reflects retention of the group. Change in the former can take place faster than in the latter. Thus, those disciplines showing a large increase in percentage of women and URMs in the assistant professor position are generally making an effort to decrease underrepresentation. Data pertaining to assistant professors are presented in their bar graphs in the same order as in the bar graphs pertaining to professors of all ranks, in order to facilitate comparison. Women – Retention Patterns Figure 1 reveals the change over time of females among professors of all ranks; growth of females in all disciplines is fairly steady. With the exception of psychology and chemical engineering between 2005 and 2007, the representation of women increased across the board. Biological science, sociology, and political science experienced the greatest increase, about 10%. This growth indicates that these disciplines generally are able to retain professors at all ranks. On the other hand, electrical engineering, physics, and computer science have seen relatively slow growth of only a few percentage points since 2002, which could suggest trouble retaining female professors. Women – Hiring Patterns Figure 2 examines the change over time of females among assistant professors. When comparing the percentage of female assistant professors in 2002, 2005, 2007, and 2012, it is apparent that some disciplines have greater increases in the representation of women. For example, between 2002 and 2012, there has been approximately a 10% increase in females among assistant professors in chemical engineering, civil engineering, and sociology. In other fields, such as astronomy and political science, representation has remained fairly stagnant, showing only minimal increases. Most troubling, however, are the fields in which representation has decreased. Despite a large jump in representation between 2002 and 2005, the proportion of females among assistant professors in economics, math, astronomy, and biological sciences has dropped since 2007. 34

35 Figure 1. Bar graph comparing the number of female professors (all ranks) in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of female professors in the 2012 survey. (see color insert)

36 Figure 2. Bar graph comparing the number of female assistant professors in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of female assistant professors in the 2012 survey. (see color insert)

Blacks – Retention Patterns Figure 3 shows the change over time of Blacks among professors of all ranks, revealing that steady growth is not present in most departments. Representation in political science and economics has actually dropped since 2002, while civil engineering, electrical engineering, physics, math, earth sciences, chemistry, biological sciences, and psychology show very little growth. A greater degree of growth can be seen in fields such as astronomy, sociology, and chemical engineering; however, even this growth is fairly minimal. In general, science and engineering departments need to find ways to increase retention and thus representation of Black professors.

Blacks – Hiring Patterns Figure 4 examines the change over time of Black assistant professors. Growth in representation of URMs is more sporadic than that of female assistant professors. The only fields that saw steady growth in the percentage of Blacks among assistant professors were those of earth sciences, chemistry, and biological sciences, but these growths were negligible (the largest growth being about 2% in chemistry). Civil engineering, economics, sociology, math, and physics each revealed a general downward trend, meaning improvement in the representation of Blacks in those disciplines is unlikely in the near future. However, a few disciplines show promising improvement between 2007 and 2012. Political science, mechanical engineering, computer science, and astronomy each experienced a significant increase in the percentage of blacks among assistant professors during that time period, possibly indicating the beginning of change.

37

38 Figure 3. Bar graph comparing the number of Black professors (all ranks) in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of Black professors in the 2012 survey. (see color insert)

39 Figure 4. Bar graph comparing the number of Black assistant professors in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of Black assistant professors in the 2012 survey. (see color insert)

Hispanics – Retention Patterns Figure 5 examines the change over time of Hispanics among professors of all ranks, showing an increase from 2002 to 2007. Representation in political science, sociology, civil engineering, chemistry, and chemical engineering increased most rapidly, while their representation in math, computer science, physics, and earth sciences grew at a slower pace. Furthermore, while most disciplines show fairly constant growth, math, computer science, electrical engineering, and astronomy were erratic, with periods of growth and decline. Hispanic representation in computer science has grown overall since 2002, but it has declined since 2005, indicating recent problems retaining Hispanic faculty. However, as a general trend among disciplines representation has been steadily increasing.

Hispanics – Hiring Patterns Figure 6 examines the change over time of Hispanics among assistant professors. In some disciplines, Hispanics have seen a vast amount of growth in the assistant professor rank. Representation in political science, sociology, chemical engineering, and psychology has significantly increased since 2002, with the largest growth happening in the period between 2007 and 2012. However, representation in math and electrical engineering has decreased, and the percentage of Hispanic assistant professors in computer science, physics, mechanical engineering, astronomy, and biological sciences has shown very little growth (less than 1%). Overall, the change in proportion of Hispanics among assistant professors varies widely based on discipline, indicating that some fields are doing more to increase their representation than others.

40

41 Figure 5. Bar graph comparing the number of Hispanic professors (all ranks) in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of Hispanic professors in the 2012 survey. (see color insert)

42 Figure 6. Bar graph comparing the number of Hispanic assistant professors in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of Hispanic assistant professors in the 2012 survey. (see color insert)

Native Americans – Retention Patterns Figure 7 examines the change over time of Native Americans among professors of all ranks. All disciplines had some representation of Native American professors between 2002 and 2012. However, that representation in economics, sociology, political science, math, and mechanical engineering has since reduced to zero. In fact, there is a general downward trend in all fields except biological sciences, civil engineering, computer science, and earth sciences. Only in civil engineering is there somewhat substantial improvement. This indicates that, in general, Native Americans are not being retained once they enter academia.

Native Americans – Hiring Patterns Figure 8 examines the change over time of Native Americans among assistant professors. Of the 15 disciplines examined in this study, only political science, earth sciences, psychology, electrical engineering, chemical engineering, civil engineering, and biological sciences have had any Native American assistant professors between 2002 and 2012. Of those, the representation in political science and electrical engineering has since dropped to zero. However, earth science and biological science show significant increases, and civil and chemical engineering show modest increases. Despite initial increases after 2002, since 2005 the percentage of Native Americans among assistant professors in psychology has declined. Overall, there seems to be very little advancement in hiring Native Americans among assistant professors.

43

44 Figure 7. Bar graph comparing the number of Native American professors (all ranks) in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of Native American professors in the 2012 survey. (see color insert)

45 Figure 8. Bar graph comparing the number of Native American assistant professors in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of Native American assistant professors in the 2012 survey. (see color insert)

Asians – Retention Patterns Figure 9 reveals the change over time of Asians among professors of all ranks, which has steadily increased in all disciplines. Computer science shows the largest growth, with math, chemical engineering, and chemistry having marginally less. Sociology, political science, and economics have the slowest growth. Thus, Asians are more effectively retained throughout all ranks, including during the tenure process, and they will remain an overrepresented minority in academia

Asians – Hiring Patterns Figure 10 graphs the change over time of Asians among assistant professors, whose representation has generally been increasing since 2002. All disciplines show growth among Asians in this rank, but it appears that this growth is leveling out. Representation in math, chemical engineering, and electrical engineering has decreased between 2007 and 2012, while representation in most other fields shows very little growth in this time period. Although Asians will probably continue to be overrepresented in academia, based on the trends shown in Figure 10, their representation will soon begin to level out.

46

47 Figure 9. Bar graph comparing the number of Asian professors (all ranks) in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of Asian professors in the 2012 survey. (see color insert)

48 Figure 10. Bar graph comparing the number of Asian assistant professors in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of Asian assistant professors in the 2012 survey. (see color insert)

White Males – Retention Patterns Figure 11 gives the change over time of White males among professors of all ranks, which exhibits the opposite trends of other demographics. In all fields, the percentage of White male professors has decreased since 2002. The reasoning is again due to increased representation in other demographics, and reveals that the demographics of academia are beginning to move towards mirroring the demographics of the U.S. However, much more change is needed before those demographics will match.

White Males – Hiring Patterns Figure 12 examines the change over time of White males among assistant professors, and it reveals this same downward trend as observed in Figure 11. In every field but chemistry, the percentage of White males among assistant professors has steadily declined since 2002, generally by 10% or more. This downward trend can be explained by the general increase in representation of other demographics. By decreasing the proportion of White males hired for professor positions, that demographic will slowly fall to more closely match the proportion of White males in the United States population.

49

50 Figure 11. Bar graph comparing the number of White male professors (all ranks) in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of White male professors in the 2012 survey. (see color insert)

51 Figure 12. Bar graph comparing the number of White male assistant professors in “Top 50” departments from FY 2002, FY 2005, FY 2007, and FY 2012 surveys. The number at the top of each 2012 bar corresponds to the total number of White male assistant professors in the 2012 survey. (see color insert)

Changes in Representation among URM Women Table 13 analyzes and compares change in the representation of female Blacks and Hispanics among assistant and full professors in 15 science and engineering disciplines over time. Specifically, displays the data from the 2002, 2005, 2007, and 2012 diversity surveys. Although the numbers are small, overall growth is present. The total numbers of both Black and Hispanic females among full professors have increased steadily each year the surveys were conducted (Hispanic females = 19, 26, 40, 50, and Black females = 22, 29, 34, 75). In addition, totals for Black and Hispanic females among assistant professors have also steadily increased (Hispanic females = 49, 60, 64, 69, and Black females = 50, 70, 66, 91), with the exception of Black professors from 2005 to 2007. The increase in full professors shows that an increasing number of female URMs are staying in the academic pipeline and reaching that rank.

Table 13. Female URM Professors by Rank and Year in Top 50 Departments

The increasing number of assistant professors reveals that, not only are female URMs increasingly staying in the academic pipeline, but they are being brought into it at a faster rate as well. This improvement shows that over time, more female URMs are being hired into academic positions, which promises future growth in their representation among faculty.

52

Conclusions This comprehensive demographic analysis of tenured and tenure track faculty in top 50 departments of 15 science and engineering disciplines shows that women, Blacks, Hispanics, and Native Americans remain significantly underrepresented. Analogous data are also compiled separately for the top 100 departments, in order to compare trends of the two groups. Space limitations prevent full discussion of all comparisons enabled by these data, but they are made available so that other researchers and organizations can take advantage of them in order to guide their own work, and so that universities can gage their own performance relative to other schools and relative to the national averages. There are relatively few tenured and tenure-track female faculty in these research university departments, even though a growing number and percentage of women are completing their PhDs. Insufficient qualified women are entering these sciences and engineering faculties at research universities. Although in some engineering disciplines, there is a better match between the representations of females in PhD attainment versus faculty, these disciplines are the ones with very low percentages of females in PhD attainment. Generally, the percentage of women in science and engineering BS attainment has been fairly stagnant over the past few years; however, undergraduate women are likely to find themselves without the female faculty needed for optimal role models and mentors. In the group of top 50 departments for each discipline, there are few female full professors in science and engineering; in ten of the fifteen disciplines surveyed the percentage of women among full professors was less than 15%. This means the highest-ranking women, those most likely to have the job security to be vocal, did not have critical mass in those disciplines. Even in the discipline with the highest percentage of female full professors (sociology), the percentage falls almost 20% short of the percentage of women in the general population (33.3% versus 50.8%). In all but one discipline surveyed (astronomy), the highest percentage of female faculty is at the level of assistant professor (23.1% vs 25% among associate professors). In order to measure utilization of the hiring pool, the percentage of women among recent PhD recipients versus among assistant professors, the typical rank of recently hired faculty. In the top 50 departments of most disciplines surveyed, the former is much higher than the latter. This means that the hiring pools for these disciplines are not being fully utilized. In order to measure the availability of same-gender or same-race mentors, the percentage of a group among BS recipients is compared against its percentage among assistant professors. The data for top 50 departments demonstrate that while the representation of females in science and engineering PhD attainment has significantly increased in recent years, the corresponding faculties are still overwhelmingly dominated by White men. For example, in 2011, 49.0% of the students graduating with a BS in chemistry were female, but in 2012, only 13.0% of faculty at the top 50 chemistry departments were female. In contrast, the corresponding percentages for White males are 36.4% and 76.0%, respectively. In some disciplines, female faculty are so few that it is likely a women can get a 53

BS or PhD without being taught by or having access to a female professor in that discipline. For the top 50 departments, data indicate that a possible reason for the persistence of low representation of women, Blacks, Hispanics, and Native Americans is because a cycle is perpetuated. For example, women are less likely to enter and remain in science and engineering when they lack same-gender mentors and role models. In most science disciplines, the percentage of women among faculty recently hired is not comparable to that of recent women PhDs. This results in fewer female faculty to act as role models for female undergraduates and graduate students. Female students observe this in the course of sampling the environment. If female professors are not hired, treated fairly, and retained, female students observe this. They perceive that they will be treated similarly. This dissuades them from persisting in that discipline. Underrepresented minorities (URMs) face many of the same issues and mechanisms as do women. In no discipline is there a critical mass of URMs, nor do the percentages of URM faculty approach the percentages of URMs in the general population. Furthermore, although the numbers of female URM faculty are generally increasing slowly, those numbers still remain zero or near zero at research universities in most STEM disciplines. The percentages of female faculty have been increasing since 2002, however, which reveals that there are improvements. In general, percentages for URMs are also increasing, while the percentages of White males and Asians have gradually been falling. These trends reveal that academic faculty in science and engineering departments are becoming more diverse in gender and race. It appears that their demographics are gradually moving towards mirroring that of the general population of the U.S. Our FY2002 Nelson Diversity Survey data for top research university faculties were for whole populations. Therefore, they provided the first measure of the representation of women and URM faculty in STEM departments, disaggregated by race, by rank, by gender, and by discipline. The data in our first survey, as well as all our subsequent surveys, were whole populations. These data satisfy several uses needed by women and URMs for years before they were collected: (1) With disaggregated data of women and URMs now quantified, data before and after implementation of a program, which is designed to remove barriers or to improve the environment, can be compared in order to discern impacts of the program. (2) The quantified demographics provide benchmarks for disciplines, universities, and departments to compare against their own data. (3) Faculty demographics for all 15 disciplines are provided once again, for the fourth time (FY2012, FY2007, FY2005, FY2002), in order to show change over time of each discipline. (4) Disciplines, departments, and universities can compare data against each other and measure and quantify relative progress. Using these data to identify points of strength and challenge for each discipline, can guide the search for programs, resources, and attitudes that are responsible for the results. Behaviors in disciplines or in individual departments which show diversity can be identified and used as models. These data can guide researchers and organizations in their work to increase diversity among faculty. The data will thereby facilitate the transfer of good practices among disciplines. 54

The author regards the extreme interest of undergraduate volunteers in this project, their attitudes toward it, their enthusiasm for it, and their positive comments about it (including by White male volunteers), as refreshing signs of the desirability of, demand for, and expectation for equality by the next generation. (See Acknowledgements below.) In other words, Dr. Nelson predicts that discrimination will not only dissuade future women and URMs from entering academia, it will also dissuade the next generation of White males. Hence, in egalitarianism activities involving the next generation, White males are more likely to be genuine allies than opponents of women and URMS in these efforts.

Acknowledgments The work presented herein spanned the years 2001 – 2014. The author is very grateful that during this time, the Nelson Diversity Surveys were supported by the National Institutes of Health, the National Science Foundation, the Ford Foundation, the Sloan Foundation, the Massachusetts Institute of Technology, and the University of Oklahoma. The author also wishes to thank sincerely the thousands of department chairs who generously gave their time by participating in these surveys over the years. Dr. Nelson appreciates the graduate students and postdocs who assisted on this project. A great deal of work was done by hundreds of undergraduate volunteers (mostly women and URMs) at the University of Oklahoma, as independent study, research, and/or directed readings. The author is grateful that undergraduates had such an extreme interest in this project; without their help in tabulating, data entry, checking and repeatedly re-checking table accuracy, and so on, its success would not have been possible.

Appendix The Appendix contains Tables A1−A15 on the following pages.

55

Table A1. Tenured/Tenure Track Faculty at the Top 50 Chemistry Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

56

Table A1-B. Tenured/Tenure Track Faculty at Chemistry Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

57

Table A2. Tenured/Tenure Track Faculty at the Top 50 Math & Statistics Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

58

Table A2-B. Tenured/Tenure Track Faculty at Math & Statistics Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

59

Table A3. Tenured/Tenure Track Faculty at the Top 50 Computer Science Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

60

Table A3-B. Tenured/Tenure Track Faculty at Computer Science Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

61

Table A4. Tenured/Tenure Track Faculty at the Top 50 Astronomy Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

62

Table A4-B. Tenured/Tenure Track Faculty at Astronomy Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

63

Table A5. Tenured/Tenure Track Faculty at the Top 50 Physics Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

64

Table A5-B. Tenured/Tenure Track Faculty at Physics Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

65

Table A6. Tenured/Tenure Track Faculty at the Top 50 Chemical Engineering Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

66

Table A6-B. Tenured/Tenure Track Faculty at Chemical Engineering Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

67

Table A7. Tenured/Tenure Track Faculty at the Top 50 Civil Engineering Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

68

Table A7-B. Tenured/Tenure Track Faculty at Civil Engineering Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

69

Table A8. Tenured/Tenure Track Faculty at the Top 50 Electrical Engineering Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

70

Table A8-B. Tenured/Tenure Track Faculty at Electrical Engineering Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

71

Table A9. Tenured/Tenure Track Faculty at the Top 50 Mechanical Engineering Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

72

Table A9-B. Tenured/Tenure Track Faculty at Mechanical Engineering Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

73

Table A10. Tenured/Tenure Track Faculty at the Top 50 Economics Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

74

Table A10-B. Tenured/Tenure Track Faculty at Economics Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

75

Table A11. Tenured/Tenure Track Faculty at the Top 50 Political Science Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

76

Table A11-B. Tenured/Tenure Track Faculty at Political Science Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

77

Table A12. Tenured/Tenure Track Faculty at the Top 50 Sociology Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

78

Table A12-B. Tenured/Tenure Track Faculty at Sociology Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

79

Table A13. Tenured/Tenure Track Faculty at the “Top 50” Psychology Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

80

Table A13-B. Tenured/Tenure Track Faculty at the “Top 51 - 100” Psychology Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

81

Table A14. Tenured/Tenure Track Faculty at the Top 50 Biological Sciences Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

82

Table A14-B. Tenured/Tenure Track Faculty at Biological Sciences Departments No. 51-100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

83

Table A15. Tenured/Tenure Track Faculty at the Top 50 Earth Sciences Departments by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

84

Table A15-B. Tenured/Tenure Track Faculty at Earth Science Departments No. 51 - 100 by Race/Ethnicity, by Gender, and by Rank (FY 2012)*

85

References 1.

2.

3.

4.

5.

National Science Foundation, National Center for Science and Engineering Statistics, Survey of Research and Development at Universities and Colleges, 2012, Integrated Science and Engineering Resources Data System (WebCASPAR). https://ncsesdata.nsf.gov/webcaspar/ (accessed May 31, 2014). Etzkowitz, H.; Kemelgor, C.; Neuschatz, M.; Uzzi, B.; Alonzo, J. The paradox of critical mass for women in science. Science 1994, 266, 51–54; http://www.kellogg.northwestern.edu/faculty/uzzi/ftp/paradox.pdf (accessed May 31, 2014).. U.S. Census Bureau: Annual Estimates of the Resident Population by Sex, Race, and Hispanic Origin for the United States, States, and Counties: April 1, 2010 to July 1, 2012, 2012 Population Estimates. https://factfinder.census.gov/faces/tableservices/jsf/pages/productview. xhtml?pid=PEP_2012_PEPSR6H&prodType=table (accessed May 19, 2017). Etzkowtiz, H.; Kemelgor, C.; Nueschatz, M.; Uzzi, B. Barriers to women in academic science and engineering. In Who Will Do Science? Educating the Next Generation; Pearson, W., Fechter, I., Eds.; Johns Hopkins University Press: Baltimore, MD, 1994. Wenzel, S. A.; Hollenshead, C. Former Women Faculty: Reasons for Leaving One Research University; Center for the Education of Women: 1998. http://www.cew.umich.edu/sites/default/files/wenzel98.pdf (accessed May 31, 2014).

86

Chapter 3

Smashing the Glass Ceiling in Chemistry Remains a Long-Range Goal Valerie J. Kuck* Bell Labs, Lucent Technologies (retired), 13622 Orchard Gate Road, Poway, California 92064, United States *E-mail: [email protected]

Historically men have held a clear majority of the tenured and tenure-track faculty positions in chemistry departments at the nation’s most prestigious research institutions. After attending a meeting that addressed the gender bias experienced by female faculty members at the Massachusetts Institute of Technology in the School of Science, administrators from nine highly regarded universities agreed to work together to improve the situation for women at their respective schools. This study focuses on the progress made by the nine institutions to increase the number and rank of female faculty members. A comparison of the chemistry faculties in 2001 and 2016 at the nine institutions showed that some schools made substantial strides in hiring and promoting women; whereas, most institutions made minimal progress. In both of those years, there was a paucity of women at the associate and assistant professor rank and the hiring of women was below their distribution in the doctorate pool. In comparison to the other top 50-ranked federally funded chemistry departments, the nine institutions hired and promoted women at roughly the same rate.

Introduction The release of the report on “A Study on the Status of Women Faculty in Science at MIT (Massachusetts Institute of Technology)” rocked the academic community in 1999 (1). The study was based on the findings of the Committee on © 2017 American Chemical Society

Women Faculty that had gathered data on the fifteen female faculty members in the six departments in the School of Science. The Committee was composed of five tenured female faculty members, one from each of the departments (mathematics had no female faculty members and was not represented), and three men who had been or were Department Heads. After gathering and analyzing their information, the Committee submitted a report in 1996 on their findings and then later amended it in 1997 and 1998. Subsequently, the report was released to the public in 1999. The Committee found that, in contrast to the junior female faculty members, senior tenured female faculty members felt that gender bias had negatively impacted their careers. It uncovered that women, in comparison to their male colleagues, had fared poorer in salary, research laboratory allocation and resources, appointment to influential positions, and receipt of awards and other forms of recognition. It was hypothesized that discriminatory attitudes at MIT had also influenced the hiring of women. It noted that in the preceding 20 years there had been slow or no growth in the percentage of female faculty members in the sciences.

The Aftermath There was wide coverage of the MIT report in the print media (2). In general, the response was positive; however, some individuals disagreed with the existence of gender bias in academe (3). Subsequently, MIT President Charles M. Vest hosted a meeting to discuss the findings of the Committee. On January 29, 2001, university presidents, chancellors, and provosts from nine highly ranked research institutions met at MIT (4). In addition, twenty-five female faculty members from the nine institutions were in attendance. All the university representatives were males. The nine institutions attending the meeting were from the University of California-Berkeley (UC, Berkeley), California Institute of Technology (Cal Tech), Harvard, Michigan, MIT, Pennsylvania (Penn), Princeton, Stanford, and Yale. After the meeting, the university administrators agreed that women faced barriers, that additional data was needed, and that the universities would collectively work to address the problems. Again, there was wide coverage in the media of the meeting and the pledge to improve the situation for female faculty members (5). Many women agreed with the report findings and stated that they were looking forward to seeing the progress resulting from the meeting. This paper addresses the hiring and promotion of women during the years 2001-2016 by the chemistry departments at the nine institutions represented at the Vest meeting. In addition, the progress made by the nine institutions to increase the number of tenured and tenure-track female faculty members will be compared with the efforts made by the other top-50-ranked departments. The National Science Foundation (NSF) had ranked the institutions based on research funding.

88

Data Sources Published data on the gender composition of the chemistry departments at the top 50-ranked institutions for the 2001-2 and 2012-13 academic years was used for part of this study (6, 7). Since the Yale chemistry department no longer was included in the list of the top 10 departments in 2016, 42 schools were included in the data generated for the other top 50-ranked schools. The faculty members in this study were not only from Chemistry Departments but also from Chemistry and Biology and Chemistry and Biochemistry Departments. To obtain the 2016 data, each of the nine departments was contacted in July, 2016 to determine the number and rank of female and male tenured and tenuretrack faculty members at that time. This study was limited to those individuals who were listed by the departments as Professors of Chemistry.

Findings During the span of fifteen years, the nine chemistry departments substantially increased the number of female faculty members. In 2001, there were on average only 3 female tenured and tenure-track faculty members per chemistry department (Table 1). By 2016, the number of female faculty members had grown on average to 6.4. It should be noted that when dealing with small numbers, as is the case for females in academe, the average can be easily skewed, if there is a substantial under or over performance by a few.

Table 1. Total Number of Female Faculty Members Year

2001

2016

Δ

UC, Berkeley

5

10

5

Cal Tech

3

5

2

Harvard

2

7

5

Michigan

4

11

7

MIT

4

6

2

Penn

3

6

3

Princeton

3

4

1

Stanford

1

4

3

Yale

2

5

3

3.0

6.4

3.4

Average

89

Some departments did significantly better than others in hiring women. At the University of Michigan, the number of female faculty members climbed from 4 to 11, Harvard from 2 to 7, and at UC, Berkeley from 5 to 10. During the same time-period, there was little change at Princeton and Cal Tech, with the former increasing the number of female faculty by one and the latter by two. Since the size of the chemistry faculties at the nine schools varied substantially, from the mid-teens to the low fifties, the percentage of faculty positions held by women was determined. In 2001, females held 9.8% of the faculty positions at the nine schools, with Stanford having the lowest percentage, 4 % (Table 2).

Table 2. Percentage of Female Faculty Members Year

2001

2016

Δ

UC, Berkeley

10

20

10

Cal Tech

11

18

7

Harvard

10

24

14

Michigan

10

22

12

MIT

13

19

6

Penn

10

18

8

Princeton

11

16

5

Stanford

4

17

13

Yale

9

14

5

9.8

18.0

8.9

Average

By 2016, the percentage of female faculty members at the nine chemistry departments had increased significantly to 18.0 %. The percentage of female faculty members at Harvard had jumped to 24%; at Michigan, 22%; at UC, Berkeley, 20%; and at MIT, 19%. The change in the percentage of female faculty members at those four schools was on average 12.3%; whereas, at the remaining five institutions the differential was only 6.2%. In 2001, there were on average 1.7 female full professors at the nine institutions (Table 3). By 2016, the number had risen to 3.7. Making this achievement noteworthy is that during the fifteen-year window some female faculty members were no longer professors of chemistry and the number of women at the associate professor level had been only 0.6 per school in 2001 (Table 4). 90

Table 3. Number of Female Full Professors Year

2001

2016

Δ

UC, Berkeley

3

5

2

Cal Tech

2

5

3

Harvard

1

4

3

Michigan

2

6

4

MIT

3

4

1

Penn

2

3

1

Princeton

0

1

1

Stanford

1

1

0

Yale

1

4

3

1.7

3.7

2.0

Average

Table 4. Total Number of Female Associate Professors Year

2001

2016

Δ

UC, Berkeley

1

3

2

Cal Tech

0

0

0

Harvard

0

1

1

Michigan

1

0

-1

MIT

0

1

1

Penn

0

1

1

Princeton

3

2

-1

Stanford

0

1

1

Yale

0

0

0

0.6

1.0

0.2

Average

To increase the numbers of female full professors while simultaneously losing some women, the universities had two options. One was to hire senior women from outside the department. Another way was to accelerate the hiring of female assistant professors and then promote them quickly through the ranks. Unfortunately, there is no obvious way to track the faculty members at the various schools during the fifteen years, as the American Chemical Society’s Directory of Graduate Research does not contain the names of the faculty members at the nine institutions for all of those years. Absent this information, the promotion of specific female faculty members cannot be tracked. Most likely, the universities used both options to increase the number of faculty women.

91

During those fifteen years, the chemistry department at Michigan managed to increase the number of women at the full professor rank by 4, while the faculties at Cal Tech, Harvard, and Yale grew by three women (Table 3). In contrast, there was no change in the number of full professors at Stanford. In 2001, six of the nine departments had no women at the rank of associate professor (Table 4). However, things did improve with time. In 2016, only Cal Tech, Michigan, and Yale had no female associate professors. On average the chemistry departments at the Vest institutions had only 1 female associate professor. In comparing the data from 2001 to 2016, there were slight changes in the number of female associate professors, with UC, Berkeley showing the greatest growth, 2. Two departments, Michigan and Princeton, had fewer female associate professors in 2016 than in 2001. Not only were there very few women at the rank of associate professor, the same was true at the assistant professor level (Table 5). In 2001 two departments, Stanford and Princeton, had no female assistant professors and the remaining departments had only 1. By 2016, only Cal Tech had no female assistant professors. In fact, it had fewer female assistant professors in 2016 than in 2001. In 2001 there was on average 0.8 female assistant professors per chemistry department and in 2016 it had grown to 1.8.

Table 5. Total Number of Female Assistant Professors Year

2001

2016

Δ

UC, Berkeley

1

2

1

Cal Tech

1

0

-1

Harvard

1

2

1

Michigan

1

5

4

MIT

1

1

0

Penn

1

2

1

Princeton

0

2

2

Stanford

0

2

2

Yale

1

1

0

0.8

1.8

1.0

Average

In general, there were more women at the assistant professor rank than at the associate level. One university stood out from the others in increasing the number of assistant professors over the fifteen years. The University of Michigan had 4 more female assistant professors in 2016 than in 2001.

92

It is fair to ask how had the number of faculty members changed over the fifteen years. In 2001 there were 248 male and 27 female professors at the nine universities. Over the intervening years, there was little growth and in 2016 there were 254 male and 58 female faculty members at the nine universities. By far, the number of faculty members had increased more for the women than that for the men. A clear majority of the faculty members were at the rank of full professor. In 2016 the gender breakdown for the full professors was 195 males and 33 females. On average, women were 13.8% of the full professors (Table 6). Because of the low number of women, especially at the associate level, the percentage of women at both the associate and assistant ranks was calculated. At the Vest institutions women held on average 29.7% of the associate and assistant professor positions (Table 6), which is significantly higher than their percentage at the full professor rank, 13.8%. Strikingly, both Cal Tech and MIT had a higher percentage of women at the full professor rank than at the combined associate and assistant professor levels (Table 6).

Table 6. Percentage of female faculty members, 2016 data School

% Female full professors

% Female assoc & assistant professors

UC, Berkeley

13.5

38.5

Cal Tech

18.5

0.0

Harvard

16.0

75.0

Michigan

18.2

27.8

MIT

20.0

16.7

Penn

12.5

25.0

Princeton

5.9

37.5

Stanford

7.1

30.0

Yale

12.9

16.7

13.8

29.7

Average

A picture of the recent hiring can be obtained by examining the numbers of male and female associate and assistant professors in 2016 (Table 7). For both the men (Table 7) and the women (Tables 4 and 5), there were twice as many individuals at the assistant professor rank than at the associate level. There were on average 6.6 males and 2.8 females at the combined associate and assistant professor ranks at the Vest institutions (Table 8).

93

Table 7. Total number of male professors, 2016 data Full

Associate

Assistant

UC, Berkeley

32

1

7

Cal Tech

22

0

1

Harvard

21

0

1

Michigan

27

5

8

MIT

16

4

6

Penn

21

5

4

Princeton

16

0

5

Stanford

13

3

3

Yale

27

1

4

21.7

2.1

4.4

Average

Table 8. Total number of associate and assistant professors, 2016 data Men

Women

% Women

UC, Berkeley

8

5

38

Cal Tech

1

0

0

Harvard

1

3

75

Michigan

13

5

28

MIT

10

2

17

Penn

9

3

25

Princeton

5

3

38

Stanford

7

3

30

Yale

5

1

17

6.6

2.8

29.7

School

Average

In 2016 women held 29.7% of the positions at the combined associate and assistant professor levels. During the years 2000-2011, the time period when most the female assistant and associate professors would have completed their graduate studies, women earned 35.6% of the doctorates in chemistry (8). In general, women were not being hired in proportion to their fraction of the available pool of chemistry doctorates. It should be noted that at four universities, Michigan, Harvard, Princeton, and UC, Berkeley, the percentage of women at the combined associate and assistant professor ranks was greater than their distribution in the doctorate pool. 94

The efforts made by the Vest institutions to increase the number of female faculty members was compared with those at the other top 50-ranked chemistry departments to see the effectiveness of the pledge made by the top administrators who attended the Vest meeting. In 2001, at both groups of schools, there were roughly the same number of female faculty members at the three ranks (Table 9).

Table 9. Average number of women/institution Full Professor

Associate Professor

Assistant Professor

% Female faculty

The Other Top 50 Funded Inst.

1.4

1.0

1.3

11.3

Vest Nine Schools

1.7

0.6

0.8

9.8

The Other Top 50-Funded Inst.

2.9

1.4

1.6

18.1

Vest Nine Schools

2.9

0.4

1.8

16.6

School 2001

2012-13

To compensate for the significant differences in the size of the faculties, the percentage of female faculty members at the three ranks was carried out (Table 10). In 2001 women held 9.8% of the faculty positions at the Vest institutions and 11.3% of the positions at the other top 50-ranked institutions. At the full and associate professor ranks, there were small differences in the percentages of women faculty at both groups of schools. However, at the assistant professor rank there was a difference between the two groups of schools. Women were 21% of the assistant professors at the other top 50-ranked institutions and 15.9% at the Vest institutions. Overall, the percentages of female faculty members at the two groups of schools were roughly the same. Examination of the data for the gender breakdown of the faculties in 2012 showed some differences. The percentage of female faculty members was still slightly higher at the top 50-ranked schools than at the Vest institutions, 18.1% vs. 16.6%. There was little difference in the percentage of women at the full professor level: 12.9% at the nine institutions vs. 13.6% at the other top 50-ranked schools. There were greater differences at the other two ranks. At the associate professor rank, the percentage of women had grown to 24.7% at the top 50-ranked schools, while it slightly dipped to 17.4% at the Vest institutions. At the rank of assistant professor, the percentage of positions held by women significantly jumped at the Vest institutions. This occurred because the chemistry departments at Michigan and UC, Berkeley had 4 assistant female professors; whereas, the remaining seven institutions had on average 1.7 assistant female professors. This resulted in raising the percentage of female assistant professors to 34.8% at the Vest schools, which is substantially higher than the 28.7% calculated for the other top 50-ranked schools. 95

Combining the data for the associate and assistant professor ranks showed that women held 28.9% of the positions at the Vest institutions and 26.7% at the other top 50-ranked schools. In general, the gains made by both groups of schools were comparable. It is not obvious that the pledge made by the administrators at the Vest meeting had made a difference, as both groups of schools had made comparable gains.

Table 10. Percent of Females Full Professor

Associate Professor

Assistant Professor

All

The Other Top 50 Funded Inst.

6.5

20.0

21.0

11.3

Vest Nine Schools

7.4

18.5

15.9

9.8

The Other Top 50-Funded Inst.

13.6

24.7

28.7

18.1

Vest Nine Schools

12.9

17.4

34.8

16.6

School 2001

2012-13

Discussion In analyzing the initial data, it became apparent that there were significant differences in the hiring of women at the nine Vest schools. All nine universities made progress in varying degrees to increase the numbers of female faculty members. However, three of the nine schools were significantly more successful than others in hiring women. A comparison of the number of female faculty members at the nine schools in 2001 and then in 2016 showed that Michigan had added 7 women and the chemistry departments at both UC, Berkeley and Harvard had increased by 5 females (Table 1). In contrast, the remaining six Vest schools had grown on average by only 2.3 female faculty members. Previously, others have looked at the differences in the training of male and female graduate students to get a better understanding of the reasons for the dearth of tenured and tenure-track women on university faculties. One study found, that prior to entering graduate schools in chemistry, a higher percentage of men were interested in pursuing a faculty position at a research institution than the women. However, during their graduate school training, the percentage of women desiring a career at a research institution decreased more than with the men (9). Other studies reported that a survey of graduate students found that male graduate students, in contrast to the female students, were more positive about their interactions with their dissertation professor and with the quality of mentoring that they had received (10, 11). Furthermore, researchers identified factors that may have influenced the career choices of the female graduate students (11). It was posited that the scarcity of female faculty members left the female graduate 96

students with few female role models to inspire them to seek a career in academic research. The dearth of female faculty members could have resulted in the female doctoral candidates questioning the feasibility of balancing a career in research and the demands of family life. In addition, the conflict between the female graduate students’ biological clocks and the tenure clock could have influenced their career choices. It is not surprising that other researchers found women were under-represented in the pool of job applicants for tenure-track positions (12) and those holding post-doctoral appointments (13). In other research, identification of the doctoral university of faculty members at the top fifty ranked National Research Council (NRC) research universities found that 50% of the faculty members had completed their doctoral training at a small group of ten institutions (14). Furthermore, in comparison to the female doctorates from those ten institutions, a higher percentage of the male graduates were hired by a top-fifty ranked NRC institution (14). Incredibly, the female graduates from the elite group of schools had run into barriers in attaining faculty positions at highly ranked institutions. Those ten elite schools were: Cal Tech; Columbia; Cornell; Harvard; MIT; Stanford; UC, Berkeley; U. of Chicago; Wisconsin; and Yale. Given the crucial role that those ten institutions play in training so many future faculty members at the nation’s top research schools, it is important to monitor the gender composition of the faculties at those ten institutions. In addition to training so many future faculty members, those elite schools are sending a subtle message to the community on the perceived value of the research efforts carried out by women and the merit of their scientific findings. It should be noted that six of the ten elite schools are Vest institutions. In 2016 there 25 female associate and assistant faculty members at the Vest schools (Table 8). During the years 2000-2014 most of the associate and assistant professors would have completed their doctoral training. The ten elite institutions granted a total of 2,880 doctorates during that time frame with women receiving 33.1% (1,470) of the doctorates (15). Three schools, Michigan; UC, Berkeley and Harvard had a total 13 women at the associate and assistant ranks. In sharp contrast, there was a total of 12 women at the other six Vest universities. It should be noted that at Harvard, Princeton, and UC, Berkeley, the percentage of women at the combined associate and assistant professor ranks was above the distribution of women in the doctorate pool. However, in general the Vest schools were hiring women below their distribution in the doctorate pools. This had occurred despite the pledge made by the top administrators at the Vest meeting and all publicity in the press to increase the representation of female faculty members. The uneven hiring of women by the Vest schools could have resulted from some search committees actively seeking out talented women, while others made no special efforts to identify outstanding females. Another explanation is that female seekers preferentially decided to apply for positions only at certain schools. Unfortunately, the exact number of women who applied for positions at each of the Vest schools is not available. All that is known is that women, in general, are under-represented in the applicant pool for tenure-track positions in the STEM fields (12). Further research needs to ascertain the applicant pools at the Vest institutions and correlate those findings with the number of women hired. In 97

addition, those findings need to be expanded to identify the reasons that some of the top 50-ranked institutions are consistently increasing their number of female faculty members, while others are making little progress. Focusing on the female faculty members at the nine Vest universities, the greatest growth in numbers occurred at the rank of full professor. In 2001 there was a total of 15 female full professors. In 2016 the number had grown to 33 (13.9% of the positions) (Tables 3 and 6). During the years 1966-1999, the time-frame when most the female full professors had received their doctorates, women earned 18.3% of doctorates in chemistry (8). Even with the growth in the number of female professors, the percentage of female full professors in 2016 at the Vest institutions is below the gender distribution in the 1966-1999 doctorate pool. Participating in the Vest conference in 2001 and the subsequent pledge to improve the situation for women probably had some effect. However, a comparison of the growth in the percentage of female faculty members found that the Vest institutions had not out-performed the other top 50 ranked schools (Table 9). In addition, both groups of schools were still hiring women below their distribution in the doctoral pool. Since the meeting in 2001, other researchers have made specific recommendations on ways to improve the situation for women in academe (16, 17). One research study found that some departments thought their growth in female faculty numbers was on a par with that of other schools, although further analysis showed clearly that they were lagging (11). It might be that the six under-performing Vest schools were not aware of the strides being made at Michigan, UC, Berkeley and Harvard to increase the gender diversity of their faculties. It appears that the pledge had little impact on those six chemistry departments.

Conclusions Reaching out to administrators at the nine institutions had mixed results. During the years 2001 to 2016, three of the Vest institutions made significant advances in hiring and promoting women, while most the Vest schools made marginal progress. Furthermore, a comparison of the 2001 and the 2012 data, showed that the increase in the percentage of female faculty members was roughly the same at both the Vest institutions and at the other top 50-ranked institutions. The Vest schools as a group had not outperformed the other 50-ranked schools. At both groups of schools, women held on average 33% of the doctorates granted by the elite group of ten universities during the years 2000-2014. The fact that three of the Vest universities did so much better than the others in hiring women, suggests that other factors are in play. Further research is needed to uncover the reasons for this hiring differential. This current study shows that getting administrators to pledge to make improvements at their schools had yielded mixed results. New measures need to 98

be taken so that in the foreseeable future all chemistry department faculties will reflect better the gender distribution of the doctorate pool.

References 1. 2. 3.

4. 5. 6. 7. 8.

9.

10. 11. 12.

13. 14. 15.

16.

17.

A Study on the Status of Women Faculty in Science at MIT. http:// web.mit.edu/fnl/women/women.html (accessed July 7, 2016). MIT Gender Equity Project. http://web.mit.edu/gep/about.html (accessed July 7, 2016). Women in Science at U.S. Universities: Criticism and Defense of the MIT Report. http://www.aas.org/cswa/status/2001/JUNE2001/MITReport.html (accessed Feb. 15, 2016). Long, J. Chem. Eng. News 2001, 79 (6), 8. Lawler, A. Science 2001, 291 (5505), 806. Byrum, A. Chem. Eng. News 2001, 79 (40), 98–99. Rovner, S. Chem. Eng. News 2014, 92 (14), 41–44. Women in Science and Engineering Statistics; Earned Doctorates by Citizenship, Field, and Sex 2001-11 http://national academies.org/PGA/ cwsem/PGA_049131 (accessed July 13, 2016). Chapman, S.; Dixon, F. F.; Foster, N.; Kuck, V. J.; McCarthy, D. A.; Tooney, N. M.; Buckner, J. P.; Nolan, S. A.; Marzabadi, C. H. J. Chem. Educ. 2011, 88 (6), 716–720. Nolan, S. A.; Buckner, J. P.; Marzabadi, C. H.; Kuck, V. J. Sex Roles 2008, 58, 235–250. Laursen, S. L.; Weston, T. J. J. Chem. Educ. 2014, 91 (11), 1762–1776. National Research Council. Gender Differences at Critical Transitions in the Careers of Science, Engineering and Mathematics Faculty; National Academies Press: Washington, DC, 2010; pp 46−47. Marzabadi, C. H.; Kuck, V. J.; Nolan, S. A.; Buckner, J. P. Are Women Achieving Equity in Science? ACS Symp. Ser. 2006, 929, 104–124. Kuck, V. J.; Marzabadi, C. H.; Nolan, S. A.; Buckner, J. P. J. Chem. Educ. 2004, 81, 356–363. Private communication with Mark Fiegener, Project Officer with the Survey of Earned Doctorates (SED) at the National Science Foundation, on July 25, 2016. National Research Council. Gender Differences at Critical Transitions in the Careers of Science, Engineering and Mathematics Faculty; National Academies Press: Washington, DC, 2010; pp 164−166. National Academy of Sciences. Beyond Bias and Barriers; Fulfilling the Potential of Women in Academic Science and Engineering; National Academy of Sciences: Washington, DC, 2006; pp 7−9.

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Chapter 4

The Gender and URM Faculty Demographics Data Collected by OXIDE Rigoberto Hernandez,* Dontarie Stallings, and Srikant Iyer Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, United States *E-mail: [email protected]

The Open Chemistry Collaborative in Diversity Equity (OXIDE) in partnership with Chemical & Engineering News (C&EN) has been gathering and publishing the demographics of chemistry departments since 2009. Disaggregated data (available since the 2009-2010 academic year) has been generated according to department, faculty rank, and gender for more than 100 departments. The data (post the 2011-2012 academic year) has been further disaggregated according to underrepresented minorities. We will report these numbers with an emphasis on the trends as well as the prospects for achieving parity with availability. Moreover, we will discuss programmatic solutions that departments can implement to effectively transition their demographics towards parity with availability.

Introduction The Open Chemistry Collaborative in Diversity Equity (OXIDE) was founded in 2010 in order to address the underrepresentation in chemistry faculties with respect to gender, underrepresented minorities, gender identity and orientation, and disabilities (1). The ontology of the phonetic acronym, OXIDE, has been a source of confusion for some, and is recapitulated in our other chapter in Volume 2 of this book (2). A side benefit of the confusion that this acronym creates is that it is a reminder that the conversion of the two “C”s into an “X” is not an obvious conversion to many of us. However, this is perhaps because few of us have the unique ability of dyslexia. That is an example of the power of diversity. We are © 2017 American Chemical Society

bringing people with different abilities, different points of view, different color, different gender, and different orientation, for example, to bear on the scientific challenges that confront us. In our work, we have focused on identifying barriers and solutions to diversity equity in chemistry departments in collaboration with department chairs, social scientists and the diversity community (1). To enable substantive changes, we have also focused on dissemination through many channels such as workshops and publications in traditional channels, and increasingly through social media and other nontraditional channels (2). However, there is another critical piece in our effort to move the demographics of chemistry faculties towards that of the available hiring pools. Namely, we need to know the demographics both historically and over the period of time of interventions by others and us. In this chapter, we report on those numbers paying particular focus to the numbers that have been reported in Chemical & Engineering News, initially collected by their reporters (3–13) and now collected by OXIDE (14, 15).

Defining the Case for Diversity In August 2014, Lego introduced the Research Institute as a limited set featuring a female paleontologist, a female astronomer and a female chemist in mock labs as shown in Figure 1 (16, 17).

Figure 1. Photographs of the Lego sets from left to right highlighting a woman scientist who is a paleontologist, an astronomer and a chemist, respectively. (Photo taken by Rigoberto Hernandez.) The set’s creation and production was motivated by the need to counter the lack of images of female scientists seen by young men and young women in their formative years generally, and, in particular, when they play with their Legos. This was a well-meaning gesture but it suffered from the fact that it sold out within days of its introduction. So the ironic result is that even in the Lego world, women scientists are actually rare and that’s what we have to fight against. It’s also relevant to note that all three characters are Lego white. We have to address such narrow imagery as well. Indeed, OXIDE aims to advance diversity along every vector. 102

Moving beyond this motivation, the case for diversity has been made by us (1, 18, 19) and others (20) along several vectors. In the so-called business case for diversity, several studies (21–27) have argued and demonstrated that diverse working groups lead to higher success in the business and academic world. Rankings of universities such as the most recent NRC study (28) include significant correlation with international representation and other forms of diversity. Interestingly, the correlation to URGs was less clear, but the observation of such weak cofactors is likely attributable to the implicit biases that are encoded in professional culture and practice (29–33). Finally, perhaps the most compelling argument from the perspective of national needs for human resource development is the fact that the demographics of our faculties differ significantly from those of our overall population, and even to those of our doctoral pools (34–40). This is a human resource management issue whose importance is growing with time as the U.S. population moves towards have a minority majority (41). The remainder of this chapter therefore focuses on summarizing efforts by OXIDE and others to obtain and document the demographics of the faculties in chemistry.

A Short History of the Gender and URM Scorecard The recent work by OXIDE (1) to gather data on the demographics of under-represented groups such as women in the faculties of the leading research-active chemistry departments has significant precedent. C&EN has been reporting data on women faculty since the early 2000s (3–12, 42–45), initially motivated by earlier surveys from the Women Chemists Committee and the findings from the Nelson Diversity Surveys (46, 47) at the University of Oklahoma (4). OXIDE began collecting data on women in 2009, and C&EN has been reporting the data from OXIDE’s gender survey every two years. It was a mission that was energized by C&E News at the turn of the 21st century with the gender scorecard (3–12, 42–45). Through its annual (or semiannual) publications, C&E News habitually spotlights the extent of under-representation of women in chemistry’s faculties as a whole as well as the departments for which the under-representation is particularly severe or laudable. It also creates an opportunity for departments to compete in terms of the largest representation of women. In parallel, OXIDE began collecting data on underrepresented minorities (URMs) in 2011 and that data was first published in C&EN last year (48). The Nelson Diversity Surveys (46, 47) were also critical in providing data on the URM representation in the faculties of many STEM departments—including chemistry—and also acted as a scorecard for the years that they reported. However, a necessary feature of the gender scorecard is that it is assessed yearly and longitudinally, as is now being gathered by OXIDE and reported by C&EN. The gender scorecard is subversive in that it appeals to the competitive drivers in Academia. Their mission is inextricably linked with excellence and their position relative to the top of rankings. The existence of a demographics scorecard provides visibility to the schools, which are at the top, and notoriety 103

to those schools near the bottom of the list. The existence of these scorecards is thereby providing motivation for departments to increase their diversity representation while also providing the community with quantitative tracking of the progress that has been made collectively towards reaching commensurability to availability.

OXIDE’s Gender Scorecard Starting with the 2011 publication in C&EN (49), the data collection of the gender scorecard has been undertaken primarily by OXIDE. Chemistry departments and department heads across the country are asked to self-report their demographics, without individual identification. This ensures that the survey collects no personally identifiable information that would leave OXIDE vulnerable to additional scrutiny by institutional review to ensure proper and ethical handling of the data. It is also notable that for the same reason, no other information is collected or correlated with the data. OXIDE surveys those departments with PhD programs and federally-funded chemical-research expenditures at or near the top 100 as tracked by the NSF (28). Thus far, the demographics have been tracked across gender —which is the focus of this section— and racial/ethnic background —which is the focus of the next section— of tenure track chemistry faculty. We have had not collected data across disability and sexual orientation data because chairs reported significant concerns over reporting such data because of privacy and legal concerns. This is unfortunate because we all recognize that the numbers of these cohorts are also important and awareness about them could help improve diversity equity (50–52) across those vectors as well. The percentages of female and male faculty across the top 50 chemistry departments over the first five years that OXIDE collected the data is shown in Table 1. The demographics are disaggregated across every tenure track level —assistant, associate and full professors— in Figure 2 and Table 2. One notable issue here is that the list used to create the cohort of top 50 schools changes from year to year. For simplicity, we refer to this data as being “congruent” in the sense that the data is generate for a give year and corresponding ranking. This practice of collecting and reporting the data in congruent sets was initiated by C&EN, and OXIDE has continued to aggregate the data accordingly. However, when the same cohort is used across the five years of OXIDE’s data collection, the aggregated representation of female scientists followed the same percentages (within statistical errors) as those shown in Table 1. One important finding of our work is that the female faculty representation, is not substantially affected by the ranking of the programs. That is, the percentages are the statistically equivalent whether you review programs in the top 10, top 25, top 50 or top 75 (13, 53), The lack of representation is partially due to the losses affecting the pipeline (54) into the faculties, but presumably also due to factors within the tenure stream as the percentages of female faculty fall precipitously across ranks. 104

Table 1. Gender data collected by OXIDE showing the percentages of professors in the top 50 chemistry departments disaggregated according to gender: male vs. female (12, 13, 49, 53) AY2009-10

AY2010-11

AY2011-12

AY2012-13

AY2013-14

Female Faculty

16.4%

16.8%

16.4%

17.1%

17.8%

Male Faculty

83.6%

83.2%

83.6%

82.9%

82.2%

Figure 2. Gender data collected by OXIDE showing the breakdown in numbers and percentages of assistant, associate and full professors disaggregated according to gender: male vs. female. All data compiled and archived by OXIDE; different parts of the OXIDE data have been reported in Refs. (12, 13, 49, 53).

Six years ago—in 2009, —the percentage of women earning PhDs was 37% (49). That same year, the female faculty representation within the top 50 chemistry programs was 16% as reported in Table 1 (12, 13, 49, 53). Fast-forward to the 2013-2014 academic year, and the female faculty representation has only increased to 18%, and 25% for assistant professors as reported in Table 2 (53). Between academic year 2009-10 and academic year 2013-14 there was only a 2% increase in female faculty representation. The rate of increased representation is too slow (1). At that pace, it would take more than 30 additional years to reach female faculty representation that correlates to 2010 female PhD availability. Moreover, even these small increases in the female faculty representation have not occurred exclusively as a function more participation by female faculty because the overall number of positions also decreased. Indeed over this period, the net increase in female faculty in this cohort over 5 years was only 12 additional female professors. 105

The representation of female faculty is not the same and decreasing with respect to the tenure track tiers: assistant professor, associate professor and full professor. Tenured and promoted female faculty representation has lagged behind female PhD for entirely too long (Table 2) (54). When one breaks down the overall percent of faculty by tiers, full faculty vastly outnumbers its corresponding tenure track tiers. While male full faculty members more than quadruple the corresponding tenure track tiers, female faculty members almost double their corresponding tenure track tiers. Meanwhile, the number of female assistant faculty is consistently larger than the number of female associate faculty. Conversely, male associate faculty consistently outnumber male assistant faculty. This data speaks to the fact that, women entering the faculty pipeline are not reaching tenure at the same rate as their male counterparts. As a result of this inequity, there are fewer female faculty traversing the pipeline to become full faculty.

Table 2. Percentage of URM chemistry professors at top 50 departments collected and archived by OXIDE. (Notably, some of this data was reported by Chemical & Enginering News in Ref. (55).) AY 2011-12

AY 2012-13

AY 2013-14

Assistant Professors

5.2%

6.0%

5.6%

Associate Professors

8.3%

7.8%

7.3%

Full Professors

2.5%

2.7%

3.4%

All Professors

3.8%

4.1%

4.2%

OXIDE’s URM Scorecard The first article providing longitudinal demographics of chemistry faculties whose race/ethnicity are under-represented within the chemistry faculty cohort was published in C&E News last year based on the data that OXIDE obtained from the chemistry departments through a gender and URM survey (55). Within the chemistry community under-represented group are defined as: Hispanic or Latino, African American, American Indian, Alaska Native, Native Hawaiian, Other Pacific Islander and individuals that are multiracial including these categories. The so-called under-represented minorities (URM) scorecard thus serves as a complement to the gender scorecard in assessing the diversity of our faculties. Groups whose race/ethnicity are under-represented within the chemistry community represent 33.1% of the United States population. Conversely that same population represents 6.6% of tenure track chemistry faculty as indicated in Figure 3. The lack of effective utilization of the URM cohort is even more profound considering the United States will transition into a majority minority nation by year 2050 (41, 56). When you drill down and look at the various relative 106

percentages, the data is not pretty. URM faculty members undergo professional advancement at a slower rate. URM faculty members are currently spending a longer than average period of time at the associate professor tier. A thin line separates top and bottom performing programs. If another institution poaches one or two URM faculty from these schools, rankings change dramatically. That is to say, the current numbers of URM professors in a given department are so small that only three or four URM faculty are needed to be at the top of the URM Scorecard. Every underrepresented minority category is truly over “under-represented” if you will.

Figure 3. This illustration of OXIDE’s under-represented minority data for AY 2013-14 stands in large contrast to the overall population of the US, which is presently well over 30% in URM representation.

Representation of URM professors over the past 15 years is very flat unlike the modest but palpable increases seen in female faculty representation. Indeed, some URM groups exhibit decreasing representation. In 2000, the number of Hispanic and Latino professors were around 1-2%, and this was comparable to the number of African American professors (4). During the last 15 years the number of Hispanic and Latinos professors have gone up while the number of African American faculty have stagnated (47, 57). Though the modest improvements in the representation of Hispanic and Latino professors are laudable, the representation of both these URM cohorts do not approach the availability in the country as a whole, or chemistry undergraduate majors. The advent of the URM scorecard provides an effective baseline to address the current inequities and the effects of future diversity solutions. Similar to the gender scorecard, the URM scorecard highlights each department’s level of “success.” The current percentage of URMs entering college is on par with majority students entering college (58, 59). As of now, there is a substantial gap between representation and availability. Though the K-12 system is problematic, 107

chemistry departments have the capacity to play a significant role in the recruitment, retention and graduation of its URM students.

Conclusion In this chapter, we have summarized some of the recent data on the demographics of the faculty in many research-active chemistry departments. The entire data set and more extensive comparisons of aggregated cohorts are available online (60). We track over a hundred schools, we did this in order to be able to retrospectively and longitudinally track the top 50 and top 75 schools in research expenditures as identified by the NSF in a given year. The longitudinal tracking is important so as to ensure that changes in the percentages over time are due to changes in the consistent cohort and not because the members of the cohort have changed. The survey collection is a yearly process and the 2015-2016 survey had been released before March 2016, and the 2016-2017 survey will be released in the late fall of 2016. Unfortunately, the data collection is arduous because we rely on a survey for which we need nearly 100% participation. While some departments respond quickly, invariably there are a few departments (and not always the same ones) that take nearly a year to complete the survey. The survey instrument continues to be refined so as to make it easier for completion, and many departments report that it takes short time to complete. C&E news released our 2013-2014 and 2014-2015 data in September 2016 (15), and we will continue to work with them to disseminate the demographics until we have reached commensurability in the demographics of the faculties and availability. OXIDE is also leveraging the data release to increase the level of conversation on inclusive excellence among the chemistry faculties and student bodies. In a separate chapter (2), we discussed our approach for engaging in this conversation via social media but we are not above using standard media. One of us has published two Comments in C&EN highlighting solutions to diversity equity (18, 61). In a workshop styled meeting OXIDE along with department heads and chairs, has generated a list of effective solutions that can be implemented in chemistry departments to advance diversity equity (62, 63). Many of these are “low hanging fruits” that require little expense and have substantial impact, such as creation of diversity equity committees (18). Finally, OXIDE plans to publish another ACS symposium series book summarizing all of our workshops—the National Diversity Equity Workshops (NDEWs). Several social scientists were invited —and all accepted— to speak at the ACS Symposium on the “Social and Chemical Science of Diversity Equity.” We encourage readers to continue the conversation: make sure that wherever you go, people know that diversity and inclusion is integral towards being the best chemist that we all want to be.

Acknowledgments This work and the OXIDE program have been jointly supported by the NIH, DOE and NSF through NSF grant #CHE-1048939. Cognizant units are the 108

Pharmacology, Physiology, and Biological Chemistry Division at the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH), the Office of Basic Energy Sciences (BES) at the Department of Energy (DOE), and the Chemistry Division of the Math and Physical Sciences Directorate (MPS) at the National Science Foundation (NSF).

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58. Krogstad, J. M.; Fry, R. More Hispanics, Balcks Enrolling in College, But Lag in Bachelor’s Degrees. http://www.pewresearch.org/fact-tank/2014/ 04/24/more-hispanics-blacks-enrolling-in-college-but-lag-in-bachelorsdegrees/. 59. Casselman, B. Race Gap Narrows in College Enrollement, But Not in Graduation. http://fivethirtyeight.com/features/race-gap-narrows-incollege-enrollment-but-not-in-graduation/. 60. Stallings, D.; Iyer, S. K.; Hernandez, R. Faculty Demographics Data. http:// oxide.jhu.edu/2/demographics. 61. Hernandez, R. Advancing The Chemical Sciences Through Diversity. Chem. Eng. News 2014, 92 (28), 45. 62. Watt, S.; Hernandez, R. Chair Recommendations from National Diversity Equity Workshop (NDEW 2013). http://oxide.jhu.edu/src/NDEW/2013/ NDEW2013_Recommendations_for_Chairs.pdf. 63. Stallings, D.; Iyer, S. K.; Hernandez, R. Chair Recommendations from National Diversity Equity Workshop (NDEW 2015). http://oxide.jhu.edu/ src/NDEW/2015/NDEW2015_Recommendation_For_Chairs.pdf.

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Workplace Environment and Work Styles for Women

Chapter 5

Career Success of Women in the Chemical Industry, Part 1: Finding a Way through the Labyrinth Penelope A. Asay,1 Jill D. Paquin,2 Julie R. Arseneau,3 Vanessa Downing,4 Melissa S. Roffman,5 Kelly D. Kettlewell,6 Tracey Berman,7 Heather M. Walton,8 and Ruth E. Fassinger9,* 1Illinois

School of Professional Psychology, Chicago, Illinois 60601, United States 2Chatham University, Pittsburgh, Pennsylvania 15232, United States 3Southeast Louisiana Veterans Health Care System, New Orleans, Louisiana 70161, United States 4Christiana Care Health System, Newark, Delaware 19718, United States 5Baptist Health, AgeWell Center for Senior Health, Jacksonville, Florida 32207, United States 6Bucknell University, Lewisburg, Pennsylvania 17837, United States 7Woodcliff Lake School District, Woodcliff Lake, New Jersey 07677, United States 8Veterans Affairs Boston Health Care System, Brockton, Massachusetts 02301, United States 9University of Maryland, College Park, Maryland 20742, United States *E-mail: [email protected]

This is the first of three articles where we report findings from Project ENHANCE, an investigation of the career experiences of women trained in science and engineering and working in the chemical industry. The project utilized both quantitative and qualitative methodological approaches, with the broad goals of identifying factors that impede or facilitate diverse women’s career success from the point of view of both women and management, and identifying corporate practices that contribute to positive workplace experiences for women in industrial chemistry. This, the first article in the series, presents all of the project methodology and broad, overall findings related

© 2017 American Chemical Society

to success, satisfaction, advancement, company support, and the home-work interface. The second and third articles in the series present findings related to specific workplace challenges for diverse women, as well as management perspectives on women working in industrial chemistry and leadership issues for women in this sector.

Introduction In April, 2015, the journal Plos One found itself in a firestorm of controversy after an editor suggested to two female researchers that they enlist one or two male biologists as co-authors to give their paper credibility and prevent it from veering into bias (1). That the research under review was a study of gender differences in the PhD-to-postdoc transition in scientific careers provided an ironic exclamation point to the public outrage. By the end of the week, the sexist review iself (which likened high publication rates of male students to their ability to run a mile faster than their female counterparts) and both the peer reviewer and the editor had been removed, and the researchers were promised a fair review. However, the scientific community was left scratching its collective head that such a blatant manifestation of bias could occur fully ten years after economist and then-president of Harvard University, Larry Summers, opined that gender disparities in academic and professional achievement—attributed by most researchers to factors such as gender socialization and stereotyping (2, 3) and discriminatory practices (4, 5)—might, instead, be explained by women’s inherently lower aptitude in science and mathematics (6). Summers’ remarks provoked controversy and outrage in 2005, and an additional decade of research and intervention regarding women in STEM fields (Science, Technology, Engineering, Mathematics) does not appear to have mitigated the public expression of deeply entrenched sexist attitudes. This is a disheartening reminder of both the glacial pace of change in this arena and the continuing importance of research exploring the barriers to and facilitators of career success for women in STEM fields. Much work has been done to document the challenges and issues for women in STEM fields. However, most of the attention in the research literature has focused on women in the academic sector (as both students and faculty), while the experiences of women working in industry (the largest employer of STEM-trained women) have remained largely undocumented. Our work in Project ENHANCE, carried out at the University of Maryland and supported by the National Science Foundation, was aimed at filling this gap by investigating the experiences of STEM-trained women working in the chemical industry. This article (Part 1), the first of three, presents an overview of the questions that drove our investigation, outlines the methodology we used to conduct our multi-year study, and presents overall results related to success, satisfaction, advancement, company support, and the home-work interface. Additional results from the study are found in the two articles (Parts 2 and 3) that follow (7, 8). 116

The Need for Women in the Scientific Workforce The strength and growth of the scientific workforce have been identified by industrial, governmental, and academic leaders as a primary concern for the U.S. economy. In 2010, Congress reauthorized the America COMPETES Act to increase funding for research and education in STEM fields, and President Obama’s Office of Science and Technology Policy asserted that “[t]he development of world-class talent in science, technology, engineering, and mathematics (STEM) is critical to America’s global leadership. Supporting women STEM students and researchers is not only an essential part of America’s strategy to out-innovate, out-educate, and out-build the rest of the world; it is also important to women themselves” (9). In 2015, the National Academies of Science, Engineering, and Medicine sponsored a national summit attended by prominent STEM labor experts and leaders to discuss the state of the U.S. STEM labor force and address current problems in STEM labor force participation (9). One expert in attendance noted that “China, India, Russia, and Japan are all producing more engineers than the United States is, and if this country does not figure out how to get more women and people of color to pursue STEM training and STEM-enabled jobs, the United States will not be competitive in the global economy because it will not meet future demand for STEM-capable employees” (10). Increasing the participation of women, including minority women, has received much attention, although the numbers still lag, particularly at the highest levels of education and position. The size of the U.S. STEM workforce is formidable (7.2 million and 6% of the total U.S. workforce in 2011) (11), but, as of 2012, women made up only 27% of the total science and engineering workforce, and only 1 out of 10 of these were women of color (12). The U.S. Census Bureau also reports that almost 1 in 5 STEM women graduates are out of the labor force, compared with 1 in 10 men (11). Moreover, even when women enter the STEM workforce, they are not advancing at rates on par with their male counterparts. In chemical and materials science, women make up 44% of all workers, but are much less likely than men to be employed in the industrial sector (12). Because the chemical industry is a key sector of the U.S. labor economy and the largest employer of U.S. scientists, the leaks in the pipeline between STEM degrees and STEM employment and advancement of women in industrial settings are particularly important. In 2012, graduates from underrepresented minority backgrounds earned 19% of bachelor’s, 17% of master’s and 11% of doctoral degrees (13), and approximately 16% of people with a bachelor’s degree were from an underrepresented minority group. This suggests that minorities as well as women are able to achieve success in terms of academic accomplishment, making all the more distressing the persistent lack of progress toward female and minority representation in STEM employment. The most recent NSF indicators note: “Underrepresented minorities’ share of S&E bachelor’s and master’s degrees has been rising since 1993, but their share of doctorates in these fields has flattened at about 7% for the past 10 years” (14). Rosser and Taylor decried “the attrition of women at every phase of the educational and career STEM pipeline. 117

Despite grades and other academic attainments equal to or surpassing those of the men who remain in STEM fields, more women than men leave science and engineering” (15). Unfortunately, the gender wage gap permeates the entire overall workforce, and persists for all categories of occupation, education, age, and race/ethnicity, with women of color earning less than White women and all women earning less than men (13). Within science specifically, National Science Foundation data on employed scientists and engineers indicates that, at all levels of education and occupational fields, men out-earn women (13). This gap does not close as women advance in their careers: in fact, younger women (age 20-25) are closer to pay equity (earning 92.3% of men’s earnings) than older women (76.4% of what men earn) (13). Across STEM occupations, compensation differences between men and women remain even when controlling for age, education, experience, performance, and other relevant variables; for example, women in physical sciences earn 78.9% of what men earn (the lowest percentage of all the science disciplines), with median salaries of $60,000 and $83,000, respectively (12). At current rates of change, it is estimated that the gender wage gap will not close until 2058 (16). In addition to the impact of gender biases, the literature suggests that racial stereotypes held by co-workers and managers may act as a substantial barrier to advancement for minority women (17). Studies of women in academic science roles suggest that the barriers to success and advancement associated with other nontraditional occupations may provide an important portal into understanding the experiences of women scientists. A study conducted at the University of Michigan examined tenured women faculty members’ experiences as STEM academics, a realm which men traditionally—and currently—have dominated. Stewart, Stubbs, and Malley (18) found that, although female faculty members in STEM fields reported high levels of satisfaction with their teaching experiences, research activities, and colleagues, they also reported high rates of gender discrimination (41% of female faculty compared to 4% of male faculty) and unwanted sexual attention (20% of female faculty compared to 5% of male faculty). Women faculty noted a lack of guidance and fewer mentoring opportunities than male faculty members. Additionally, women faculty reported a more hostile, unwelcoming workplace climate; this negative perception of climate was related significantly to lower overall job satisfaction, which has been linked clearly to retention, productivity, engagement, and loyalty in previous studies (19).

How Women in Chemistry Are Faring The participation of women in chemistry is increasing in terms of degree attainment, with 48% of bachelor’s degrees, 46% of master’s degrees, and 39% of doctoral degrees in chemistry obtained by women in 2014 (14). However, despite what appears to be an increasingly robust pipeline of women earning doctoral degrees in STEM fields, women scientists are largely absent from the highest ranks of career success in their fields. They are significantly less likely than men to hold management, senior management, or corporate officer roles within industrial settings (12); among S&P 500 companies in 2013, women held only 19% of 118

board seats, 80% of which were held by White women, 12% by African American women, 4% by Latinas, and 4% by Asian women (12). The 2016 Chemical and Engineering News (C&EN) annual survey indicated that women in the chemical industry are continuing to make small gains for the fourth year in a row but remain seriously underrepresented at leadership levels (20). Women currently occupy 16.2% of board seats at 45 U.S. companies and 13.2% of the executive office positions. Of the executive positions women hold, 33% are in Human Resources, 28% have Business Responsibility, 18% are Legal, 14% are Financial, and 7% are in Administration. Data from Catalyst indicate that the chemical industry is “behind the rest of the corporate world,” with 19.9% of board positions at S&P 500 firms held by women (20). By comparison, the C&EN survey indicates that, of thirteen top European chemical firms, 28.6% of their board seats are filled by women.

Challenges for Women in STEM Fields Why do these persistent gender patterns seem relatively impervious to change efforts? Explicit public assertions about women’s lack of scientific abilities (such as Summers’ comments) or inferior work (undergirding the Plos One comments) reflect implicit beliefs that many people still hold about women and science. Recent research suggests that many people believe that women are not associated with traits scientists are presumed to possess (21), and 61% of a sample of high school, undergraduate, and graduate women students report experiencing gender bias in the past year (22). Other research reveals that setbacks for men in STEM fields are attributed by others to external factors, while setbacks or failures for women are viewed as the fault of the women themselves (23). Even if people do not consciously espouse such beliefs, research on implicit bias posits that unconscious beliefs toward majority and minority groups are held that belie conscious attitudes, beliefs that may affect behavior (24). It is likely that such bias comes into play for STEM women during their careers, as insidious beliefs that women are less capable at science may affect hiring, advancement, and myriad other career opportunities (25). Data from more than 628,000 participants in a “Gender-Science Implicit Association Test,” for example, indicate that 52% had a strong or moderate automatic association of “male” with science and “female” with liberal arts; only 10% had such associations for “female” with science and “male” with liberal arts (23). It is important to note that women themselves (as well as members of other underrepresented groups) often internalize such biases and beliefs about their own capabilities. In addition to individual beliefs and biases, vocational psychologists who study career development processes have posited that systemic societal and organizational factors act as barriers to women’s success and advancement across disciplines, especially in nontraditional occupations. Specifically, Betz and Fitzgerald, in a now-classic book (26), outlined the multiple factors that disadvantage women and compromise their career development. These include such factors as negative workplace climates, occupational stereotyping and field segregation, lack of female role models and appropriate mentors, restrictive 119

gender role socialization, professional isolation, and discriminatory organizational practices in hiring, compensation, and evaluation, which act as barriers to women’s career advancement. These factors combine to create a “cumulative disadvantage” for women—that is, seemingly minor disparities that compound over time to result in gross inequities for women relative to their male peers—a disadvantage that has been shown to be more prominent in fields that are dominated by men (26–28). The vocational psychology literature also suggests that in fields where women are significantly underrepresented, societal and organizational factors intersect with women’s “self-concept” (an amalgam of various internal factors) to become multi-layered forces influencing success outcomes for talented women. Just as external variables (e.g., workplace climate, discriminatory practices) have been shown to be powerful predictors of women’s workplace experiences, internal factors (e.g., sense of self-efficacy, estimation of one’s own competence and knowledge, outcome expectations, levels of commitment, confidence and willingness to perform the tasks most frequently associated with advancement) also have been found to be related significantly to vocational outcomes. The literature further suggests that high career self-efficacy is a self-concept factor that is predictive of women’s persistence in scientific fields (26), and that persistence in the face of external barriers may be a key factor related to success for women scientists (4, 5). Recent research indicates that women who had experienced gender bias in the last year had lower STEM self-concepts than those who did not (22). Thus, exploring the intersection of external and internal factors is essential to understanding the constellation of barriers to and facilitators of women’s success. Women and the Home-Work Interface One of the most important determinants of women’s career entry, retention, and advancement involves the interface between the workplace and the home. The ability to achieve, maintain success, and advance in one’s career often is a difficult task that involves hard work, sacrifice, and managing competing desires and demands in and out of the office and lab. For many women, however, the demands of home disproportionately fall to them, thus potentially affecting the amount of time and energy they can or are willing to devote to the demands of advancement and increased responsibilities in the workplace. Despite radical shifts in family life over the past several decades, women are still responsible for the majority of family care and housework (29, 30). As members of the “sandwich generation,” women’s care demands may involve children, elderly parents/relatives, or both (29). Women may question their involvement in scientific careers early (e.g., during college), anticipating an inability to combine being a scientist with the future demands of home or family (31). Such questioning seems quite reasonable given the realities for working women with families. Recent research ranks the U.S. as one of the 10 worst countries for paid maternity leave (32), and childcare costs often are a barrier to employment for women (30). The “motherhood penalty” and “fatherhood bonus” persist, whereby men’s careers are boosted by having children, while women are penalized for their family responsibilities; on 120

average, men’s earnings increase 6% for each child, whereas women lose 4% of their earnings for each child they have (33). Female scientists and engineers who are unemployed or not in the labor force are far more likely to cite family responsibilities than are men (who are more likely to cite retirement) as a reason for unemployment (11). For millennials, literature suggests that the work-life balance is particularly important to them, such that they may be less willing to make the sacrifices currently required to advance into leadership roles. A recent study of millennial workers (34) indicates a significant drop-off over time in their expectation of advancing to the most senior levels in their fields (from 49% at the start of their careers, to 45% 4-8 years in, to 39% 9 or more years in). Of those respondents who aspired to an executive (or “C-suite”) position, only 38% were women, and only 31% of millennial respondents overall (versus 68% of older employees) held those aspirations. If issues of home-work conflict are not addressed by companies, it may be that the numbers of women in leadership positions will level off as millennials age (34). It thus is imperative that any exploration of women’s career success and advancement investigate how home roles may complement or compete with women’s career trajectories. Perhaps unsurprisingly, given the intransigence of traditional gender role ideologies, much research attention has been paid to negative effects when conflicts between family and work roles occur. Home-work conflict can manifest in different ways, that is, fulfilling obligations may be physically impossible (e.g., being in two places at once) or psychologically/emotionally taxing (e.g., simultaneously worrying about a sick child and an important presentation). The strain of managing multiple, sometimes competing, demands with limited time, energy, support, and resources can take its toll in multiple ways: home-work conflict has been associated with strain, depression, somatic problems, and decreased overall feelings of well-being (29). Research also suggests a “negative spiral” of home-work conflict, whereby the strain leads to increasing interpersonal friction with co-workers, that then gets brought home and affects the employee’s family, thus leading to additional strain (35). However, research also indicates that, overall, multiple roles are healthy for women (36). Simultaneously managing both professional and personal roles and responsibilities can create healthy opportunities and satisfactions. Active participation in work and family roles can provide greater possibilities for social support, meaningful interpersonal interactions, and increased income. Women who manage multiple roles also find increased opportunities to experience success and broaden their framework of life experiences (36). Recent work by Cheung and Halpern (37) proposes that the traditional concept of the home-work interface now can be understood as an integrated model (picture an overlapping Venn diagram of home and work spheres), rather than as two distinct and separate (and, presumably, competing) domains. In their review of successful women leaders, they found that women “redefined their own norms for being a good mother and being a leader, making these roles more compatible than they were under the norms prescribed by the larger society” (37). Despite the substantial body of literature on the intersection of work and family, insufficient attention has been paid to the positive effects of combining and integrating work and family roles. 121

In summary, although the loss of women from every point along the STEM career pipeline is well-documented, and although a great deal is known in the vocational psychology literature about challenges and barriers to women’s career development (including women in non-traditional careers), there has been insufficient research that brings these areas of study together. Moreover, little is known about the experiences of women in industrial settings more specifically, and even less about women who advance into leadership roles in industry. Little is known about how societal, occupational, organizational, family, and self-concept factors may influence the achievement and success of women chemists in industrial chemistry. Moreover, previous research provides only a partial view of the pathways to advancement for women, which Eagly and Carli (leading scholars in women’s leadership) have likened to a labyrinth, rather than a glass ceiling. This metaphor is thought to capture better the reality that career advancement for women does not consist of a straightforward trajectory of upward movement toward a clear goal suddenly and transparently blocked, but rather resembles a complicated maze of numerous opaque barriers to forward movement, with no clear goal in sight (38). Finally, existing research on women in STEM fields mostly elicits only the perceptions of women workers and fails to capture the points of view of managers—those who hold the bulk of the power in making the decisions that lead to women’s success and advancement, particularly in corporate settings. If the Plos One and Larry Summers examples we cited earlier are any indication, this represents a serious oversight in the research literature. This article and the subsequent two articles in our three-part series describe how Project ENHANCE attempted to address these gaps.

Project ENHANCE: Studying Women in the Chemical Industry This article and the two additional articles in the series report findings from Project ENHANCE, a multi-year investigation of the career experiences of women formally trained in science and engineering currently working in the chemical industry. The project utilized both quantitative and qualitative methodological approaches, with the broad goals of identifying factors that impede or facilitate women’s career success from the point of view of both women and management, and identifying corporate practices that contribute to positive workplace experiences and climates for women chemists. Project ENHANCE built upon the literature on women in nontraditional occupations by focusing specifically on industrial chemistry and paying particular attention to the experiences of diverse women in the industry (e.g. women of color, sexual minority women, and women with documented disabilities). One of the main goals of Project ENHANCE was to produce a resource for industry leaders: It’s Elemental: Enhancing Career Success for Women in the Chemical Industry (39), was distributed to industry leaders, and it provides a readable, accessible summary of our work. The three articles here provide greater detail regarding our methods and findings, and although our data are now several years old, the very recent example of blatant sexism with which we began this article speaks to the 122

disturbing likelihood that little change has occurred in industrial workplaces and to the continued relevance of our research. This article (Part 1), outlines the overall methodology of Project ENHANCE and presents specific results regarding women’s success, advancement, and job satisfaction, as well as company support and the home-work interface for women. The second article (Part 2) (7) in this series focuses on specific challenges for diverse women in the workplace, including organizational support and climate, mentoring, stressors and coping responses, and perceptions and use of company benefits. The third article (Part 3) (8) in the series focuses on management and compares the responses of women and managers, including their judgments regarding company initiatives aimed at supporting women, and it also offers a brief discussion of the challenges for women in leadership roles in the industrial sector. Methods of the Study Research for Project ENHANCE was conducted by a diverse, multidisciplinary research team. The research team consisted of one doctoral-level psychologist with expertise in women’s career development and 10 (then) advanced doctoral students in psychology. Two doctoral-level chemists (one employed in industry, one in academia) were co-investigators and consultants to the project, and our industrial consultant was particularly important in connecting us to industry leaders. Ten senior managers from the chemical industry served in an advisory capacity and guided our research team throughout the development and implementation of the study, including the recruitment of participating companies. Additional assistance was provided by professional societies, especially the Women Chemists Committee of the American Chemical Society (ACS). The multi-year investigation consisted of four main components and a follow-up study: Quantitative, anonymous, web-based surveys from 1,725 women and 264 male and female managers; voluntary qualitative interviews with 26 women and 6 male and female managers; and a follow-up qualitative interview study of mentoring with nine male managers (40). All participants in the investigation came from 25 Fortune 1000 chemical companies that were diverse in size and revenue. Solicitation of participants was made through company cooperation, with the assistance of the senior industrial leaders advising our study as well as professional societies such as the ACS Women Chemists Committee. Surveys were extensive (about 45-60 minutes to complete) and accessed electronically, and they focused on (for women) their professional experiences as women scientists and engineers and (for managers) their perceptions regarding their female employees in the areas of: a) Success, satisfaction, and advancement; b) organizational support, climate, and diversity; c) mentoring; d) stress and coping; e) the home-work interface; and f) company initiatives to facilitate career success. Companies notified employees of the study and encouraged participation, but responses were completely voluntary and anonymous. Women and managers who were willing to be interviewed indicated this separately from their surveys, and, from many dozens of volunteers, we selected interviewees 123

who were representative of the overall samples from which they were drawn; interviews averaged about 45-60 minutes in length. In terms of data analysis, we obtained descriptive statistics for all data in the Project ENHANCE study, and where relevant, we conducted formal quantitative analyses common in psychology and appropriate to the variables, sample sizes, and research questions of interest to us. Due to space constraints here, we cannot include detailed descriptions of the hundreds of analyses we carried out and the many statistical symbols and analytic conventions used to denote those analyses. Rather, we summarize here the broad categories of analyses we did, and we refer readers to reference 41 for a relatively brief, accessible explanation of quantitative and qualitative approaches to data analyses typical in psychology. Our quantitative analyses included: a) Assessing the psychometric properties of our instruments (e.g., internal consistency reliability, factor structure); b) obtaining correlations among variables to explore significant relationships: c) conducting analyses of variance (ANOVA), t-tests, and chi-square tests to compare similarities and differences among groups and sub-groups across variables; d) running regression analyses to establish the significant prediction of variables by other variables; e) completing all follow-up statistical tests demanded for interpretability in the various approaches; and f) making statistical adjustments due to unequal sample sizes, missing data, and the like. Due to the large sample sizes and considerable numbers of analyses we conducted, we used a very stringent standard for determining significance in our quantitative findings (p < .001), and we used a conservative cut-off (r = .25) for interpreting relationships among variables, according importance only to correlations that reached the .25 level or higher. In addition to analyzing quantitative data, we transcribed, coded, and interpreted hundreds of pages of narrative data from our interviews using a common analytic procedure for qualitative data, Grounded Theory (41). Again, due to space constraints here, we present the qualitative findings selectively and briefly, to illustrate or clarify more fully our quantitative findings. Participants in the Women’s Portion of the Study Participants whose experiences are detailed in the first two articles of this series were the 1,725 women who responded to our surveys and the 26 women from that sample who were tapped for interviews. Of the 1,725 respondents, 1,388 (82.5%) women identified as Caucasian/White, 104 (6.2%) identified as Asian American/Pacific Islander, 88 (5.2%) identified as African American/Black, 59 (3.5%) identified as Hispanic/Latina, and 1% or less identified as Arab/Middle Eastern American, American Indian/Native American, Multiracial, or other. The age range of the sample was 21-65. Twenty-five of the participants (1.5%) reported a documented disability. Fifty-one participants (3.1%) identified as sexual minorities (i.e., lesbian, gay, bisexual, questioning). All participants had completed a degree in higher education: 54.7% held bachelor’s degrees and 44.4% held higher than a bachelor’s degree. The number of dependent children at home ranged from 0 to greater than five; 370 participants (32.0%) had no dependent children, 306 (26.4%) had one dependent child, 370 (32.0%) had two 124

dependent children, and 112 (9.7%) had three or more dependent children living at home. Participants represented diverse functional areas within the chemical industry, with most working in technology (47.1%) and manufacturing (19.2%). Participants reported having varying numbers of supervisees; while the majority of women (63%) reported having no supervisees, 26.8% reported supervising 1-10 people, 7% reported supervising 11-50 people, and 3.3% reported supervising 51 to more than 500 people. Participants’ total compensation per year ranged from less than $25,000 to more than $500,000, with the majority (67%) earning $50,000-$100,000. Participants’ tenure in their positions ranged from less than a year to more than 10 years, with the largest group (49%) reporting 1-3 years in their current positions. In industrial settings, having supervisees is not necessarily indicative of a formal management position, which is determined instead by such factors as the number of direct (and indirect) reports, job title, and functional area. Detailed analyses of these chracteristics of our sample of women suggested that approximately one-fifth of them held positions in management (16.6%) or executive leadership (3.8%) that were equivalent to the sample of senior managers who were recruited for the management portion of our study. Further analyses revealed some significant differences between the “managerial” and “non-managerial” participants in the women’s portion of the study; thus, this “managerial” subgroup of the women participants was analyzed separately where appropriate. Because we conducted a parallel study of managers tapped specifically to provide a management perspective on our research questions, we distinguish between the two management groups of women throughout these articles: we use the descriptor “managerial women” to refer to participants in the women’s portion of the study who held degrees in chemistry and engineering and whose positions were essentially managerial in nature but who responded to our surveys based on their own experiences as women; and (primarily in the third article in this series) we use the descriptor “female managers” to refer to female participants in the management portion of the study who were recruited specifically from senior management ranks to provide a “management” perspective on conditions for women in their employ (although many of these held degrees in chemistry, a number of them held other degrees such as MBAs). [More detailed description of participants in the management portion of our study and the follow-up study of managers and mentoring can be found in the third article in this series (8)]. Measures Our extensive surveys were designed to assess the areas of success and advancement, workplace climate and support (including mentoring), the home-work interface, issues of diversity in our samples, perceptions of management regarding women employees, and existing initiatives aimed at supporting women. As one of our goals was to determine whether or not women and managers agreed on issues related to women’s success in industrial chemistry, we administered parallel forms of our surveys to each of the two main samples 125

in our study (women and managers). As far as possible, items were identical in both surveys, except that women responded based on their own experiences, whereas managers (both male and female) responded to most items based on their perceptions of their women employees who had been trained in science and engineering. The following descriptions apply to both of these parallel surveys.

Demographics Participants were asked to report on a wide range of personal, job, and company variables (e.g. race/ethnicity/sexual orientation, title, number of supervisees, total annual compensation, company type/size, etc.). Additionally, participants were asked about their (or, for managers, their women employees’) leadership aspirations using a 4-point scale that assessed their desire to advance. Participants were also asked to report whether a variety of benefits (e.g., “childcare subsidy on site”) were provided by their companies, and, for women, whether they had used each of those benefits.

Success Standard indicators of success (SIS) are external, objective, easily quantified variables that capture aspects of how individuals are assessed by others. However, some researchers have suggested that measures of success should include both other-referent and self-referent measures (42), and that job satisfaction may be one of the most salient aspects of self-referent, subjective career success (43). Thus, both SIS (position title, total compensation, and number of current supervisees) and job satisfaction (“Overall, how satisfied are you with your current job/position?”) were assessed. Our study used both a standard global single item measure of job satisfaction (44) and a researcher-constructed 3-item “Career Satisfaction” scale (reliability =.70). We report only the one-item measure in these articles, as it was statistically shown to be the most relevant to the rest of the variables we studied (reliability =.77).

Beliefs about Career Advancement Women’s and managers’ own beliefs about career advancement were assessed by a 20-item researcher-constructed measure. The beliefs involve what is thought to be necessary to achieve career advancement (e.g., “Getting ahead in one’s job requires continuous upgrading of skills.”). Each item was scored on a 5-point scale from 1 (strongly disagree) to 5 (strongly agree). The items were not summed into full scale scores because they do not inherently each have a positive or negative valence; rather, they were examined for patterns of endorsement across samples.

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Willingness and Confidence to Advance Women’s own willingness (and managers’ perceptions about women’s willingness) to engage in tasks needed to obtain or maintain a leadership or managerial position and their confidence (or perceived confidence) in their ability to do those tasks were assessed using a 14-item researcher-constructed measure. Sample items included, “Engage in substantial travel to operational and customer locations,” and “Defend your vision or what you think is appropriate in the face of upper management opposition.” The Willingness scale was scored on a 5-point scale from 1 (very unwilling) to 5 (very willing), and the Confidence scale was scored from 1 (no confidence) to 5 (complete confidence). Higher scores on each scale indicated more willingness and confidence. Both scales exhibited high reliability (.85 and .88, respectively).

Home-Work Conflict Pressures in the home-work interface, more commonly known as home-work conflict, were measured by selected items of the Work-Family Conflict Scale (45) as well as additional items generated by the researchers to more fully cover concerns that might apply to women in the chemical industry. Sample items included, “My work keeps me from personal/family activities more than I would like” and “Due to all of the pressures at work, sometimes when I come home I am too stressed to do the things I enjoy.” The scale contained 14 items, scored on a 5-point scale from 1 (strongly disagree) to 5 (strongly agree). The possible range for full scale scores for the instrument was 14-70, with higher scores indicating a higher level of conflict felt by women (or, for managers, perceived to be experienced by their female employees). In the current sample, the reliability estimate for the full modified scale was .81.

Confidence Regarding the Home-Work Interface Women’s confidence in their ability to manage the demands of home and work (or manager’s perceptions of women’s confidence) was measured by a slightly modified version of the Self-Efficacy Expectations for Role Management Scale (46). Modifications were made to provide a more inclusive definition of “family” and items were eliminated to shorten the scale. In the current study, the scale consisted of 15 items, scored on a 5-point scale from 1 (no confidence) to 5 (complete confidence). The possible range for full scale scores for the modified instrument was 15-75, with higher scores indicating greater confidence. In the current sample, the reliability estimate for the scale was .78.

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Workplace Climate Workplace climate was measured by selected, modified items of the Organizational Diversity Inventory (ODI (47)) and the Sexual Experiences Questionnaire (SEQ (48)), as well as items generated by the researchers to include an assessment of company policies surrounding diversity, e.g., “I am proud of my company’s track record regarding diversity (gender, race, disability, etc.).” The ODI is composed of five subscales measuring existence of discrimination, discrimination against specific groups, managing diversity, actions regarding minorities, and attitudes toward religion. The SEQ measures three categories of sexual harassment that women experience: gender harassment, unwanted sexual attention, and sexual coercion. The measure used in the current study consisted of 14 items scored on a 5-point scale from 1 (strongly disagree) to 5 (strongly agree); some items were reverse scored. Mean item scores were calculated, with high scores indicating a perception of one’s own (or one’s female employees’) workplace climate as positive/tolerant (reliability = .84).

Support of Supervisors and Coworkers Support was measured by a modified version of an instrument by House and Wells (49). The measure was composed of three subscales measuring different types of social support for work-related experiences from three potential sources of social support (i.e., friends/family, coworkers, supervisors). Each subscale contained five items scored on a 5-point scale from 1 (rarely) to 5 (always). The possible range for each subscale was 5-25, with high scores indicating higher levels of perceived social support for work-related experiences from friends/family, coworkers, and supervisors (or, for managers, perceptions of women’s support from those sources). In the current sample, we used only the supervisor and coworker subscales, with reliability estimates for the coworkers support subscale and supervisor support subscale of .90 and .95, respectively.

Company Support (CS) Beliefs about current company support were measured using a modified version of the short form of the Perceived Organizational Support survey (POS (50)), and the Worker Empowerment Scale (WES (51)). Twenty-one items composed the scale, with possible responses on a scale ranging from 1 (strongly disagree) to 5 (strongly agree). High scores indicated greater beliefs that one’s company is supportive. In this sample, the reliability estimate was .92. For the current study, a principal components analysis was conducted and resulted in a three-factor solution, accounting for 52.7% of the variance. The variance accounted for by the first factor was 23.9%; 14.9% for the second factor; and 13.9% for the third factor. The three factors were described as Perceived Organizational Support, Perceived Discrimination, and Connections 128

and Opportunities. Because these factors (or subscales) were used in the present study as individual measures, they are described further below.

CS/Perceived Organizational Support The first factor of the Company Support measure formed the subscale “Perceived Organizational Support.” This factor consisted of twelve items, eight of which were items from the POS (49) and four of which were generated by the researchers. Sample items include, “My company values my job-related opinions” and “Help is available from my company when I have a problem.” This measure contained twelve items which were scored on a 5-point scale from 1 (rarely) to 5 (always). Scores were obtained by averaging the item scores, with a possible score range of 1-5, higher scores indicating higher levels of perceived organizational support. In the current sample, the reliability estimate was .89.

CS/Perceived Discrimination The second factor of the Company Support measure formed the subscale “Perceived Discrimination.” This factor consisted of five researcher-generated items designed to assess participants’ experiences with company support as related to gender. Sample items included, “Men and women get treated very differently in this company, with men at an advantage.” The Perceived Discrimination measure contained four items scored on a 5-point scale from 1 (rarely) to 5 (always). Scores were obtained by averaging the item scores, with a possible score range of 1-5, higher scores indicating lower levels of perceived sexist discrimination. In the current sample, the reliability estimate was .85.

CS/Connections and Opportunities The third factor of the Company Support measure formed the subscale “Connections and Opportunities.” This factor consisted of five items, two of which were items from the WES (50) and three of which were generated by the researchers. Sample items include, “In my company, I have opportunities to contribute to visible projects where my accomplishments will be noticed” and “I am well-networked and respected in my company.” The Connections and Opportunities measure contained five items scored on a 5-point scale from 1 (rarely) to 5 (always). Scores were obtained by averaging the item scores, with a possible score range of 1-5, higher scores indicating higher levels of perceived access to networking and other opportunities. In the current sample, the reliability estimate was .74. 129

Presence of Mentor(s) Participants were asked whether they have (or are perceived by managers to have) one or more mentors in their current companies/workplaces; the number of mentors they have in the current companies/workplaces; whether participants wish they had a mentor if they currently do not have one; and, for those identifying at least one mentor, their most influential mentor’s age, race/ethnicity, gender, and sexual orientation, if known.

Mentoring Extent and Adequacy Extent and adequacy of mentoring as judged by women (or manager’s perceptions of women’s experiences) were assessed using the University of Michigan’s Survey of Academic Climate and Activities (51). Each item asks the extent to which a mentor performs a given task, and the perceived adequacy of the mentor’s efforts regarding that task. An example of a task is “promotes my career through networking.” Fourteen items composed the measure, with respondents answering on a 5-point scale ranging from 1 “rarely” to 5 “always.” Scale scores were obtained by summing the item scores, with higher scores indicating more mentor involvement and satisfaction with mentor’s assistance in professional development. The reliability estimates for the measures of mentoring extent and adequacy in this study were .93 and .94, respectively.

Perks and Benefits Participants completed a researcher-created measure titled “Perks and Benefits,” where they were asked to indicate whether various benefits (e.g., “health care benefits,” “child care subsidy or site”) were provided by their companies, and whether they had used these benefits. Participants also were asked whether they had negotiated for any “perks” (e.g., “lab space allocation,” “moving and relocation expenses”), and if so, whether they were satisfied with what emerged from negotiations. Participants chose between yes or no for all items, and were provided a third option of “Don’t know” where they were asked which benefits were provided (this measure was not administered to managers).

Recognition Participants were asked to report the recognition they had received in their companies. With yes/no questions, they were asked whether they had ever been nominated for a professional award or honor, whether they had ever received a professional award or honor, whether they had ever failed to receive a nomination for a professional award or honor for which they felt qualified, and whether they had ever failed to receive an advancement opportunity for which they had applied 130

or expressed interest and for which they felt qualified (this measure was not administered to managers).

Stress and Coping Women were asked to list up to three of the most critical work-related stressors they faced and, for each of the stressors listed, to indicate at least one coping strategy they use to manage that stressor (managers were asked to list what they believed to be the most important work-related stressors for their female employees). To code the data, researchers analyzed the responses, performing independent and dyadic coding, then determining best assignment of data by consensus. All data were categorized. A final list of three broad stressor categories was created: Workplace Difficulties, Professional/Personal Life Intersection, and Company Support. Fourteen specific sub-categories also were created. Five sub-categories of Workplace Difficulties included: a) time, b) tasks and responsibilities, c) interpersonal issues with coworker, d) interpersonal issues with management, and e) sexual harassment/treatment based on gender. The five subcategories of Professional/Personal Life Intersection included: a) parenting issues, b) partner issues, c) personal, graduate school, hobbies, and medical issues, d) travel and commute, and e) financial struggles. The four sub-categories of Company Support included: a) benefits/perks, b) job security, c) salary/wage, and d) resources. There were 4,026 total stressor responses provided for Stressors 1, 2, and 3 combined. Data on coping strategies were coded in the same manner as stressor data. Six broad categories were created: Seeking Workplace Help, Personal Help, Seeking Company Help, Avoidance, Proactive Steps, and Don’t Know How to Cope. Subcategories also were created. Two sub-categories for Seeking Workplace Help were: a) supervisors and b) coworkers. Six sub-categories for Personal Help were: a) focusing on the positive/keeping a positive disposition, b) keeping to self/selfreliance, c) tension reduction (e.g., exercise, meditation), d) seeking family and outside support, e) religion/spirituality/faith and f) crying. Four sub-categories of Proactive Steps were: a) time management (personal and work), b) making lists/ organizing/prioritizing, c) planning for career/work transitions (e.g., retirement, continuing education), and d) personal/career/work sacrifice (e.g., choosing not to pursue career advancement or cutting work hours). There were 3,943 total coping responses provided for Coping responses 1, 2, and 3 combined (coping items were not administered to managers).

Results and Discussion In this first article of our three-article series, we provide a broad overview of our findings from the women’s portion of the study. We investigated: a) How satisfied and successful are women and what predicts success and job satisfaction?; b) Do success and satisfaction differ across important status variables (e.g., race/ 131

ethnicity, sexual orientation, disability)?; c) How willing are women to take on tasks to advance, and how confident are they in their ability to do so?; d) How does company support relate to success?; and e) How does the home-work interface relate to women’s career success? We present our quantitative findings below, with brief discussion of those findings and illustrative quotations from our interviews to further clarify and elaborate on our findings.

How Satisfied and Successful Are Women Working in Industrial Chemistry? The majority (approximately 2/3) of women in our study reported salaries between $51,000 and $100,000, with one-quarter earning between $100,000 and $200,000. More than two-thirds (69%) were individual contributors to their organizations, and those in supervisory roles reported between one and ten supervisees. Racial/ethnic minority women were less represented than White women in positions at higher levels, with higher salaries, and with greater numbers of supervises, findings consistent with previous research regarding women of color in the workplace. Table 1 (below) shows the descriptive statistics (means and standard deviations) for the satisfaction, success, and support variables examined in this sample of women working in industrial chemistry. As the table shows, women chemists reported moderately high levels of job satisfaction (M = 3.71, SD = .80) overall. Although both the “managerial” and “non-managerial” subgroups of women tended to have moderately high job satisfaction, comparison analyses indicated that non-managerial women reported significantly lower job satisfaction than did managerial women (p < .001). Due to limited numbers of women chemists in racial minority subgroups, we were unable to perform statistical analyses comparing women of racial subgroups to one another on most of the variables in this study. Instead, we combined the women of color into one subgroup and compared them to the subgroup of White women on job satisfaction and standard indicators of success, as well as willingness and confidence to advance. Combining all racial/ethnic minority subgroups into one yielded 337 women of color. Although this is an unusually large number of women of color in vocational psychology research (particularly women of color in STEM fields), it is still relatively small in comparison to the number of White women (1,388) in our sample, although we adjusted for unequal sample sizes in our analyses (and our reporting accounts for this). Our analyses of racial/ethnic differences in job satisfaction indicated that women of color, sexual minority women, and women with disabilities were significantly less satisfied than White, heterosexual, and non-disabled women (p < .001).

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Table 1. Satisfaction, Success, and Support Variablesa Variable

M

SD

Entire women’s sample

3.71

.80

Women’s sample, non-managerial

3.65

.81

Women’s sample, managerial

3.96

.74

Entire women’s sample

3.81

.62

Women’s sample, non-managerial

3.73

.62

Women’s sample, managerial

4.13

.54

Entire women’s sample

3.76

.61

Women’s sample, non-managerial

3.68

.60

Women’s sample, managerial

4.07

.51

Entire women’s sample

3.31

.59

Women’s sample, non-managerial

3.30

.58

Women’s sample, managerial

3.40

.62

Entire women’s sample

3.15

.95

Women’s sample, non-managerial

3.14

.96

Women’s sample, managerial

3.19

.91

Entire women’s sample

2.94

1.2

Women’s sample, non-managerial

2.90

1.2

Women’s sample, managerial

3.07

1.2

Entire women’s sample

3.26

.58

Women’s sample, non-managerial

3.26

.58

Women’s sample, managerial

3.23

.58

Job Satisfaction

Willingness to advance

Confidence to advance

Company Support

Coworker support

Supervisor support

Workplace Climate

a M = Mean, SD = Standard Deviation, score ranges can be found in the Measures section. As noted in the text, several differences were found that were statistically significant using very conservative criteria, despite apparently similar Means in the table.

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In analyses predicting success variables among non-managerial women, job satisfaction was predicted significantly by company support (β = .58) and supervisor support (β = .12). Among standard indicators of success (total compensation, position title, number of supervisees), total compensation was predicted significantly by company support (β = .21), by confidence to advance (β = .26), and negatively by workplace climate (β = -.17). Position title was predicted significantly by confidence to advance (β = .16). None of the variables significantly predicted number of supervisees. Similarly, among women in managerial roles, company support predicted job satisfaction (β = .46) and total compensation (β = .22), but also predicted number of supervisees (β = .24); none of the variables significantly predicted position title. Thus, for both the managerial and non-managerial participants in the women’s sample, the strongest predictor of both job satisfaction and the standard indicators of success was company support. Interestingly, while company support and confidence in their ability to perform tasks associated with advancement predicted compensation level for non-managerial women chemists, workplace climate was shown to have a negative predictive relationship. One possible explanation for this negative predictive relationship may lie in a closer examination of the conceptual underpinnings of company support and workplace climate. While company support refers to the extent to which companies convey their valuing of employees and their willingness to invest in them—in short, their “best intentions”—workplace climate, a variable which aims to capture responses to diversity and experiences of discrimination and harassment, might provide a snapshot of what actually occurs in work environments. Higher salaries may reflect women who have been in the company for longer periods of time, and consequently perhaps have encountered barriers and other negative events not (yet) experienced by newer employees. In terms of significant relationships among variables, our analyses revealed that, for non-managerial women chemists, job satisfaction was correlated positively and significantly with all three types of perceived support (company, r = .62; supervisor, r = .42; and coworker, r = .28), as well as with workplace climate (r = .32). Among managerial women chemists, however, job satisfaction was correlated positively and significantly with perceived company support (r = .55), supervisor support (r = .34), and workplace climate (r =.38), but not with coworker support. Overall, then, company support and (particularly as manifested in) supervisor support appeared to be the most important variables explaining the job satisfaction and success of both managerial and non-managerial women. For both non-managerial and managerial women, although statistically significant relationships emerged between the standard indicators of success (compensation, position, supervisees) and job satisfaction, none occurred at the magnitude of our r =.25 cutoff, suggesting that job satisfaction was distinct from traditional indicators of success for these women overall.

Do Women Have the Willingness and Confidence to Advance? As Table 1 (above) indicates, women overall reported being willing to advance (M = 3.81, SD = .62), and confident in their ability to do so (M = 3.76, SD = 134

.61). In the words of one woman, “I think you can pretty much interview for any job you want and be considered for it. I think in the past, that wasn’t the case. They didn’t really want women in certain areas.” Women of color reported greater willingness to do tasks associated with advancement than did White women. The majority of women in the sample (two-thirds) indicated that they wanted to obtain or maintain leadership positions. As one participant said, “I am where I want to be professionally. I’m not finished yet but I have a path forward, I have a plan for it and I have the opportunity...if not in this company then somewhere else. I don’t feel if it doesn’t work here it won’t work elsewhere.” For managerial women, two of the three standard indicators of success were related significantly to advancement variables; specifically, total compensation and position title were correlated positively with willingness (r =.35 and r =.32, respectively) and confidence (r =.36 and r =.28, respectively) to perform tasks necessary for advancement. This is in contrast to the non-managerial women chemists, for whom confidence was associated significantly only with compensation (r =.22), suggesting some interesting differences in the way in which confidence and willingness variables may operate in different subgroups of women. Although the women in our sample expressed both willingness and confidence in advancing, a full 44% of them reported that they had failed to receive an advancement opportunity for which they had applied or expressed interest and for which they felt qualified. The fact that almost half of the women in this very large sample reported experiences of having been passed over for advancement opportunities may speak to the barriers still firmly in place in industrial chemistry. In the words of one participant, “We can fight in combat, but we can’t be CEOs.” As might be expected, racial and sexual minority women appear to be faring more poorly than White, heterosexual women on some of the success and advancement variables. Heterosexual women reported significantly higher job satisfaction than sexual minority women, reported a better workplace climate, and perceived more company support. Although women of color reported significantly higher levels of willingness to do the tasks associated with advancement than White women, they appear to be receiving, on average, lower levels of compensation, lower supervisory status, and lower position titles. [The second article (7) in this series explores in greater detail the experiences of diverse women in our sample.] Table 2 (below) shows the top five beliefs about career advancement expressed by the non-managerial and managerial women participants. Although not analyzed statistically, it can be seen in the table that both non-managerial and managerial women endorsed similar beliefs about what it takes to advance. The notable exception is that managerial women believed in the importance of willingness to take risks, which was not a top belief for non-managerial women, who instead expressed the belief that advancement is one’s own responsibility. It is possible that women who already have attained managerial roles (in comparison to women who have not) recognize the impact of others on their career trajectories, and also are conscious of the personal risks and sacrifices they have made to attain those positions. 135

Table 2. Comparison of Top Five Endorsed Beliefs about Career Advancement Women’s sample

1. To get ahead, it is important to be on highly visible projects where contributions can be recognized and rewarded.

(non-managerial)

2. Having executive presence and the ability to talk to senior leadership is a critical element to career advancement. 3. Getting ahead in your job requires continuous upgrading of skills. 4. How you look and fit into company culture is key for career advancement. 5. Advancement in your career is primarily your own responsibility.

Women’s sample

1. Having executive presence and the ability to talk to senior leadership is a critical element to career advancement.

(managerial)

2. To get ahead, it is important to be on highly visible projects where contributions can be recognized and rewarded. 3. To get ahead, you have to be willing to take risks (e.g., accepting a promotion even if you feel not fully prepared to do the job). 4. Getting ahead in your job requires continuous upgrading of skills. 5. How you look and fit into company culture is key for career advancement.

We also tested for relationships between specific beliefs about career advancement and success variables. The item “Getting ahead in your job requires continuous upgrading of skills” was the only item that correlated with any of the success variables (specifically, positively with job satisfaction, r =.31) at a level that exceeded our .25 cut-off, although the item “Women generally have to work harder than men to prove themselves in the workforce” approached our cut-off (r = -.23), and also correlated (negatively) with job satisfaction. How Are Women Faring in the Home-Work Interface? Women in this study reported relatively mild levels of home-work conflict on our quantitative measures overall (M = 2.32 on a five-point scale). This may be due to the fact that less than half (46%) of the sample indicated at least one dependent child at home. Analyses indicated that the more children women reported having, the higher overall level of home-work conflict they reported (r = .49), and more than half of the women in the sample (62%) reported managing 136

home and work responsibilities as among their top two work-related stressors, with specific difficulties in: a) having enough time with family; b) excessive time spent commuting between home and work; c) caring for aging parents; and d) concerns about health. Notably, every one of the women interviewed discussed some aspect of home-work conflict. Managerial women and women earning between $101,000-$200,000 reported significantly higher levels of home-work conflict than those earning $51,000-$100,000, perhaps because geater supervisory responsibilities may lead to longer work hours and thus increased conflict. Women reported feeling moderately confident in their ability to manage home-work conflict overall (M = 3.32), and women with children reported significantly more confidence in their ability than those without (M = 3.51 and 3.16, respectively). Women who indicated that their company provided childcare facilities (44%) reported significantly less overall home-work conflict than those who indicated no childcare facilities provided by their company (M = 2.25 and 2.50, respectively). In interviews, some women suggested the importance of company policies and climate in their decision-making about integrating work and family; one woman said, “You know, it will probably come to a place where, for my family, I need to progress in my career a little bit more, and if I’m not able to do that or if the company is not, you know, friendly enough, then I’ll make a decision…” Although mentoring is discussed in detail in the second article in this series (7), it is worth noting in the context of the home-work interface that women with female mentors (less than 30% of the sample) reported significantly greater advisement from mentors about managing work and personal life than did women with male mentors (M = 2.73 and 2.39, respectively). This finding is consistent with literature suggesting that male mentors tend to focus on task support, while female mentors focus on both personal/emotional and task support (7). The correlation between home-work conflict and job satisfaction found in our sample was small and non-significant (r = -.03), and is somewhat puzzling. The relationship between home-work conflict and negative job-related outcomes documented in the literature (which includes women across many occupational and compensational levels) (29) would predict higher scores, suggesting that there may be something unique about this population of women. It may be that the relative financial stability accorded to women with STEM salaries aids in managing home and work by providing greater resources for daily home maintenance and childcare, as well as for crisis management when necessary. The finding that having more dependent children was associated with higher levels of home-work conflict in our sample is entirely consistent with the literature documenting increased responsibility associated with caring for children. As one participant explained, “Because even though there are some stay-at-home dads here, there are very few. So we [women] end up having to do it and the only way we can is with flexible time.” Along with increased conflict, however, women with children in our sample reported higher levels of confidence in their ability to manage the home-work interface than those with no children. Perhaps women with children have had greater exposure to work-home conflict and have developed strategies to negotiate these competing roles successfully; alternatively, women with lower levels of confidence may simply choose not to have children, or may 137

represent more of the younger women in our sample who have not yet incorporated children into their lives. In our sample, being a manager or supervisor was related significantly to higher levels of home-work conflict than being an individual contributor. This result is consistent with extant literature. Those who hold extensive supervisory or managerial responsbilities may be under greater demand at work, and therefore experience increased strain in this role. Increased strain in one’s work role may take time, energy, and resources away from non-work roles, thus creating conflict. This speculation is supported by our finding that higher annual earnings were associated with significantly higher levels of home-work conflict. It is likely that increased earnings represent increased work responsibilities (e.g., longer hours in the workplace, traveling, and/or shouldering additional tasks), which, in turn, may lead to less time and energy for other roles, resulting in higher levels of home-work conflict.

Implications and Future Directions Project ENHANCE obtained data from a large number of women working in industrial chemistry, increasing the body of knowledge about a population that rarely has been studied. A primary strength of our study is the large and representative sample of women scientists and engineers, producing reasonably generalizable results. In addition, the large sample size allowed us to assess many constructs without compromising statistical power in our analyses. The study also surveyed a relatively large number of racial/ethnic and sexual minority women, compared to that typically found in research in this area. Moreover, the mixed-methods approach of combining quantitative and qualitative data is a strength of the study, as is the extensive use of advisory input from consultants and leaders in the chemical industry throughout every phase of the project. However, the study is not without limitations. Self-report measures are subject to a variety of external influences and interpretations, and we can report only on the snapshot of experiences that our participants provided. Additionally, most participants came from companies that formally participated in, and therefore endorsed, our study. It is possible leaders of companies who felt confident in their ability to provide a fair and positive workplace climate were more likely to participate in this study, and that could have affected some of our obtained results. Moreover, while this study explicitly sought the voices of marginalized women (e.g., women of color, sexual minority women, women with disabilities), we struggled with obtaining large enough samples of these groups to make meaningful comparisons. This was particularly unfortunate for women with disabilities in our sample, as the small numbers prevented us from conducting detailed analyses of their experiences. Given that scientists without disabilities out-earn those with disabilities (45), we might assume that women with disabilities are disadvantaged in the industrial workplace, but we could not ascertain this with certainty. Unfortunately, the overall underrepresentation of racial/ethnic and sexual orientation minorities and people with disabilities in our sample is reflective of the current state of industrial workplaces and in STEM fields more 138

broadly. It seems clear that additional studies of the experiences of women in STEM workplaces who are further marginalized by other status characteristics (e.g., race/ethnicity, sexual orientation, gender expression, disability, age, and immigration status) are very much needed. There are several other important future directions for research suggested by our study. For both managerial and non-managerial women chemists, company support seemed to tap into both tangible markers of success and satisfaction with their jobs. Future research might explore how company support is experienced by women with differing self-concepts and facing varying types of barriers. In addition to elucidating the gaps that may exist between managerial women chemists and non-managerial women chemists, future research might explore the source of these gaps and the means of addressing them effectively in the workplace. Our explorations of the home-work interface revealed some puzzling results; for example, women in this study did not report high levels of overall home-work conflict, but did report it as a primary stressor. It may be that women have developed coping strategies, have supportive partners or communities, or have come to understand home and work in ways that prevent or mitigate conflicts that are reported repeatedly in existing research on the home-work interface. Recent literature suggests the importance of supportive romantic partners for women undergraduate STEM majors who are anticipating balancing home with career (52) and the importance of peer support to female science students to buffer the negative impact of gender bias (22). Such relationships may continue to have an impact as women move into professional careers and consider their career aspirations and goals. Data from our study bear this out, as one woman in a managerial role observed: “The [women] that are most successful are the ones that have a strong agreement with their husband...how hard they can push and how [much] the husband will pick up the slack.” Research on successful female leaders also highlights the importance of a supportive partner or spouse even at the highest levels (36). Future research might attend to partner support for lesbian women in STEM fields, as social scripts and gender roles may provide greater flexibility and allow for different kinds of support; examining the career trajectories of lesbian women as they intersect with personal lives may offer unique insights about managing the home-work interface. In sum, our findings suggest that additional research that explores relationships between home and work roles for women scientists (both in management and individual contributor roles) is very much needed. Implications for the Industrial Workplace Our findings have important practical implications for industrial workplaces. In terms of success and advancement, the fact that company support, particularly as manifested by supervisors, was a critical factor in women’s success (both in tangible indicators such as compensation as well as personal satisfaction with one’s job) suggests that company leaders should attend carefully to ensuring that their workplaces are perceived as supportive. Supervisors constitute the front line in communicating support, as they are the face of the 139

company with which women interact most regularly, and their attitudes can have a deep impact (perhaps not always conscious) on the career trajectories of women employees. Our findings that women exhibited both willingness and confidence to advance, that managerial women exhibited higher job satisfaction than non-managerial women, and that a large percentage of women perceived themselves as having been passed over for advancement opportunites is a clarion call for company leaders to implement encouraging, fair, and transparent mechanisms for tapping into women’s advancement talents and desires. Moreover, although offered tentatively, our finding that women further marginalized by status variables such as race/ethnicity, sexual orientation, and disability appear to be faring less successfully than their majority counterparts suggests the need for company leaders to examine their company data thoroughly to determine whether there are differential patterns of retention and achievement based on status variables. In regard to the critical home-work interface, our results indicating that managing home and work emerged as a top work-related stressor, that women with more dependent children and more managerial responsibility indicated greater home-work conflict, that company-provided childcare was associated with less home-work conflict, and that female mentors were more likely than males to provide support for the managing the home-work interface all lend credibility to the importance of this arena for women in the workplace, and also suggest areas where company leaders may intervene successfully. Data can be gathered by individual companies to assess how best to enable women (and men) to integrate home and work effectively. Company policies, practices, and initiatives can be examined for patterns of use and outcomes (e.g., who is actually using parental leave and is it producing specific outcomes?), and company culture can communicate a supportive attitude about integrating work and personal lives (providing childcare and eldercare facilities or subsidies is the most obvious example of supportive structures that could be put into place). Finally, given that most mentors in current industrial workplaces are men, company leaders can mentor their mentors in how to talk about and support their female mentees regarding this arena that is so crucial to success for women in the workplace In conclusion, it is the hope of the Project ENHANCE team that this work will stimulate new thinking and creative strategies for maximizing the success of women scientists and engineers. Companies have extraordinary power to ameliorate or eliminate barriers to women’s success in industrial workplaces, and many experts agree that the very survival of science in the U.S. depends on corporate attention to the professional experiences of women scientists and engineers.

Note The contents of this article do not represent the views of the Department of Veterans Affairs or the United States Government.

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Acknowledgments Project ENHANCE was supported by a grant from the National Science Foundation. We especially thank Judith C. Giordan, our industrial chemistry consultant and co-investigator, for her many important contributions to our study. We also thank our academic chemistry consultant and co-investigator, Sandra C. Greer, and the following: Company leaders who assisted us (Lissa Dulaney, Sharon Feng, David Greenley; Elaine Harris, Ned Polan, Pamela Roach, Susan Stanton, Jennifer Weinberg, Bob Wikman, and Frankie Wood-Black); professional society leaders who supported us, particularly the ACS Women Chemists Committee (Amber Hinkle, Jody Kocsis, and Carolyn Ribes); and the many, many women and men who provided us with important data about their experiences in industrial chemistry.

Author Note This article is based on preliminary drafts written by V. Downing, M. Roffman, K. Kettlewell, and T. Berman, and on the resource created by our team for industry leaders (39), written by R. Fassinger, J. Arseneau, J. Paquin, H. Walton, and our industry consultant and co-investigator, Judith C. Giordan. Additional team members who contributed to this research are Sheetal Patel and Susanna Gallor.

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Chapter 6

Career Success of Women in the Chemical Industry, Part 2: Navigating Workplace Challenges Julie R. Arseneau,1 Penelope A. Asay,2 Jill D. Paquin,3 Heather M. Walton,4 Vanessa Downing,5 Melissa S. Roffman,6 and Ruth E. Fassinger7,* 1Southeast

Louisiana Veterans Health Care System, New Orleans, Louisiana 70161, United States 2Illinois School of Professional Psychology, Chicago, Illinois 60601, United States 3Chatham University, Pittsburgh, Pennsylvania 15232, United States 4Veterans Affairs Boston Health Care System, Brockton, Massachusetts 02301, United States 5Christiana Care Health System, Newark, Delaware 19718, United States 6Baptist Health, AgeWell Center for Senior Health, Jacksonville, Florida 32207, United States 7University of Maryland, College Park, Maryland 20742, United States *E-mail: [email protected]

This is the second of three articles where we report findings from Project ENHANCE, an investigation of the career experiences of women trained in science and engineering and working in the chemical industry. The project utilized both quantitative and qualitative methodological approaches, with the broad goals of identifying factors that impede or facilitate diverse women’s career success from the point of view of both women and management, and identifying corporate practices that contribute to positive workplace experiences for women in industrial chemistry. The first article in the series presents all of the project methodology and broad, overall findings related to success, satisfaction, advancement, company support, and the home-work interface. This, the second article in the series, focuses in particular on challenges in the workplace for

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diverse women, including organizational support and climate, mentoring, stressors and coping responses, and perceptions and use of company benefits. The third article in the series presents comparisons between women and management in their experiences and perceptions of women working in industrial chemistry, including their judgments regarding company initiatives aimed at supporting women, and also offers a brief discussion of leadership issues for women in this sector.

Introduction Women’s underrepresentation in science and engineering is well documented and much discussed. Although women scientists continue to approach parity with male scientists in employment (composing 44% of all chemists and material scientists in the American workforce as of 2012), they are much less likely to be employed in the industrial sector, the largest employer of science and engineering workers (1). Most previous research on women scientists and engineers has focused on women working in academia, and relatively little is known at present about the experiences of women scientists and engineers working in the chemical industry. Prior research on women’s career development, largely conducted by vocational psychologists, has revealed a number of important factors that affect women’s rates of participation and advancement in the workplace more generally, and particularly in fields traditionally dominated by men, such as STEM (Science, Technology, Engineering, Mathematics) occupations. For example, research has documented that female science faculty report less influence, fewer opportunities for leadership, slower advancement, and more social isolation than their male counterparts (2). Multiple negative factors within the workplace—which may be formal structures, climate-related features of the environment, or specific experiences (e.g., harassment)—have been found to hinder the success of women workers, and perhaps especially women scientists. Such factors limit opportunities, increase obstacles, and result in lowered success, satisfaction, and workplace longevity. Additional research on these factors is needed, as well as attention to how these features may interact with positive factors in the workplace known to enhance occupational success, such as organizational support and mentoring. To begin to address the knowledge gap regarding women working in industrial settings, our work in Project ENHANCE, carried out at the University of Maryland with support from the National Science Foundation, was aimed at investigating the experiences of STEM-trained women working in the chemical industry specifically. The first article (Part 1) (3) in this three-article series presents an overview of the questions that drove our investigation, outlines the methodology we used to conduct our multi-year study, and presents broad, overall results related to success, satisfaction, advancement, company support, and the home-work interface. This, the second article in the series, explores specific challenges for diverse women in the workplace, including organizational support and climate, mentoring, stressors and coping responses, and company benefits 146

available to and used by women working in industrial chemistry. The third article (Part 3) (4) in the series presents results specifically related to management perspectives, comparisons between managers and women employees, and leadership issues for women in industrial settings.

The Committed Company: Perceived Organizational Support One of the most extensively-studied and widely-cited influences on women’s career choice, retention, and success is the extent to which workplaces proactively support and encourage women employees. A number of different constructs compose a cluster of environmental “support” variables that use different terminologies (e.g., organizational support, workplace climate, social support) and methods of assessment; research also has explored a wide array of more specific sources or kinds of support (e.g., mentoring, sponsorship, supervisor feedback, co-worker attitudes, and the like). One articulation of this broad kind of workplace support that has been particularly robust in the literature is termed Perceived Organizational Support (POS) (5). Organizational support theory posits that the commitment of employees to their organization is influenced strongly by their perceptions of the organization’s commitment to them. Eisenberger and colleagues (5) hypothesized that because employees tend to personify their organizations—that is, they tend to view actions by agents of the organization as actions of the organization itself—employees develop global perceptions of the extent to which the organization values their contributions and cares about their well-being. Employees use these perceptions to judge the personified organization’s readiness to reward their work effort. Employees thus become more committed to organizations that are perceived to be committed to them. This theory has been supported empirically, with evidence that perceived organizational support (POS) is a unidimensional construct that is distinct from general job satisfaction (5, 6). Various recognition, rewards, and employee benefits have been found to be related to POS, including compensation (7), perceived usefulness of work-life benefits (8), and organization-level recognition and rewards (6). Perceived organizational support has been found to be distinct from supervisor support, coworker support, and work-group support (6, 9, 10); however, POS is positively correlated with support from supervisors, coworkers, and the work-group. Employee perceptions of top management’s general expressions of support for employees have been found to have a significant relationship with POS, as has formal positive feedback directed toward individual employees; furthermore, when asked which source they thought was most influential in shaping their perceptions of organizational support, respondents in one study indicated that their immediate supervisors were most important, while people within their workgroups also were important (9). Perceived organizational support has been related to outcomes favorable to both employees and their organizations. In multiple studies, POS has been found to be related positively to employee attendance and performance (6), as well as to employee affective and organizational commitment (11). Results 147

have been somewhat mixed regarding the existence of a relationship between POS and employee turnover (6, 12). However, job satisfaction was identified as a positive outcome of POS in an important meta-analysis of research on the construct (6). Perceived organizational support therefore is a critical construct to examine when considering the satisfaction and success of women scientists and engineers working in industrial settings, particularly given evidence that perceived organizational support may differ by gender (13). Increased understanding of the ways in which other workplace variables are linked to POS might allow for more effective interventions aimed at supporting the success of women in the STEM workplace broadly and industry specifically.

Mentoring: Helpful but Hard To Find? A specific form of organizational support that has received considerable attention in the career development literature is mentoring. Mentoring has been defined as an interpersonal process in which a more experienced colleague provides support and guidance to a less experienced colleague; according to this model, mentors’ support may be career-related and instrumental or emotionally-supportive and psychosocial in nature (14). Career-related functions involve helping mentees develop professional skills for career advancement, such as how to garner recognition or set long-term career goals. Career-enhancing mentoring activities also include coaching, assigning challenging work, enhancing visibility, or providing professional exposure and protection to the mentee. Psychosocial functions concern features of the relationship that provide emotional support or facilitate a mentee’s sense of competence, such as role modeling or advice-giving. Mentors’ provision of psychosocial support may also include acceptance and confirmation, counseling, and friendship. The literature on mentoring indicates that male mentors tend to provide more task-oriented support, whereas women tend to provide both task-oriented and personal/emotional support (15). Research also suggests that the quality of the mentoring relationship is more important than other features such as demographic matching of mentor and mentee (e.g., same race or gender); rather it is perceived similarities to one’s mentor in attitudes, values, and beliefs that are associated with highest levels of satisfaction for mentees (16). The importance of having a mentor has been associated with greater job satisfaction and career commitment, higher salaries, higher levels of perceived organizational support, more promotions, and higher levels of personal identity, self-esteem, and creativity (17). The difficulty that women often experience in finding mentors in their organizations has been identified as a significant barrier to women’s career advancement (17–19). A recent study of those receiving doctoral degrees from 11 top graduate programs in chemistry, for example, found that women reported fewer positive experiences with mentors than did men across their undergraduate, graduate, and postgraduate educational experiences (20). Catalyst studies documented more than a decade ago that women scientists in industry face organizational barriers to advancement that result from lack of women in more advanced positions who can serve as mentors, lack of female role models, and 148

unwillingness of men to mentor women (21). Moreover, even when mentoring appears to be occurring for women, there is evidence that the kind of mentoring being offered is supportive but not necessarily instrumental (what is often referred to in the corporate world as “sponsorship”)—that is, women may be receiving emotional support and help, but mentors may not be helping them to network, providing them with opportunities to develop skills, sponsoring them for awards and honors, or moving them into choice assignments (22). As it is the latter activities that actually lead to success, women may end up confused and blaming themselves when they feel they are receiving support but remain unable to progress. Finally, racial/ethnic and sexual minority women, as well as women with disabilities, often have the most difficulty in accessing mentors and obtaining the kind of mentoring that moves them forward (23–25).

In the Ether: Negative Workplace Climate Sonnert and Holton (26) classically proposed that gender disparities in science careers can be understood best by the structural mechanisms that serve as barriers toward women’s advancement, as opposed to inherent gender differences that were assumed by many. These barriers include gender discrimination, (e.g., being passed over for jobs and tenure or left out of social networks and scientific collaborations), gender socialization (e.g., poor and inaccurate self-assessments of abilities leading to lowered ambitions), and gender differences in professional and scientific behaviors (e.g., men are more self-promoting). This is consistent with an important finding in the literature, well-documented over time, that a negative workplace “climate”—generally conceptualized as overt and covert sexism, direct and environmental harassment, and “isms” embedded in organizational policies and practices (e.g., sexism, racism, heterosexism, ableism)—is an important barrier to women’s career development and professional outcomes in STEM fields (24, 25). Much has been written on the “chilly” climate (27) experienced by women in education and the workforce. In such environments, women often are sent subtle messages that they are not on equal footing with their male colleagues, while being told overtly that discrimination against women is nonexistent. Manifestations of a chilly climate include approaching women professionals with stereotyped expectations (e.g., accommodating, less intelligent, nurturing); holding contradictory judgments of comparable behavior for women and men (e.g., she is emotional, he is angry); focusing on women’s personalities and appearances as opposed to accomplishments and competencies; and devaluing women’s accomplishments even if they are the same or better than those of their male colleagues (e.g., her accomplishments are a result of external factors such as luck, his are a result of internal factors such as ability). Additionally, negative workplace climate may be reflected in exclusion of women from informal and formal social networks, and minimizing the importance of discussions about improving the workplace climate for women in science and engineering (27). The vocational psychology literature also acknowledges that seemingly neutral or “null” environments can inadvertently fail to support women, because they 149

ignore the societal advantage and disadvantage in career development that men and women, respectively, experience (28). More overtly negative workplace experiences such as sexual harassment, sexist conversations and jokes, racism, heterosexism, and ableism also exist, and are indicators of a hostile, rather than simply chilly, climate. A specific organizational climate may (and often does) include both hostile and chilly features. Perceptions of workplace climate generally have been associated with attitudes and behavior toward work and one’s company (29). Perceptions of climate related to gender equity and discrimination specifically have been associated with numerous outcomes. Gender discrimination is negatively associated with job satisfaction, affective commitment, and tenure for women; perceived discrimination has been found to be positively associated not only with undesirable job-related variables but also with reductions in physical and emotional health (30). A large study of the experiences of women engineers found that women who reported experiencing a negative workplace climate (e.g., belittling and condescending treatment, systematic undermining by supervisors and coworkers) were significantly less satisfied in their jobs and more likely to want to leave their organizations than those who did not; additionally, negative workplace climate was cited frequently among the women in the study who had elected to leave the field of engineering (31). Even very recent research reveals that women continue to be less associated than men with traits that scientists are expected to possess (32). Perhaps unsurprisingly, women, more than men, report gender inequity and organizational injustice, particularly around pay, respect, organizational practices regarding awards and advancement, and discrimination (33).

Sexual and Gender Harassment Whereas stereotyping, diminishing of accomplishments, and fewer supportive relationships may comprise a “chilly” workplace climate, sexual harassment is more specifically associated with a hostile organizational climate for women. Sexual harassment can be defined as the “sexualization of a work relationship, usually directed at women by men, and includes sexist comments (gender harassment), unwanted sexual attention, sexual coercion, and sexual assault” (2). Male-dominated fields, such as science and engineering occupations, are more likely to breed sexual harassment (2); in addition to a numerical majority of men in science and engineering, a hierarchy in which men are highly and visibly overrepresented at the top supports the proliferation of a sexist climate, where harassment is used to maintain the gendered power structure. Perhaps unsurprisingly, women who believe that their organization is tolerant of sexual harassment generally report experiencing more harassment (34). Organizational variables found to relate to lower reported experiences of unwanted sexual behaviors include organization concern for employee welfare, gender-specific aspects of organizational climate (e.g., positive attitude toward treatment of women), and a friendly attitude by management toward the home-work interface (35). 150

Sexual harassment has been associated with numerous negative occupational and psychological outcomes. Satisfaction with coworkers, supervisors, and work have been found to lessen, decreases in productivity have been observed, and reduction in commitment to and engagement in work have been documented. Furthermore, employees who experienced harassment reported more mental health difficulties, absenteeism, and increased desire for job turnover (36, 37). Gender harassment is a related experience documented in hostile male-dominated work environments that is characterized by hostility toward individuals who violate gender ideals; rather than inappropriate expressions of sexual advancement, these are verbal and nonverbal behaviors that convey generally insulting, hostile, and degrading attitudes about women. Gender harassment of professional women in traditionally male-dominated fields has been associated with a wide variety of negative outcomes, including reductions in job satisfaction, job performance, organizational commitment, satisfaction with professional relationships, psychological well-being, and satisfaction with health (38). Over time, the accumulation of sexual harassment experiences, subtle and/or overt, can have a devastating impact on women employees (39).

Workplace Climate and Diverse Women For women of color and sexual minority women, organizational policies and practices that comprise the workplace climate additionally may be experienced as racist and homophobic or heterosexist, and these may compound the negative effects of sexism or impose unique effects on job outcomes. For example, Catalyst research within the business sector found that African American women encountered negative racist stereotypes, doubts of their ability, and little support from their organizations (40). Additionally, African American women reported less inclusion in informal networks, and experienced difficult relationships with White women colleagues. Similarly, Latina women reported that their top barriers to advancement were the absence of mentors/sponsors, informal networks, and Latina role models; 38% additionally reported confronting stereotypes in their careers that made it difficult to advance. Asian American women perceived that lacking important professional relationships had hindered their career advancement (21, 40). Furthermore, differences between cultural and workplace values may impede success; for example, self-promotion is cited as an advancement tool, but may conflict with a cultural value of self-effacement held by some Asian American women. Finally, for sexual and gender minority (e.g., bisexual, lesbian, transgender) individuals, identity disclosure at work has been associated with more negative workplace climate experiences, including unfair treatment and stress (41). Similarly, racial and sexual minority women in science and engineering are believed to experience poorer job outcomes because their double or triple minority status results in more barriers and limited opportunities (24, 25). 151

Project ENHANCE: Studying Women in the Chemical Industry Little direct information exists on the experiences of STEM-trained women working in industrial settings. However, the existing vocational literature suggests that perceived organizational support, particularly through the contribution of mentoring, may play an important role in their job-related behaviors and outcomes. A goal of Project ENHANCE was to examine perceived organizational support in a sample of women scientists and engineers currently working in the chemical industry. We examined variables that have been studied in prior research, including supervisor support, coworker support, perceived rewards and recognition, and employee benefits. In addition, several measures of mentoring, an important variable in the literature on workplace support, also were included. The study sought to explore the amount and types of support perceived by this sample of women. Additionally, the study aimed to discover workplace experiences that predict POS for this sample of women and to assess their relative contributions to POS. The career development literature further suggests that perceived gender discrimination, an aspect of workplace climate, had a significant impact on women’s overall attitudes toward their employment (4). Thus, Project ENHANCE also explored how workplace climate relates to employment outcomes for these women generally (e.g., success, advancement experiences), as well as for diverse subgroups of women specifically (e.g., racial/ethnic and sexual minority women). Additionally, although previous studies have examined workplace climate as a predictor of other variables such as job satisfaction, we sought to examine which variables would lead to the prediction of perceptions of workplace climate. Finally, we were interested in assessing coping strategies used by women who have experienced a negative workplace climate, including those reporting experiences of sexual harassment.

Methods of the Study Summarized As described in the first article in this series (3), the Project ENHANCE multiyear study was carried out at the University of Maryland by a diverse team of faculty and (then) advanced doctoral student researchers, as well as consultants from industry and academe. The project consisted of four main components and a follow-up study: Quantitative, anonymous, web-based surveys of 1,725 women chemists and 264 male and female managers; voluntary qualitative interviews with 26 women and 6 managers (selected from among volunteers as representative of the respondents to our surveys); and a follow-up interview study of mentoring conducted with nine male managers (42). Respondents were from 25 Fortune 1000 U.S.-based chemical companies, and were recruited in collaboration with company management, our industry consultant, our advisory board of top leaders in industrial chemistry, and professional societies such as the Women Chemists Committee of the American Chemical Society (ACS). This, the second article in the three-article series, uses data from the women’s portion of the study, and focuses on the experiences of diverse women regarding organizational support 152

and climate, mentoring, stressors and coping responses, and availability and use of company benefits. Descriptions of all of the measures used in the study are presented in the first article in this series (3). As described in the first article in this series (3), we conducted hundreds of quantitative analyses common in psychology and appropriate to the variables, sample sizes, and research questions of interest to us, including: a) assessing the psychometric properties of our instruments (e.g., internal consistency reliability, factor structure); b) obtaining correlations among variables to explore significant relationships: c) conducting analyses of variance (ANOVA), t-tests, and chi-square tests to compare similarities and differences among groups and sub-groups across variables; d) running regression analyses to establish the significant prediction of variables by other variables; e) completing all follow-up statistical tests demanded for interpretability in the various approaches; and f) making statistical adjustments due to unequal sample sizes, missing data, and the like. Due to large samples and numbers of analyses, we used a very stringent standard for determining significance in our quantitative findings (p