Methods and Instruments in the Study of Meaning-Making 3031219945, 9783031219948

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Methods and Instruments in the Study of Meaning-Making
 3031219945, 9783031219948

Table of contents :
This Volume
About the Editors
Part I: Framework
Chapter 1: The Analysis of Meaning
1.1 The Meaning of Meaning
1.1.1 The Triadicity of Meaning
1.1.2 The Reversal Between Meaning and Sense-Making
1.1.3 The Pre-Reflexivity of Meaning
1.1.4 Significance In Absentia (SIA)
1.1.5 Performativity of Meaning
1.1.6 Performativity of the Meaning and Stability of the Social Group
1.1.7 Individual and Social Sense-Making
1.1.8 Synthesis
1.2 The Investigation of Meaning: Foci and Levels of Analysis
1.2.1 Foci of Analysis Dynamics Structure Content
1.2.2 Levels of Analysis Implications Hierarchy of Meanings
1.2.3 Conclusive Remarks
1.3 Analytic Approaches
1.4 The Epistemic Functions of the Analysis
1.4.1 Meaning as Explanandum, Meaning as Explanans
1.4.2 Meaning and Social Environment
1.5 Conclusion
Part II: Strategies of Analysis
Chapter 2: The Challenges of Cultural Segmentation: New Approaches from Computational Social Science
2.1 Introduction
2.2 Model-Based Recursive Partitioning
2.2.1 Technical Details
2.3 Relational Class Analysis and Correlation Class Analysis
2.4 Implicit Association Test and Concept Association Test
2.4.1 Concept Association Task
2.5 Conclusions
Chapter 3: The Dimensionality of Sense-Making
3.1 The Meaning of Dimensionality
3.2 The Dimensionality of Meaning
3.3 Dimensionality and Language
3.3.1 Meaning Between Words
3.3.2 Development of Language
3.4 Dimensionality as a Methodological Framework
3.4.1 Homogenization of Classification Functions Measurement (HOCFUN): A Method for Measuring the Salience of Emotional Arousa... Theoretical Framework Operational Premise Method Results and Discussion
3.4.2 The Discursive Dynamic of Sense-making Theoretical Framework Operational Premise Method Results and Discussions
3.4.3 Affective Saturation Index: A Lexical Measure of Affect Theoretical Framework Operational Premise Method Results and Discussions
3.4.4 The Phase Space of Meaning Model of Psychopathology: A Computer Simulation Modeling Study Theoretical Framework Operational Premise Method Results and Discussion
3.5 Conclusion
Part III: Textual Meanings
Chapter 4: The Themes of Texts: Automatic Co-occurrence Analysis for Semantic Mapping (ACASM)
4.1 Introduction
4.2 Theoretical Framework
4.3 ACASM Procedure
4.3.1 Stage 1. Construction of the Digital Representation of the Corpus Step 1: Text Segmentation Step 2: Lemmatization Step 3. Selection of the Lemmas in Analysis Step 4: Construction of the Matrix
4.3.2 Stage 2. Multidimensional Analysis Step 5. Lexical Correspondence Analysis. The Map of the Semantic Structure Step 6: Cluster Analysis. The Identification of Themes
4.4 Reliability and Validity of ACASM
4.5 ACASM Applications
4.6 Conclusions
Chapter 5: The Analysis of Sensemaking Dynamics in Communicative Contexts: The Discourse Flow Analysis (DFA)
5.1 Introduction
5.2 Discourse Flow Analysis: Theoretical Background
5.2.1 Meaning and Sensemaking
5.2.2 Discursive Dynamics of Sensemaking
5.3 Discourse Flow Analysis: Procedure of Analysis
5.3.1 Content Analysis
5.3.2 Sequential Analysis
5.3.3 Structural, Functional, and Dynamic Analysis
5.4 Discourse Flow Analysis: Empirical Review
5.5 Conclusions and Future Directions
Part IV: Domain Meanings
Chapter 6: A Tool to Analyze the Cultural Milieu: View of Context (VOC)
6.1 Introduction
6.2 Framework. The Affective Grounds of Sensemaking
6.2.1 Symbolic Universes
6.2.2 Lines of Semiotic Force
6.3 The Questionnaire
6.3.1 Item Construction
6.3.2 Data Analysis
6.3.3 VOC Construct Validity. A Study
6.3.4 The Idiographic Nature of the Instrument
6.4 VOC Applications
6.4.1 The Map of the Cultural Milieus of European Societies
6.4.2 The Influence of Symbolic Universes Self-Representation and Attitudes Voting Behavior Vaccination
6.4.3 Stability and Change of Symbolic Universes Over Time
6.5 Conclusion
Chapter 7: The Inner Side of Experience: The Meaning Behind Customer Satisfaction
7.1 Introduction
7.2 The Prosumership Service Quality Model (PROSERV)
7.2.2 VALUE
7.2.3 The PROSERV Questionnaire (PROSERV-Q)
7.3 Conclusions
Chapter 8: Images of the Patient-Physician Relationship Questionnaire (IPPRQ): An Instrument for Analyzing the Way Patients Ma...
8.1 Introduction
8.2 Scenario
8.3 Framework
8.4 The Images of the Patient-Physician Relationship Questionnaire (IPPRQ)
8.4.1 The Detection of the Images of the PPR
8.5 Initial Evidence in Support of the Validity of the IPPRQ
8.5.1 Images of the PPR and Compliance
8.5.2 Stability of the Representations Detected Through the IPPRQ Method Results Discussion
8.6 Conclusion
Appendix. Images of the Patient-Physician Relationship Questionnaire (IPPRQ)

Citation preview

Culture in Policy Making: The Symbolic Universes of Social Action

Sergio Salvatore Giuseppe Alessandro Veltri Terri Mannarini   Editors

Methods and Instruments in the Study of Meaning-Making

Culture in Policy Making: The Symbolic Universes of Social Action Series Editors Sergio Salvatore, Department of Dynamic Psychology, La Sapienza Università di Roma, Rome, Italy Terri Mannarini, Department of History, Society and Human Studies, Università del Salento, Lecce, Lecce, Italy Jaan Valsiner, Psychologie, Aalborg Universitet, Aalborg, Denmark Giuseppe A. Veltri, Department of Sociology, Università di Trento, Trento, Trento, Italy

The book series develops and consolidates the innovative approach to policy-making and politics based on the recognition of the central role played by cultural dynamics, intended as on-going processes of sense making channelled by symbolic resources the cultural environment makes available and through which people make sense to the experience, therefore feel, think, act. It pursues both a theoretical and practical purpose: the development of the conceptual approach to policy and politics based on the view of human being as homo semioticus, as a subject engaged constantly with the need to make meaningful ordinary daily experiences, as well as participation in society.

Sergio Salvatore • Giuseppe Alessandro Veltri • Terri Mannarini Editors

Methods and Instruments in the Study of Meaning-Making

Editors Sergio Salvatore University of Salento Lecce, Italy

Giuseppe Alessandro Veltri Università di Trento Trento, Italy

Terri Mannarini Università del Salento Lecce, Italy

This work was supported by European Commission –H2020 framework ISSN 2523-7306 ISSN 2523-7314 (electronic) Culture in Policy Making: The Symbolic Universes of Social Action ISBN 978-3-031-21994-8 ISBN 978-3-031-21995-5 (eBook) © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland


This book is the fourth volume—all published in the Culture in Policy Making series—resulting from the Re.Cri.Re. research program (Between the representation of the crisis and the crisis of the representation), the EU H2000 project that between 2015 and 2018 analyzed the cultural dynamics of Europe and their impacts on institutions, societies, and people. The first and second volumes (Mannarini et al., 2020; Salvatore et al., 2019) presented the theoretical and methodological framework grounding the analysis—the Semiotic Cultural Psychology Theory—as well as the main results—namely, the longitudinal, multimethod, and multifocal picture of the cultural milieus of the European societies, together with their psycho-social and institutional impact. The third volume (Cremaschi et al., 2021) focused on the implications for policy making that can be drawn from the understanding of the cultural milieus. From that standpoint, it discusses ideas about how to design culturally-sensitive policies, aimed at promoting the semiotic resources required to foster social and institutional development. This volume represents the conclusive act of that journey. It collects a set of approaches and instruments of analysis of meanings and sensemaking, developed within the Re.Cri.Re. framework and designed to facilitate the understanding of the semiotic resources and dynamics substantiating cultural milieus. Re.Cri.Re. cultural analysis had to address a highly challenging methodological issue—how to integrate the in-depth, situated understanding of the cultural dynamics with its extensive, systematic detection. Generally, analyses sacrifice one aspect to the other. Thus, one finds, on the one hand, “wide angle studies” that provide a global picture of the cultural landscape of entire social groups, also enabling them to be compared, yet this is obtained at the cost of giving up the exploration of the specificity of the local contexts of meaning. On the other hand, one finds “zoom studies” focused on specific, contingent dynamics of sensemaking, aimed at detecting patterns of meanings embedded within situated social practices, yet uninterested in extensive, system-level pictures of the cultural dynamics such social practices help to foster.




This fracture weakens the capacity of culturally-oriented approaches to build empirically based, general interpretative frameworks of social phenomena and to draw from them systemic strategies of interventions to tackle global challenges (e.g., the migration crisis, climate change, Euroscepticism, distrust in democratic institutions). A symptom of this limitation is the fact that the scientific knowledge that policies take into consideration is the kind supplied by disciplines that are able to provide extensive, quantitative detection of socio-cultural and political phenomena—e.g., economics, demography (however, for an exception, see Appadurai, 2004). After all, the Re.Cri.Re. project was the only one based on a socio-cultural framework, among those (around 20) funded in the first round of the H2020 program. The methods and instruments brought together in the volume reflect the effort to overcome the fracture between systemic and subjective dimensions of meaning. They are designed to provide extensive analyses of the sensemaking dynamics and/or patterns of meanings that characterize entire social groups—analyses that adopt standards of reliability and validity similar to those of econometric and sociometric approaches and instruments. At the same time, they focus on the local, subjective dimension of meaning, namely on the understanding of how meaning is construed and experienced within the situated practices it mediates. Thus, thanks to these methods and instruments, and more in general to the theoretical-methodological framework they are based on, the cultural approach to society pursues the goal of providing analysts, professionals, and policy-makers with a view of socio-institutional phenomena that brings together the global detection of the forest and the analytic view of the trees.

This Volume The volume is divided into four parts. The first part consists of an introductive chapter that provides the theoretical and methodological framework of the methods and instruments presented in the following chapters. It moves from the pragmatist, dynamic, intersubjective definition of meaning adopted and elaborated further by the Semiotic Cultural Psychology Theory to a discussion of what can be analyzed when one analyzes meaning and for what purpose. The second part focuses on the methodological approaches to the analysis of meaning. It comprises two chapters. Chapter 2 presents some strategies of analysis designed to take the cultural variability of the investigated social group into account. The specificity of these strategies lies in the fact that they enable a bottom-up, datadriven segmentation of the sample, by reason of how variables combine with each other in different ways in different subsets of individuals. Though this strategy is not specific of the analysis of meaning, it enables the cultural segmentation of the social group, namely a differentiation of the sample in terms of how culturally relevant responses combine with each other across respondents. Chapter 3 presents the notion



of the dimensionality of meaning and presents several strategies of analysis aimed at modeling sensemaking in terms of its dimensionality. At the core of the dimensional view of meaning rests the idea that sensemaking is a dynamics based on the ongoing process of selection of the qualities of experience that are worth mapping. Each of these qualities is a component of the meaning brought to the fore. Accordingly, sensemaking can be analyzed not only in its content, but also in terms of the number of dimensions taken into account (i.e., its degree of complexity), and its variation over time. The third part of the volume is focused on the analysis of the meaning conveyed by written texts. Chapter 4 outlines ACASM (Automated Co-occurrence Analysis of Semantic Mapping)—an automated method of textual analysis designed to detect the thematic contents conveyed by texts and the semantic structure underpinning them. ACASM was developed more than a decade ago in the context of the analysis of the psychotherapy process. Yet, in recent years it has been used to study extensively the content and structure of the cultural representations of social objects (Mannarini et al., 2020). Chapter 5 presents DFA (Discourse Flow Analysis). This method, too, was developed in the past decade, in the psychotherapy process field. We have included it in the volume because of its consistency with the dynamic conception of meaning that it shares with the theoretical framework of the entire book. Indeed, the DFA focuses on how meaning emerges from how signs combine with each other across time. The DFA indexes provide a way to measure and model the dynamics and the structure of such interaction. The fourth part of the volume is devoted to presenting instruments designed to map the patterns of meanings through which sensemakers interpret experience. Chapter 6 outlines the VOC (View of Context) questionnaire. VOC is designed to detect the affect-laden worldviews that are active within the cultural milieu—the symbolic universes—and the underpinning semiotic structure—the lines of semiotic force. While the VOC is focused on the generalized worldviews substantiating the whole sense of being in relation with the world, the instruments proposed in the following two chapters aim at analyzing the meanings related to specific objects/ domains of social practice. The PROSERV (Prosumership Service Quality Model) questionnaire outlined in Chap. 7 is designed to detect how people interpret the experience of being clients of a service. Like other similar instruments, it adopts a multidimensional approach, based on breaking down the client’s evaluation of the service into components, each of which viewed as a dimension of meaning. What distinguishes PROSERV from the other instruments of the field is the inclusion in the model of analysis of a dimension of meaning concerning the sense of service as a co-constructive relationship with the provider—a dimension which comes from the Re.Cri.Re. dynamic, intersubjective view of sensemaking. Finally, Chap. 8 presents the IPPRQ (Images of the Patient-Physician Role), an instrument aimed at detecting the affect-laden modes in terms of which sensemakers interpret the domain of experience consisting in their being patients in relation with a physician. The IPPRQ adopts the same VOC bottom-up approach—it does not measure meaning by reason of exogenous, pre-fixed dimensions but detects the patterns of meanings based on how responses combine with each other across respondents.



Our desire and our purpose is that this volume might contribute to making the analyses of meaning systematic, extensive, and reliable, without this weakening their capacity to understand the subjective side, namely to comprehend how experience is interpreted from the point of view of the sensemaker that construes it. The reader will say if the volume has lived up to these intentions. Good reading. Lecce and Trento, July 2022 Università del Salento, Lecce, Italy University of Salento, Lecce, Italy Università di Trento, Trento, Italy

Terri Mannarini Sergio Salvatore Giuseppe Alessandro Veltri

References Appadurai, A. (2004). The capacity to aspire: Culture and the terms of recognition. In V. Rao, & M. Walton (Eds.), Culture and public action (pp. 59–84). Stanford: Stanford University Press Cremaschi, M., Fioretti, C., Mannarini, M., & Salvatore, S. (2021). Culture and Policy-making. Pluralism, Performativity and Semiotic Capital. Cham (Switzerland): Springer Mannarini, T., Veltri, A. G., Salvatore, S. (Eds). (2020). Media and Social Representations of Otherness. Psycho-Social-Cultural Implications. Cham (Switzerland): Springer Salvatore, S., Fini, V., Mannarini, T., Valsiner, J., & Veltri, G.A. (Eds.) (2019). Symbolic Universes in Time of (Post)Crisis. The Future of European Societies. Cham (CH): Springer


Part I 1

The Analysis of Meaning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sergio Salvatore and Raffaele De Luca Picione

Part II 2




Strategies of Analysis

The Challenges of Cultural Segmentation: New Approaches from Computational Social Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Giuseppe A. Veltri The Dimensionality of Sense-Making . . . . . . . . . . . . . . . . . . . . . . . . Johann R. Kleinbub and Sergio Salvatore

Part III 4


31 53

Textual Meanings

The Themes of Texts: Automatic Co-occurrence Analysis for Semantic Mapping (ACASM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alessandro Gennaro and Sergio Salvatore


The Analysis of Sensemaking Dynamics in Communicative Contexts: The Discourse Flow Analysis (DFA) . . . . . . . . . . . . . . . . . . . . . . . . . 107 Gloria Lagetto and Omar Carlo Gioacchino Gelo

Part IV

Domain Meanings


A Tool to Analyze the Cultural Milieu: View of Context (VOC) . . . . 127 Skaiste Kerušauskaitė, Matteo Reho, and Terri Mannarini


The Inner Side of Experience: The Meaning Behind Customer Satisfaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Paola Pasca and Enrico Ciavolino





Images of the Patient–Physician Relationship Questionnaire (IPPRQ): An Instrument for Analyzing the Way Patients Make Sense of the Relationship with the Physician . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Claudia Venuleo, Tiziana Marinaci, Giulia Savarese, and Annalisa Venezia

Appendix. Images of the Patient–Physician Relationship Questionnaire (IPPRQ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

About the Editors

Sergio Salvatore is Professor of Dynamic Psychology at the Department of Human and Social Sciences, University of Salento. His scientific interests regard the psychodynamic and semiotic theorization of psychological and social phenomena and the methodology of analysis of socio-cultural and mental processes as field dynamics. He also takes an interest in the theory and the analysis of psychological intervention in socio-political, community, scholastic, organizational as well as clinical fields. On these issues, he has designed and managed various scientific projects and published more than 300 works among volumes, chapters, and articles. Co-editor of the book series: Culture in Policy Making: The Symbolic Universes of Social Action (Springer) and Yearbook of Idiographic Science (IAP). Associate editor of journal Integrative Psychological and Behavioral Science. Editor-inChief of Rivista di Psicologia Clinica (The Italian Journal of Clinical Psychology). Email: [email protected]. Terri Mannarini is Professor of Social Psychology at the University of Salento, Lecce, Italy, and Editor-in-Chief of the international journal Community Psychology in Global Perspective. Her research interests cover political, social, and community psychology and focus specifically on community participation and development processes, collective action, acculturation processes, and gender issues. Email: [email protected] Giuseppe Alessandro Veltri holds an MSc in Social Research Methods (Statistics) from the Methodology Institute of the London School of Economics (LSE) and a PhD in Social Psychology from the LSE. He is a Full Professor of Computational Social Science and Cognitive Sociology at the Department of Sociology and Social Research of the University of Trento. Email: [email protected]


Part I


Chapter 1

The Analysis of Meaning Sergio Salvatore and Raffaele De Luca Picione

The meaning of meaning is anything but obvious. Human beings live within meaning, and for that very reason are blind to what meaning is. Thus, any discourse about the analysis of meaning needs to be framed in a preliminary discussion on what one means by meaning. To map something, one has to know what that something is. In this chapter we provide a way to answer this basic question. More specifically, we focus on two main issues. First, a general model of meaning will be proposed, based on the Semiotic Cultural Psychology Theory (SCPT; Cremaschi et al., 2021; Salvatore, 2016, 2018, 2019; Salvatore, Valsiner, & Veltri, 2019; Salvatore, De Luca Picione, et al., 2021; Salvatore, Palmieri, et al., 2021; Valsiner, 2007, 2014). Second, a map of different aspects involved in the analysis of meaning are discussed—foci and levels of analysis, logical architecture, approaches and the epistemic function of knowledge concerning meaning.

1.1 1.1.1

The Meaning of Meaning The Triadicity of Meaning

According to the everyday view, meaning is contained in and conveyed by signs: images, sounds, and symbols are experienced as having meaning, as if the latter were S. Salvatore (✉) University of Salento, Lecce, Italy e-mail: [email protected] R. De Luca Picione “Giustino Fortunato” University Benevento, Benevento, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. Salvatore et al. (eds.), Methods and Instruments in the Study of Meaning-Making, Culture in Policy Making: The Symbolic Universes of Social Action,



S. Salvatore and R. De Luca Picione

its inherent quality. Actually, this is not just a naïve view—indeed, it is consistent with the de Saussure (1916/1977) structuralist theory, which models the sign as the association between a signifier and a signified, the latter considered inherent to the relation (in the case of indexical and iconic signs) or arbitrary, based on a conventional code (in the case of symbolic signs). However, this view raises several problems (Salvatore, 2016), the main one being that it leads to meaning being reified and considered a self-contained entity that is independent and upstream of the practices of sense-making. This is made clear by the fact that de Saussure distinguished between langue and parole and considered the former—i.e., the abstract rules of a system of signs—the elective focus of interest. Here we want to highlight a methodological problem associated with the structuralist conception of meaning—the fact that, once the meaning is separated from the concrete arenas where it is used, it becomes hard to detect it empirically. If the meaning lives outside social life, in a Plato-like world, how can we reach it and map it? This problem is overcome—or rather, it disappears—once one adopts the pragmatist view of meaning, and, more particularly Peirce’s triadic theory of the sign. Briefly, according to the pragmatist view, the meaning is the effect of the sign, namely the way the sign contributes to the regulation of the action in the context in which the latter is deployed. Consider a person who enters a coffee bar states: “a coffee, please,” and receives a cup of hot dark liquid. The meaning of the statement uttered consists of its capacity to regulate the exchange with the barman in the way that ends in the delivery of the cup. Peirce provides a model of the semiotic dynamics making up this capacity (Peirce, 1902/1932; for a discussion, see Salvatore, 2016). According to the American philosopher, the meaning of a sign (say, sign A) is not “within” the sign; instead, sign A acquires its meaning by means and in the terms of the following sign (say, sign B), which sign A triggers in the sensemaker’s mind as its interpretation. More specifically, sign B’s interpretation of sign A consists of the definition of the quality or property of the object—what Peirce defines “ground”—that sign A stands for. Indeed, sign A could represent infinite qualities of the object—the meaning emerges precisely because by means of sign B the sensemaker selects a given quality, among the infinite set of possible ones. For instance, take a person looking at a photo (sign A) of a landscape (object) and thinking: “what a nice place” (sign B). In this case, sign B defines the beauty of the place as the object’s ground, which sign A stands for. The Peircean triadic definition of the sign has some important implications that are worth briefly highlighting. First, the Peircean semiotic theory implies a functional view of the sign—a sign is any element of the reality that works as such, namely that interprets the previous sign—doing so by means of how it is in turn interpreted by its following sign. Thus, a sign has no inherent ontological quality that distinguishes it from what is not a sign. Rather, everything may (or may not) take over the function of standing for something else and triggering a further sign. A relevant corollary of this functional


The Analysis of Meaning


definition is that emotions, affects, and more in general body states can work as signs, insofar as they interpret the semiotic chain backward and continue it by triggering further signs. This conclusion is consistent with and enforces the embodied conception of the mind, developed by contemporary psychology (Salvatore, 2018; Salvatore et al., 2022). Second, Peircean theory is a pragmatic definition of meaning. Indeed, the fact that sign B, in interpreting sign A, is triggered by the latter means that the meaning of sign A consists of its effect, namely its capacity to trigger a certain following sign as its interpretation. The meaning is the sign that follows, as one of the present authors concluded (Salvatore, 2016, 2019). Third, this theory attributes a constitutive role to the subject. Indeed, sign B is the means by which the sensemaker defines the grounds that make sign A meaningful for him/her. Thus, Peircean semiotics overcomes the langue-parole hiatus—meaning is inherently a matter of how signs are used by someone. Fourth, the Peircean theory outlines a view of sense-making as an endless chain of signs—an infinite semiotic flow. Indeed, it must be taken into account that, once sign B interprets the relation between sign A and its object, it needs to be interpreted itself—therefore, it triggers a further sign (say sign F) defined by the sensemaker according to in which quality sign B stands for sign A; and so on, in an endless backward/forward process where any sign is the interpretation of the previous and the trigger of the following one. In so doing, any sign reproduces the meaning at a given instant, in a way that sometimes stabilizes it or, in some cases, leads to something new. One could say that meaning is to meaning making what instantaneous speed is to movement.


The Reversal Between Meaning and Sense-Making

The Peircean semiotic theory leads to a reversal of the relation between meaning and sense-making—it is the former that emerges from the latter, rather than the opposite. To interpret is not to mobilize pre-existing meanings; rather, the meaning emerges from the flow of signs that make up sense-making. The emergence of the meaning from the semiotic flow is modeled by Peirce as the maintenance of a relation of correspondence. Namely, a sign is something, A, which brings something, B, its interpretant sign determined or created by it, into the same sort of correspondence with something, C, its object, as that in which itself stands to C. (Peirce, 1902/1976, vol. 4, pp. 20–21)

As stated in the previous section, the sign does not stand for its object in all its aspects and qualities; instead, the sign establishes a specific relation with its object, and it is this relation that is reproduced by the following sign. More specifically, sign B is the interpretation of sign A simply because it maintains a relation with the object that is equivalent to that maintained by sign A. In other words, the relation between


S. Salvatore and R. De Luca Picione

sign A and its object is equivalent to the relation between sign B and the object, to the relation between sign F and the object and so forth. In the final analysis, this means that the sign does not “grasp” the piece of the reality it stands for; signs relate only with each other, not with the world they refer to. They are able to stand for the world because the relation they establish with each other is assumed (by the sensemaker) to keep the relation with the realty invariant. This leads to a reversal between sense-making and reality. Sense-making is not motivated by the characteristics of the reality; rather, it is the meaning—or better, the chain of signs comprising the sense-making—that allows the object to be abductively construed in the mind as the condition of the chain’s interpretability. In other words, the “something” referred to by the sign comes to life in the sensemaker’s mind as the premises thanks to which the sequence of signs A, B, F. . . can be experienced as meaningful, namely as an association that keeps the correspondence with the object unchanged over time. In brief, object X emerges as if it were the response to the question: what is the X according to which signs A, B, F. . . are different, yet correspond to the same relation with X? The inference implied in this response is abductive because it consists of the identification of the possible cause (i.e., the object) that explains the observed effects (i.e., the sequence of signs) (Peirce, 1902/1932, CP 5.189). Incidentally, this leads to recognize the inherent temporality of meaning: experience of the reality emerges from the sequential combination of signs (for a similar view focused on the constitution of the value of goods by the exchange, see Appadurai, 2013).


The Pre-Reflexivity of Meaning

The reversion between meaning and sense-making implies a pre-reflective, antimentalist view of meaning. Indeed, if the meaning emerges from the combination of signs, then it cannot guide the choice of the signs to combine. Therefore, one must conclude that it is not the sensemaker’s intention/plan to signify that selects the subsequent sign; rather, the very intention/plan must be considered a post-hoc backward interpretation made possible by the meaning that emerged—namely it must be considered the by-product of the sense-making, rather than its causal driver. But then, how is the following sign selected? The answer is: as the product of a habit. The combination of signs is a matter of procedural memory that makes the selection of the following sign a function of the frequency of the instances of that association in the past: the more the sensemaker has mobilized the sign q after the sign p, the more it will tend to make q follow p. The frequency of the association between signs reflects the format and scope of the social action within which signs are mobilized for the sake of regulating it. Thus, the meaning is inherently social: it is an event (an environmental variation, Eco, 1975) activated to regulate the social action (Engel et al., 2015). In the final analysis, a sign and a relational pattern are the same process viewed from two different perspectives (and related languages). The sensemaker participates in the action and


The Analysis of Meaning


thereby learns the frequency of association between a given combination of signs and the global evolution of the action itself—i.e., the probability that a certain sequence of signs is associated with a certain variation in the course of action. Meaning consists of this probability. Language acquisition is the paradigmatic example of this pre-reflexive learning. Infants do not learn the meaning of words as if it consisted of conceptual, symbolic content. Instead, they learn to use the (proto)words to regulate the exchange with their caregivers and their physical environment—e.g., they learn the frequency of association between the combination of certain sounds they produce and the caregiver’s response (e.g., Borghi et al., 2017). It is only when language competence is consolidated enough that it is used reflexively to interpret the already acquired language habit (which, however, remains the grounds of the reflective interpretation).


Significance In Absentia (SIA)

These considerations raise the question of how frequency distribution can explain the great variability in the use of signs—we use any particular sign (words, gestures, sounds) in very many ways, in combination with an infinite set of other signs. The response to this question is based on the recognition of the fact that any sign is characterized by a plurality of frequency distributions, each of them related to the probability of association within a given social setting. Accordingly, sign m has the highest probability of triggering sign n in the context of social setting A, while sign o in the context of social practice B—for example, saying “how are you?” is expected to trigger quite different following signs if it happens in a medical room or when one meets a friend after a long time. This is due to the fact that the pattern of signs that usually follows “how are you” is quite different in these two different social settings. A relevant implication of the multi-dimensionality of frequency distribution is that the sign’s capacity to trigger the following sign depends on the fact that one distribution is active and the others are made inactive. Indeed, only when a specific frequency distribution is selected, can the link between the sign and the following sign be established. One of the present authors (Salvatore, 2016) has proposed to define the active frequency distribution significance in absentia (SIA). Thus, SIA is the scenario that is activated as the background, against which the sign selects the following sign and, in doing so, acquires meaningfulness. In the final analysis, SIA can be viewed as a micro-analytic model of the Peircean notion of ground—it defines the main quality the sequence of signs concerns, namely the relation of correspondence that is maintained through the chain of signs. A relevant aspect of the concept of SIA is that it highlights the twofold dynamics of sense-making. On the one hand, thanks to the following sign, the previous sign is interpreted. On the other hand, in order to make the following sign occur, an SIA has to be active. Therefore, the following sign does not only provide a local


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interpretation of the previous sign, but it also reproduces the SIA by reason of which it was selected. In other words, it triggers the sensemaker to foreground a semiotic scenario—i.e., to activate the memory of a social setting—as the global condition of interpretability of the whole semiotic chain (global because it concerns the whole chain of sign). This twofold dynamics of sense-making—local/global—is evident when it fails, namely when the local interpretation compels the global interpretation to vary considerably. This is the case, for instance, of humorism or jokes, when the last utterance/act of a sequence brings about an unexpected, profound change of the active semiotic scenario (i.e., of the SIA) grounding the sensemaker’s interpretation. For instance, take the person who replies “it’s time to buy a watch” to the friend who asked the time. In this case the joke consists of the fact that by producing such a following sign, she/he compels the person asking to reorganize the SIA—from a scenario of | seeking/being given information| to the scenario of, as it were, |relying on others/relying on oneself|.


Performativity of Meaning

Social practices occur within meaningful frames that serve as an implicit system of assumptions that are taken for granted (e.g., Berger & Luckman, 1966/1967, Bion, 1962; Douglas, 1986; Rommetveit, 1992; Schütz, 1945; Weick, 1995). This system of assumptions reduces the potentially infinite variability of agents’ action, thus carrying out the fundamental function of coordinating acts and their effects. It is worth noting that this coordination is far from being a sort of agreement between actors. Coordination means that actors can foresee the other’s action, not that they share it. This means that the reduction of the set of possibilities provided by the system of assumptions does not obliterate the freedom of the social actor; rather, it is the condition itself for exercising this freedom. In semiotics terms, there is a bordering process (De Luca Picione, 2021a, 2021b) that circumscribes the field of interaction by providing some normative representation of social interaction. Accordingly, people are able to interact in meaningful ways; and their actions can receive social feedback within a broad range of predictability, with the breadth depending on the specific circumstances. Normativity works as an operation of semiotic scaffolding (De Luca Picione, 2021c) that supports, orients, and channels certain trajectories (and not others) of social actions. Yet, we do not consider this process in terms of rigid prescriptions or formal obligations. The violation of canonicity is possible, generating in many cases an effort to restore canonicity and normativity at a further level. In so doing the violation usually confirms the norms and values. It should be added that coordination is not a matter of the ability to understand the intention of the interlocutor. Indeed, actors need not share the same understanding of what they think about their action. What is important is that the system of assumptions constrains the individual’s potentially infinite possibility of action in a way that


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makes each actor’s act consistent and foreseeable by other actors. Most social games are made possible precisely by means of this process. For instance, a football player runs after the ball that is in the opponent’s possession and tries to intercept it, but if the two players don’t share the same rules of play any match is impossible. The foreseeability that soccer players will try to put the ball into the opposing goal limits the set of possibilities on the field, informs about a certain normativity and rules, and coordinates the social interaction (both in terms of cooperating with team mates and of opposing the other team). A certain degree of freedom and variability of choices, actions, and behaviors are fully allowed, while the referee can sanction violations of canonicity and sets conditions of restarting after an interruption. What is worth highlighting here is the general transparency of the system of constraints in social coordination. This means that normativity is not always manifestly or clearly stated. Rather, it generally works in conditions of transparency for the actors, as a sort of backgrounding, of “dazzling” alternatives, which, as underlined by Harmon (2020, see Chap. 2) makes a huge set of potential orientations unthinkable. The phenomenologist and sociologist Alfred Schütz speaks about a condition of “epochè of common sense.” This notion indicates the suspension of judgment, of the verification and of critical thinking during daily activities and normal social routines (Schütz, 1945). The social frame—becoming transparent and invisible—allows the coordination and the development of social interactions. The world does not require to be discussed and verified each time—before, during and after an action—inasmuch as it is assumed to be stable, foreseeable, and shareable with other agents. This last assumption has a major implication: social interactions, negotiations between people (and conflicts as well) work together to reproduce the world and its assumptions. The taken-for-granted nature of the system of assumptions—namely, the transparent frame that makes experience possible—emerges and is reproduced over time through the very fact that the action it grounds is enacted (see Salvatore et al., 2006/ 2009). This is what the performative and recursive nature of sense-making consists of: any social practice enacts the social meaning it is embedded in. For example, in vaccination hesitancy (as well as in refusal), we can see a choice framed and motivated by a worldview connoting the social worlds (e.g., distrust in institutions, people, future) negatively and distrustfully; yet, at the same time this worldview is enacted, reproduced, and confirmed through the social and discursive practices it triggers (Rochira et al., 2019).


Performativity of the Meaning and Stability of the Social Group

The performativity of meaning enables us to recognize the strong link between the taken-for-grantedness of meaning and the stability of the social group.


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Taken-for-grantedness is the condition by reason of which meaning is pre-reflexively assumed. As a result, people treat their beliefs as if they are pure facts, and thus they see experience of the world as a stable entity. In other words, the taken-for-grantedness consists of experiencing a meaning as a fact. Consider the case of nations and their borders. They are felt to be facts, natural entities, no differently from rivers, oceans, mountains, etc. (Carrettero & Kriger, 2011). There is a sort of direct relation between taken-for-grantedness and the attributed value of truth of one’s worldview: the more the taken-for-grantedness of meanings, the more the actor considers her/his ideas and beliefs as the immediate mirror of the inherent qualities of the reality. Assuming the idea “the world is just as it is” involves being unaware of the fact that one’s own experience is an act of interpretation, reflecting the interpreter’s contingent standpoint. The recursive link between taken-for-grantedness and stability of the social group constitutes a self-perpetuating cycle. The more a certain system of meaning is taken for granted, the more it works as an instituted assumption for the social practice underlying it. As a result, the social practice acquires the status of a routine, therefore a fact, a stable reality. This is the way habit works: it provides an ordered, predictable domain, wherein each actor has a pre-reflective map of the possible acts other actors could perform. At the same time, the more the social practice is routinized, established as a matter of course, the more the redundancy of its replication conveys the consolidation of the taken-for-granted meanings underlying it. This is what constitutes the recursive link. Money is a good example of the dynamics outlined above. The value of the banknote does not lie in the sign (i.e., the piece of paper) but in the stability of social practices that adopt the interpretation of the sign in terms of the banknote as a takenfor-granted assumption regulating them. In each economic transaction (selling, purchasing, transfer, investment, etc.), we do not think about the “fictional” role played by banknotes, coins, or checks. People pre-reflexively assume the value of money without questioning it during exchanges. A certain quantity of money “does not represent” a certain economic value, but “it is” that value (Salvatore, 2012; see also the concept of social intentionality, Searle, 1990, 1995; and of interobjectivity, Harré & Sammut, 2013; Moghaddam, 2003).


Individual and Social Sense-Making

The previous discussion implies a peculiar understanding of the relation between cultural meanings and individual sense-making. Such a relation is modeled in several ways. Top-down perspectives consider cultural meanings as super-order frames that prescribe the individual sense-making. In our view, these conceptualizations fall into the mistake of the hypostatization of meaning. In other words, they consider it an entity endowed with its own ontological status and acting upon the individual sense-making from the outside. To be honest, this kind of perspective is able to address the issue of how individual interpretations can converge with each


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other and thus bring about social coordination. Yet, it raises as many problems as it solves, in the final analysis related with the idea of meaning as an entity. Indeed, if meaning is a thing of the world, where is it located? Where does it come from? How does it act on the individual mind from the outside? (for a discussion of these points, see, inter alia, Bickhard, 2009). The theoretical and methodological perspective of SCPT adopts a different perspective, based on the view of the embodiment of meaning. More specifically, it considers any meaning a sensorimotor propensity to interact in a certain way in the situated circumstances of the social practice (Salvatore, De Luca Picione, et al., 2021; Salvatore, Palmieri, et al., 2021). In this way, individual sense-making and social practice are closely connected. Indeed, sensorimotor patterns work as implicit systems of learning (according to the tenet of transformations of the frequency into preference—see Salvatore, 2018). This implies that the more redundant social practices are, the more they strengthen the sensorimotor pattern that makes them up. As a result, the cultural meanings that shape the action are interiorized as individual habits of feelings, thought, and action. Two relevant implications of this are worth highlighting. First, the meaning is inherent to the social practice and there is no need to split the cognitive processes underpinning individual sense-making and the cultural meanings inherent to the social practice (for a similar idea, see Lindblom, 2015). Each social practice is always simultaneously a dynamic pattern of sense-making, and vice versa. Second, neither cultural nor individual meanings are to be viewed as abstract super-order systems of rules. Instead, they are consolidated sensorimotor preferences (i.e., habits) shaping the pre-reflexive preference in terms of which actors select the following signs in the course of the action. As such, cultural meanings are at the same time individual meanings, just as any semantic and syntactic structure of the language is both a characteristic of the cultural milieu and a mode of working of the individual mind. Summarizing these reflections, the normativity of cultural meanings—that is, the function of orienting and shaping the ways of feeling, thinking, and acting—has its roots in the constitution of pre-reflexive habits that instantiate and consolidate social practices.



In the previous sections of this paragraph the structuralist idea of meaning as something inherently associated with the sign and conveyed by the latter has been challenged by the view of meaning as emerging from sense-making, namely as the product of the sensemaker’s activity, consisting in the activation of the following sign in terms of which the backward interpretation of the previous semiotic chain is taken a step ahead. This view enables us to avoid the reification of meaning and binds sense-making to the social setting of the action, depicting it as an inherent social and temporal field


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dynamic. Above all, it facilitates the operationalization of the analysis and the modeling of meaning. Indeed, the pragmatic view of meaning as the use of signs, and more specifically as the effect of this use—i.e., the following sign that the sign triggers—provides the empirical investigation with a clear indication as to what to look for and how to look in the search for a phenomenon that is both elusive and powerful enough to move mountains.


The Investigation of Meaning: Foci and Levels of Analysis

Based on the definition of the meaning discussed in the previous section, this section explores the different aspects that the empirical investigation of meaning can bring to the fore. To this end, two dimensions are considered: the focus and the level of analysis. The first concerns the aspect of meaning targeted by the analysis; the second concerns with the degree of generalization adopted to detect meaning.


Foci of Analysis

We propose to distinguish three foci of analysis: the dynamics of sense-making, its structure, and the content it produces. This distinction is based on the reversal between meaning and sense-making: if the meaning emerges from the sense-making, as the sign that follows, then a major task of analysis is the modeling of the semiotic dynamics from which the meaning comes—its inner organization (the structure) and its emergent product (the content).


The dynamic focus concerns the semiotic chain—it is aimed at modeling the sensemaking, namely how signs combine with each other over time and, in doing so, make the meaning emerge. We introduce a further specification for this focus, distinguishing between a genetic and systemic-developmental view of the dynamics. The genetic view focuses on the emergence of meaning, namely on the conditions, mechanisms, and microprocesses that underpin the constitution of meaning (e.g., representations, beliefs, pockets of knowledge) and its reproduction within people’s mind and the social landscape. Ethno-methodological analyses, as well as discourse analyses are instances of this focus on the genetic dynamics of sense-making. A further example of this approach is provided by Salvatore et al. (2006/2009) who modeled the emergence of a shared frame of meaning between patient and therapist. They showed


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that the dimensionality of the sense-making comprising patient-therapist communication underwent a dramatic drop after the first stage and then remained stable over the rest of the psychotherapy. They interpret this pattern as indicative of the emergence of constraints on the freedom of signs to combine with each other, interpreting it as the operational indicator of the supervenience of a context framing the communication and therefore making it interpretable and governable. The systemic-developmental view focuses on the inner organization of the dynamics, on its stability/evolution, in relation to the social context and its transformation. This approach is epitomized by Salvatore and colleagues’ analysis of the cultural dynamics underpinning the current socio-institutional crisis of Western societies (Salvatore, Mannarini, et al., 2019). The authors’ main argument is that the increasing salience of the affective form of sense-making in Western societies—and more specifically, the friend/foe schema—should be interpreted as indicative of the way many people try to make sense of the radical uncertainty characterizing the current socioeconomic context. The Equifinality Trajectory Model represents another instance of this approach, focused on the intra-individual evolution of the semiotic chain, modeled in terms of a trajectory subjected to a series of bifurcation points across irreversible time (e.g., Sato et al., 2009; Zittoun & Valsiner, 2016).


We identify the structure as another focus of the analysis of meaning. By structure we are referring to the inner organization of the dynamics of sense-making, namely the constraints that channel the selection of the signs activated through the semiotic chain, similarly to how the riverbed channels the course of the river. According to this view, the analysis of the structure of sense-making can be described with the analogy with wave spectrum analysis, namely as the decomposition of the semiotic chain in terms of elementary components, each of which is to be considered a basic dimension of sense mapping a component—i.e., a part of the variability—of the way signs combine with each other (Salvatore & Venuleo, 2013). For instance, the alternative views of migrant as drivers of threat as opposed to human beings in need of help can be broken down into two basic dimensions: value (good/ friend vs. bad/foe) and power (powerful vs. powerless). Accordingly, the combination of the poles negative and powerful, and positive and powerless generate the connotation of migrants as a threat and as people in need of help, respectively. Indeed, to be a threat one has to be bad and able to hurt, while to be in need of help one has to be good and unable to provide for oneself. To make it consistent with the characteristic of the semiotic chain of being a field dynamics (see above, § 1.5), Salvatore, Valsiner, and Veltri (2019) have further elaborated the concept of dimension of sense, in terms of line of semiotic force. They start from a geometrical model of the semiotic dynamics, namely a space each point of which represents a sign and each temporal association between two signs (e.g., sign B interpreting sign A) represents the movement from one point to the other within the space. Accordingly, sense-making can be mapped in terms of the


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trajectory followed by the signs within the semiotic space. Now, an implication of the notion of field is that it defines a space where the behavior of any element depends on the position within it. The gravitational field epitomizes this characteristic—each body is subjected to gravitational force as a function of its position within the gravitational field. Now, the field can be modeled in terms of the lines of forces that map the direction and magnitude of the force each point is subjected to. Similarly, the semiotic field can be modeled in terms of lines of semiotic force, where each line of semiotic force detects the intensity and orientation of the “pressure” that a component of sense exerts on the trajectory of signs at each point. The analysis of the Western societies’ cultural milieu carried out by Salvatore, Avdi, et al. (2019) takes the structural level of analysis into account. The authors identified three lines of semiotic forces, interpreted as the major components of the semiotic field comprising the cultural milieu of the European countries investigated. Line of semiotic force 1. Affective connotation of the world—friend versus foe (. . .) [This line of semiotic force] polarizes two opposing generalized, affect-laden ways of connoting the field of experience as a whole. On the one hand a positive connotation that depicts the world as a fine, trustworthy object, that can be engaged with; on the other hand, a negative connotation depicting it as unfair, meaningless, unreliable. (. . .) Line of semiotic force 2. Direction of desire—passivity versus engagement [This] line of semiotic force [consists] of what we propose to consider the direction of desire, namely the position assumed with regard the world: passivity versus engagement. Passivity is characterized by the sense of dependency on institutions, agencies and the primary network, thanks to which the subject can cope with the uncertain world; Engagement is characterized by the sense of agency, fostered by trust in people and institutions. In the final analysis, this line of semiotic force concerns the meaning of the world as the source of the action directed towards the subject (i.e., passivity) or, in contrast, as the goal of the subject’s investment (i.e., engagement). In other words, being the object or the subject of desire (investment, commitment, acting on). Line of semiotic force 3. Form of the demand—demand for systemic resources versus demand for community identity Overview In short, the polarities characterizing this [line of semiotic force] can be interpreted as the marker of the line of semiotic force consisting of the opposition between what we propose to consider two forms of demand, namely two basic views of what is one’s fundamental need: the demand for systemic resources versus the demand for a community bond. In the former case, the demand concerns the functional devices and services one needs in order to address a challenging, uncertain world; in the latter case the demand concerns the need to make life meaningful in spite of the untrustworthiness of institutions; where the meaning lies in the significant, vital participation in community bonds, namely bonds that go beyond the primary linkages (i.e., beyond the relation with family and close friends). (pp. 61–65)

It is worth adding that we do not see the structure of the semiotic field as separate from the dynamics and working on the latter from the outside. Rather, we consider the structure as the instant-by-instant constraining effect that the history of the dynamics exerts on its subsequent unfolding. A path in the woods exemplifies how the structure is inherent to the dynamics—the path is the effect of the walks


The Analysis of Meaning


that have taken place along it. Each walk leaves a track, which increases the probability that the walk is “selected” the next time, in a recurrent cycle that makes the walk, once happened, first a track and then a path.


Finally, the content of the sense-making is the third possible focus the analysis of meaning may valorize. This is the most practiced focus and therefore it does not need to be specified further. Many concepts are used in psychology and social science to denote the content of meaning; some of them refer to the meaning inside people’s head—e.g., mental models (Johnson-Laird, 1983), phantasies (e.g., Klein, 1967); others refer to the meaning which is active in the social context—e.g., social representation (Moscovici, 1961/1976), worldviews (Koltko-Rivera, 2004), basic values (Schwartz, 2016), political cultures (Gamson, 1988). In spite of how these concepts differ, they share the focus on the content—namely, the view of meaning as, broadly speaking, a stable enough association of signs providing a descriptive or evaluative statement as to what is/should be the segment of the world it refers to.


Levels of Analysis

One can distinguish different levels in the analysis of meaning, according to the degree of abstraction involved (for a similar approach, though adopted with a different analytical aim, see Valsiner, 2014). First of all, it is worth specifying what we mean by abstraction here. According to a view that can be associated with Bühler (1934/1990; see Salvatore & Valsiner, 2010), to abstract means to foreground/make pertinent some aspects/characteristics of the object and to background others: the greater the abstraction, the narrower the set of characteristics brought to the fore. This definition has important implications when applied to classes and sets. A highly abstract set is a collection that adopts a low number of characteristics as its classification function. For instance, the category “living being” is more abstract than “human being,” because the former’s classification function is poorer than the latter’s—an entity simply has to have the capacity of autopoiesis to be classified as a living being. It is important to add that the richness/poorness of the classificatory function is not only or mainly a matter of quantity of characteristics. Needless to say, the class of blue objects is more abstract than the class of cubic blue object, because the former’s boundary adopts a poorer classification function. Yet, the relevant difference concerns qualitative degrees of abstraction, due to the relation between the object and its context. From this standpoint, one can distinguish three degrees, at least. At degree 1, the object is defined based on its invariant characteristics, regardless of its links with other objects and the context. As a result, the object is classified by reason of its absolute empirical characteristics—e.g., a given object is classified as a


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specimen of apple, because of its color, form, organoleptic properties; Eleonora is classified as a specimen of the class of young girl, due to her age and sex. At degree 2, the object is defined in terms of its relation with other objects and the context—the empirical characteristics of the object can vary, yet the relation between the object and the other objects/context remains unchanged. For instance, the class of events “to pay” can be instantiated by specimens—e.g., to give a banknote, to sign a check, to place one’s credit card or phone on the electronic reader—that have very few, if any, detectable similarities with each other. What makes these actions equivalent specimens of the same class is their function, which is a specific kind of relation with other contextual elements. At degree 3, the object is defined in terms of meta-relations, namely relations of a relation. For instance, take generosity—specimens of this class could be: a person that adds a big tip to the restaurant bill; a person who does voluntary work to help other people; a group of people that collect funds for financing social projects; a person who invites a friend to dinner and serves the best food and wine. These specimens are similar because the actions that make them up have the same relation with the context; namely, in all four instances someone donates something to a target. Now, given that, as said above, the four actions are already forms of relation, then the similarity among them has to be considered a relation of relations—a metarelation. As appears clear if we compare payment and generosity, in the latter case the empirical content of the similarity among specimens disappears and the class is defined by a completely abstract classification function—in other words, the class includes elements that convey its defining quality in infinite empirical forms, in accordance with the similarly infinite circumstances. Generosity, like other meanings with this level of abstraction, has billions of ways of manifesting itself just as many forms of social exchange may be considered a form of generosity in certain circumstances and in accordance with certain points of view but not in others.


The empirical emptiness of the abstract category has four related implications that are relevant for the discussion below. First, the lack of empirical content of the abstract class’s classification function makes this kind of category inherently homogenizing—an abstract category encompasses elements even very different to each other, making them equivalent, as a result of their shared membership. It is worth noting that the homogenizing valence of abstract categories concerns not only specimens, but also properties (Tonti & Salvatore, 2015). The fact that elements, in many respects different to each other, are merged implies that the properties associated with these elements tend to be merged as well. This happens regardless—and above a certain level of abstraction, in spite of (Ciavolino et al., 2017)—their functional and conceptual differences, but rather, as a consequence of their being “attracted” by the category. For instance, for many people generosity and honesty are strictly associated—as the positive attitude most of us have toward Robin Hood shows—though there is no logic or functional relation between these two categories.


The Analysis of Meaning


Second, an abstract class has fuzzy boundaries—indeed, the weaker the anchorage to concrete experience, the more the boundary of that experience becomes a matter of interpretation, subject to the inherent pluralism of sense-making. This makes abstract categories inherently polysemic (Salvatore, De Luca Picione, et al., 2021; Salvatore, Palmieri, et al., 2021). The polysemy of abstract classes lies in the fact that any act of interpretation concerning this kind of category selects a particular pattern of elements among the infinite patterns made possible by the meta-relational definition of the abstract category. For instance, whereas the class of spherical objects is clearly defined by an invariant sensorial characteristic, the class of generosity is not defined by one or more stable characteristics—what generosity means depends on contexts and standpoints, which afford and select, respectively, the set of classification elements (e.g., a given combination of, say, feelings, frequency, quantity and type of resource mobilized, characteristics of receiving, other motivations and interest, secondary consequences, redundancy, and so forth). Third, an abstract class is holistic, namely it depends on the broader system of meaning it is framed in. Indeed, the fact that the abstract category is not defined by concrete elements that are invariant across context (see previous point) implies that its boundary follows a top-down path, being channeled by the sensemaker’s global system of meaning rather than by the constraints provided by experience. To continue the example used above, what the sensemaker means by generosity is not driven and channeled by sensorial data, but is a function of what the sensemaker thinks of social relations, what kind of value they endorse and so forth. To summarize, the more abstract the category is, the more its meaning is homogenizing, fuzzy, generalized, polysemic, holistic, autonomous from data of experience, as well as contingent to contexts (an illuminating example of this aspect is provided by Rommetveit, 1992) and to standpoints. Incidentally, the combination of polysemy and homogenizing makes abstract categories the grounds of the social exchange—people can feel they share the same categorical frame and at the same time use this frame in even very different ways—one of the present authors has called this process at the basis of social life the Pentecost effect (Salvatore, 2016).

Hierarchy of Meanings

This long premise was needed in order to clarify the assumption at the basis of the hierarchy. At the lowest level of abstraction, one finds meanings referring to specific, discrete specimens. Henceforth, we call this level singularities. Concrete meanings may concern events (“The train departed from the station at 11am” [a]), persons (“Sigmund Freud was born in Freibergon in 1856” [b]), physical entities (“the earth follows an elliptical orbit around the sun” [c]), social entities (“My son’s school” [d]), fictional entities (“Harry Potter was a brilliant student at the Hogwarts School of Witchcraft and Wizardry” [e]). This level corresponds to degree 1 outlined above. At a higher level of abstraction, one finds meanings referring to well-defined collections of objects. Rome’s Baroque churches [g], psychotherapy [h], vaccination


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[i], health system [j], migrants [k] are examples of this kind of set. We call this level discrete collections. These sets are more abstract than singularities; however, the abstraction is still somewhat limited here. As [g]-[k] show, at this level, collections still have somewhat clear-cut boundaries, defined by reason of a concrete enough classification function. This level can be placed in correspondence with degree 2. A further higher level of abstraction is provided by what we call generalized signs here, namely a combination of signs that have no factual reference and that can therefore have high polysemy and generalization. Generosity, love, honesty, duty, and so forth are instances of this class. This level corresponds to degree 3. According to Valsiner, categories of this kind can be seen as a sign to be modeled as fields, rather than points (Valsiner, 2007). Domain beliefs are a special subclass of generalized signs. Due to its very high level of abstraction and therefore extension, a domain belief—e.g., sense of community (e.g., Peterson et al., 2008), political value (e.g., Schwartz et al., 2010), conceptions of nature (Douglas & Wildavsky, 1982)— envelops a whole field of social life, working as a system of assumptions shaping the sensemaker’s interpretation and engagement with that domain of experience. A further level of abstraction is provided by hyper-generalized signs—namely, basic meanings providing a global interpretation of life as an all-encompassing whole. Basic values (Schwartz, 2016), the individualism-collectivism continuum (Trandis et al., 1988), the four types defined by the grid-group theory (Douglas & Wildavsky, 1982), worldviews (Koltko-Rivera, 2004), symbolic universes (Salvatore et al., 2018) are instances of constructs focused on this highly abstract level of meaning. It would correspond to a high level of degree 3 abstraction. We put the self-other schemata as the highest level of abstraction. The consideration of this further level is based on the psychoanalytic view of the self as endowed with an inner world consisting of primitive, unconscious patterns of embodied meaning emerging from the generalization of the early relational experiences with caregivers (Bowlby, 1969; Klein, 1967; Stern, 1985; see also Fornari, 1979) and shaping the experience of the object (i.e., the global class of what is other-from-theself)—e.g., the persecutory object, the feeding object and so forth. We consider this level to be characterized by even higher abstraction than hyper-generalized signs because, whereas at the level of hyper-generalized signs the content of the reality is still retained to a certain extent (as it is in the case of the worldview “life is a jungle”), at the self-other schemata latitude the content of reality disappears. At this level of maximum abstraction, the only characteristic abstracted is the immediate state of affective activation of the body, namely the re-activation of a pattern of sensorial memory that is always the same from the early stage of life when it emerged. Accordingly, at the self-other schemata level, the sensemaker assimilates the present time to an ultra-generalized class of meaning that makes the current field of experience homogeneous to an infinite set of past experiences, crossing the whole sensemaker’s life. The homogenizing function of abstraction merges present, past, and future in a deeply embodied single totality (Salvatore, De Luca Picione, et al., 2021; Salvatore, Palmieri, et al., 2021; for a discussion from a psychoanalytic standpoint, see Matte Blanco, 1975).


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Conclusive Remarks

Before concluding this section, we want to make two remarks. First, the forms of meanings outlined above are not intended to be separate entities, each endowed with its own ontological status. Rather, the hierarchy concerns the way of looking at meaning and sense-making—i.e., it concerns the observer’s heuristic framework, rather than what is observed (as implied in their labels as “levels of analysis”). This specification is needed because given its field nature (cf. §1), meaning—or rather, sense-making is a single global dynamic, whose many manifestations reflect the standpoint from which it is mapped—namely, what level of analysis (and focus) is adopted. To use an analogy, being in piazza di Spagna, in Rome, in Italy, in Europe are not different facts, which, because of their having autonomous ontological status, interact with each other—rather, they are different representations of a single state, each of them generated by the observational framework adopted (for similar considerations, see Heft, 2013). Second, for the sake of simplicity, the hierarchy of levels of analysis has been outlined above in reference to the content, outlining a continuum of the degree of abstraction of the categories of meaning. However, the differentiation among levels of analysis affects the structure too. Indeed, the dimensions of sense underpinning the dynamics of sense-making can be mapped in terms of discrete collection, generalized or hyper-generalized signs, as well as by magnifying the self-object schemata level. For instance, the lines of semiotic force described by Salvatore, Avdi, et al. (2019) (cf. 2.1) are a model of the dynamics of sense-making focused on the level of hyper-generalized signs. By contrast, Mazzara et al. (2020) adopt the discrete collections level in their structural analysis of the semantic field underpinning the way a sample of Turkish, Italian, and Greek newspapers represent migration. Indeed, they interpreted the dimensions of sense identified as “migrant vs. migration,” “indoor vs. outdoor,” “human issue vs. political issue,” “international conflict vs. internal affair” (although, in one case the dimension was represented at the generalized signs level—“engagement vs. protection”). Finally, the dimensions of the semantic differential (pleasantness/unpleasantness; powerful/ powerless; active/passive; cf. Osgood et al., 1975) are instances of components of meanings represented at the self-other schemata level.


Analytic Approaches

Just as one can use a wide-angle lens, or magnifying glass, or microscope or the like to explore the phenomenon under investigation, one can analyze meaning with a range of resolutions and related heuristic purposes. We propose to distinguish among the following approaches to meaning: semantic mapping, dimensional measurement, symbolic epidemiology, computational modeling, algorithmic implementation, and functional analysis.


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Semantic mapping provides a representation of the meaning—its content and/or underpinning structure—in verbal (or iconic) terms, namely in semantic form. The description of the lines of semiotic forces outlined above is an instance of this approach. Most studies based on social representation theory adopt this approach (e.g., Sammut et al., 2016). Dimensional measurement addresses meaning as a construct of variable size which needs to be estimated in its magnitude. Analyses based on the semantic differential epitomize this approach. For instance, Osgood et al. (1975) detected the meaning of a vast array of concepts by the estimation of the magnitude of their association with the three basic components underpinning the semantic differential scales. In other words, they defined the meaning of the concepts in terms of the salience of the three basic components within each of them. By symbolic epidemiology we mean a set of approaches that are involved in the distribution of meanings (e.g., attitudes, cognitive models, cultural worldviews) within a given social group. Thus, in this case the analysis concerns the incidence of the patterns of meaning investigated, namely where (in what social segment) and how much they are endorsed. The analysis of the incidence of the symbolic universes within European societies (Salvatore et al., 2018) epitomizes this approach. Crosscultural analyses aimed at estimating the degree of individualism/collectivism of societies is another well-known example (e.g., Heine, 2016). Computational modeling and algorithm implementation are less popular approaches that are mentioned here reflecting Marr’s discussion on analytical approaches to cognition (Marr, 1982). By computational modeling we mean the building of a description of the semiotic mechanisms underpinning sense-making dynamics. Thus, in this case meaning is not intended as content, but is analyzed in the terms of the rules that organize its emergence. In other words, whereas the other approaches address the what, the where, and the how much questions, computational modeling intends to respond to the why and how questions. The modeling of the emergence of a shared frame of sense developed by Salvatore et al. (2006/2009; cf. § 2.1) is an example of this approach. Further examples are provided by a series of psychotherapy case studies that are aimed at modeling the specific characteristics of the sense-making generated by the clinical setting and interpreting the clinical changes as a function of them (Salvatore et al., 2010; Salvatore & Gennaro, 2015). For instance, Salvatore et al. (2010) empirically modeled the trajectory of the sense-making characterizing a good-outcome psychotherapy, in terms of an oscillation between a phase of increasing constraints on the patient-therapist communication and a phase of increasing the degree of freedom that provides room for the emergence of semiotic innovation. The empirical model was built in terms of time series analysis of the dynamics and structural parameters of the network of meanings characterizing each session (see chapter DFA). Again, Kleinbub et al. (2021; cf. Chap. 2) have adopted this approach to validate the model of sense-making underpinning psychopathology. A neural network was trained in conditions of poor environmental stimulation, in order to simulate a low performing cognitive system. Then, the inner micro-dynamics of that cognitive system was compared with that of a high-performing cognitive system.


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The comparison focused on their respective dimensionality. Findings were coherent with the hypothesis that the “psychopathological” cognitive system is characterized by low-dimensional computational dynamics. Algorithm implementation complements the computational modeling. The aim of this approach is to translate the computational model of sense-making dynamics into a set of algorithms and parameters enabling the replication and forecasting of that dynamics on a simulation machine. This approach was epitomized by Madeo et al. (2021). The authors set a network of agents to simulate the interaction within a social landscape, with the aim of representing the evolution of cooperative behavior. The network’s parameters (e.g., agents’ propensity to cooperate; form and extension of the interactive sphere) were drawn from the characteristics of the symbolic universes identified by Salvatore, Avdi, et al. (2019). Thirty networks were established, each simulating the epidemiology of symbolic universes in a European region. An almost perfect overlapping between the output of the simulation and the actual level of cooperation in the regions sampled was found, a result that provides an initial validation of the computational interpretation of the symbolic universes on which the network parameters were set. Finally, by functional analysis we mean the understanding of the relation between meaning and other dimensions of the individual and social reality. It is worth adding that this relation can be analyzed in both directions—i.e., as the estimation of impact of meaning on other socio-psychological factors—e.g., voting behavior (Mannarini et al., 2020; Veltri et al., 2019); academic drop out (Venuleo et al., 2016), gambling (Venuleo et al., 2015)—as well as the detection of the role played by these factors in shaping meaning—e.g., the effect of the characteristics of the psychotherapeutic relation on sense-making (Rocco et al., 2017), the role played by uncertainty in the polarization of meaning (Greenberg & Arndt, 2012; Proulx & Inzlicht, 2012), the impact of the representation of medicine on patients’ compliance (Venezia et al., 2019).


The Epistemic Functions of the Analysis

By epistemic function we mean the general purpose and logical position of the analysis in the broader theoretical framework and strategy served by the empirical investigation of meaning. More specifically, in what follows we address two major issues related with this theme—the logical position of meaning in the architecture of the knowledge pursued and the relation between meaning and social environmental.


Meaning as Explanandum, Meaning as Explanans

Meaning can have two logical positions within a given process of knowledge building. On the one hand, it can be considered the core aim of the analysis, namely


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the phenomenon that has to be mapped, understood, comprehended; on the other hand, meaning can be considered the factor/process through which another phenomenon is understood. In the former case, one can speak of meaning as explanandum, while in the latter, meaning as explanans. The map of the representations of climate change active within the US population (Roser-Renouf et al., 2014) is an example of a study that locates the meaning in the position of the explanandum. Indeed, the aim of the study is to map what people think of issues related with climate change and to segment the US population according to those representations. The evocative title “Six Americas” epitomizes the methodological focus on meaning (the six representations the analysis identified) and on the use of this meaning as the criterion of population segmentation. It is worth adding that we use the term “explanandum” here in a broad sense—to indicate that the study has the analysis of meaning as its core aim, regardless of whether this meaning is considered strictly speaking something to be explained or only to be described. Veltri et al.’s (2019) analysis of the role played by symbolic universes in the Brexit vote is an example of positioning the meaning as explanans. Authors distinguished the 12 UK regions between those above and below the median of the proportion of leave votes. By means of a discriminant analysis, they showed that the difference between the two groups was fully predicted by a combination of parameters concerning the incidence of the symbolic universes and lines of semiotic force (cf. § 2.1) within each region. Thus, in this case the meaning was mapped, but as a way to explain the voting behavior. Mannarini and colleagues’ analysis (Mannarini et al., 2020) of the Italian voting behavior at the 2013 election epitomizes a mixed approach. They successfully tested an empirical model, with the mainstream vs. non-mainstream vote as the outcome and two layers of latent variables related to meaning as the predictor. More specifically, the model considered the voting behavior as affected by political cultures— e.g., level of trust in institutions, commitment to democracy, level of egalitarianism (Layer 1), in turn affected by symbolic universes (Layer 2). Thus, while the L1-outcome involves meaning as explanans, the L2–L1 relation treats meaning both as explanandum (L1) and explanans (L2).


Meaning and Social Environment

The relation between meaning and the social environment is a theoretically relevant issue. Long-standing disagreements are fuelled by the diametrically opposed tendency to emphasize the role of one element over the other—the social sphere as explicative, with the symbolic/cultural realm as super-structural and epiphenomenal as opposed to meaning as explicative, with the socio-economic aspect pushed into the background and/or in the role of dependent variable. Finding a synthesis between these polarizations can take two routes. The first route, the one preferred by the authors of the current chapter, comes from those who


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embrace a holistic approach to psychosocial phenomena. This holds that “social,” “psychological,” “cultural” are not indicative of ontological domains of the reality, but of epistemic strategies of analysis. According to this perspective, the social reality is a single whole corresponding to a general dynamics, which to be understood needs to be approximated step by step to work toward a unifying theory. Thus, just as physics operates in the framework of the unification of forces, the social sciences build a middle range theory as intermediate steps toward the general theory. In this view, meaning and the social sphere are distinguishable at the methodological and epistemic level, not ontologically. Consequently, they need to be modeled in terms of within-field dynamics, according to a notion of formal causality (Heft, 2013; Salvatore, 2021). Nevertheless, it should be recognized that this view is an intellectual niche—most psychologists and social scientists see the social environment and meaning as two different ontological domains, interacting with each other. As a result of this view, the issue of their interaction assumes great importance. This importance is also recognized by the advocates of the first approach, who are aware that, at the operational level of empirical analysis, the holistic approach based on the logic of formal causality does require at least a partial simplification with a computational model adopting the interactional logic that reifies meaning and the social context as two mutually related ontological domains (Salvatore & Cordella, 2022). Thus, once this interactional perspective has been adopted, for reasons of theoretical agreement or methodological convenience, the way of modeling the interaction gains momentum and leads to two different approaches. On the one hand, one finds analyses that are focused on the realm of meaning, focusing on intra-system linkages, i.e., on the interplay between different levels and spheres of meaning. Rochira et al.’s (2019) analysis of vaccination hesitancy as a function of symbolic universes epitomizes this approach—a hyper-generalized meaning (symbolic universes) is used as the explanans of a less abstract meaning (the view of vaccination). We call this approach endogenous, to underline the intra-systemic focus it pursues. On the other hand, one finds analyses that are aimed at comprehending the connection between contextual factors and sense-making. This connection can be explored both in the meaning-to-social-reality direction—as in the analyses already mentioned that model social behavior as a function of meaning (e.g., Mannarini et al., 2020; Veltri et al., 2019)—and in the social context-to-meaning direction. An instance of the latter approach is provided by Salvatore and colleagues (Salvatore, Mannarini, et al., 2019; see also Cremaschi et al., 2021) who interpret the current salience of affective sense-making in cultural dynamics as the way broad segments of society try to cope with the destabilization of their system of meanings due to the socio-economic turmoil generated by globalization. It is worth adding that the interpretative framework adopted by Salvatore, Valsiner, and Veltri (2019) is not confined to the society-to-meaning analysis. Indeed, it also takes the other approach into account, focusing on the impact of the affectivization of the public sphere in terms of impoverishment of social capital and weakening of institutional infrastructures. Thus, the analysis provides a recursive model of the connection between


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meaning and society. This is consistent with the holistic view and lends itself to be considered its operational translation at the level of empirical investigation.



In this chapter we have tried to highlight relevant issues concerning the analysis of meaning. The proposal was based on a preliminary theoretical discussion on the definition of the concept of meaning, aimed at presenting the arguments leading to adopt the Peircean pragmatic view of signs as a theoretical framework to model meaning and its role in social life. Our arguments converge in recognizing the fact that the anchoring of meaning to the social practices of sense-making provides the researcher with concrete, empirical points of access—i.e., discourse, actions, texts— to grasp a phenomenon that is both influential and hard to detect. On this basis, we have tried to outline a kind of map of the complex territory that any analysis of meaning has to find its place in. To this end, we concentrate on two major issues—the methodological strategy adopted—modeled in terms of foci and levels of analysis—and the epistemic purpose/aim of analysis—elaborated in terms of approaches, logical function, and meaning-environmental models.

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Sergio Salvatore is Professor of Dynamic Psychology at the Department of Human and Social Sciences, University of Salento. His scientific interests regard the psychodynamic and semiotic theorization of psychological and social phenomena and the methodology of analysis of sociocultural and mental processes as field dynamics. He also takes an interest in the theory and the analysis of psychological intervention in socio-political, community, scholastic, organizational as well as clinical fields. On these issues, he has designed and managed various scientific projects and published more than 300 works among volumes, chapters, and articles. Co-editor of the book series: Culture in Policy Making: The Symbolic Universes of Social Action (Springer) and Yearbook of Idiographic Science (IAP). Associate editor of journal Integrative Psychological and Behavioral Science. Editor-in-Chief of Rivista di Psicologia Clinica (The Italian Journal of Clinical Psychology). Email: [email protected]. Raffaele De Luca Picione, Ph.D., is associate professor of Dynamic Psychology at Giustino Fortunato University (Benevento, Italy), ASN qualified to the first rank, psychotherapist and psychoanalyst. His research focuses on subjectivity, affectivity, mind modelization and semiotic borders, temporality, narration and sense-making processes, qualitative research methodologies, from a psychoanalytic, cultural and semiotic perspective. He held research periods at Clark University (Massachusetts—USA) in 2012 and Aalborg University (Denmark) in 2015. In 2019, he was invited to give a lecture series at Universidad del Desarrollo in Santiago, Chile. He is the author of more than 150 international and national papers, including articles/books/essays/chapters. He is a member of editorial and scientific boards of several national and international scientific journals. He is co-editor of the International Journal of Psychoanalysis and Education: Subject, Action & Society. Email: [email protected].

Part II

Strategies of Analysis

Chapter 2

The Challenges of Cultural Segmentation: New Approaches from Computational Social Science Giuseppe A. Veltri

In this chapter, we explore a selection of computational methods that are being discussed in the context of cognitive sociology research for the purpose of cultural segmentation. While there is no perfect solution, these methods provide potential insights into identifying implicit cognitive schemata and their distribution across a population by means of samples. In particular, we will discuss two more theorydriven methods, Relational Class Analysis and Concept Association Task, and one method that is more based on the principles of statistical learning and data-driven, model-based recursive partitioning. From different angles, all three methods discussed can be applied to the task of cultural segmentation if combined with the use of proper large samples of participants. We will discuss the three approaches, their strengths and their shortcomings in their application to potential cultural segmentation.



Human variability manifests itself in many forms, and cultural pluralism is one of these forms. Cultural pluralism is about the multiplicity of meanings people attribute to events and social objects. Hence, it is connected to how individuals understand and make sense of their world (Cremaschi et al., 2021). As explained in Chap. 1, individuals are embedded in a network of semiotic resources within which every single element draws its meaning from being linked with the others. Accordingly, the cultural milieu is inherently pluralist: it hosts different standpoints, worldviews

G. A. Veltri (✉) University of Trento, Trento, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. Salvatore et al. (eds.), Methods and Instruments in the Study of Meaning-Making, Culture in Policy Making: The Symbolic Universes of Social Action,



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and beliefs, connected in a network of relationships of similarity and difference. In social research, as well as in policymaking, usually, socio-demographic, economic or legal variables drive the population segmentation, whereas cultural variables—i.e. different ways of thinking and relating to others, along with identity issues—are usually neglected (Andriola et al., 2019). Indeed, while from a theoretical point of view, the idea of cultural segmentation is appealing and fruitful, much still needs to be done in terms of research methodology. Specifically, for cultural segmentation we mean the complex relationship between declarative knowledge of culture and its visible repertoires and people’s implicit cultural schemata. Every research method in the social sciences that concerns people have an implicit model of how people behave, create their preferences and attitudes and how humans decide to do something. This model is often taken for granted in any context. For example, if I conduct in-depth interviews about how people shop at the supermarket, the assumption is that an individual’s purchasing choices are guided by conscious deliberation. This may be the case in some circumstances, but it is well known how the implicit, hence non-conscious, heuristic mode plays a crucial role in many contexts such as this, where one has little time and few cognitive resources to devote to action on the matter. Recent methodological debates in sociological circles raise critical questions about what data we collect and what these can tell us about culture and cognition. For example, Vaisey (2009) suggests that interviews primarily capture discursive consciousness and ex post facto justifications for action but cannot access unconscious cognitive processes (which more accurately predict implicit cultural schemas, according to Vaisey). Instead, Vaisey argues that forced-choice surveys effectively reveal patterns in people’s practical moral consciousness, forcing respondents to make a choice quickly. Critics who suggest that ‘talk is easy’ argue that not only verbal methods such as interviews fail to capture the cognitive frames that influence action, but also that the surveys Vaisey claims are victims of an ‘attitudinal fallacy’ (Jerolmack & Khan, 2014). The heuristic and implicit modes of cognition pose a significant challenge to traditional methods based on ‘self-reported’ data, i.e. based on what participants report doing and believing. The necessity of identifying not only cultural schemas through declarative data but also inferring those that are non-consciously adopted requires the use of different methods compared to the past. At the same time, the presence of cultural schemas, often implicit, that may cut across the traditional sociological categories into which individuals are classified, essentially based on social, economic and demographic variables, requires new forms of data modelling and categorisation tools. There is still no canonisation of the most effective methods in the study of culture and cognition, so this selection must be understood as non-exhaustive. Before we proceed further, we need to clarify what we mean here by cultural schemata (or schemas). In our approach, we should use cultural schemata as a macro-level analogue of cognitive schemata, rather than as a sub-type of cognitive schemata. There are three main arguments for this, all related to the goal of accessibility and usefulness as a bridging concept. A supra-individual conceptualisation of cultural schemata: (1) is better suited to the object of


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sociological research: culture in the broadest sense, (2) has better compatibility with most sociological theories and (3) is not incompatible with a strong emphasis on individual cognition as the micro-foundation of culture when treated as an analytical concept. There are, however, strong objections to the conceptualisation of the cultural schema as a supra-individual macro-level concept. Many cognitive science-inspired cultural researchers have recently argued against the ‘traditional’ supra-individual views of culture, in favour of an ‘individualist’ view in which culture refers to more or less shared cognitive schemas constructed from interaction and shared experiences (cf. Lizardo, 2007; Lizardo et al., 2016; Turner, 2007a, b). The main objection of these researchers seems to be an aversion to what Lizardo called ‘ontologically spurious anti-cognitive pseudo-objects’ (Lizardo, 2014, 988), or what Turner (2007b) refers to as mysterious ‘collective objects’. Looking more closely at their arguments, it becomes clear that what Lizardo and Turner are objecting to is mainly the reification of analytical concepts at the macro level, i.e. the treatment of things like cultural patterns as ‘ontologised units’ existing only in the ‘sociological ether’. However, there are two unjustified assumptions in the critique against supraindividual cultural concepts, namely that (1) analytical concepts must have an independent ontological substance to be meaningful and (2) working with higherorder abstractions necessarily obscures their micro-foundation. It should be made clear that a supra-individual conceptualisation of cultural schemata is understood as an analytical concept and not an ontological object, in the sense of Turner’s (2007b) ‘collective objects’ and ‘ontologised units’. As an analytical concept, cultural schemata are anything but mysterious—they are what they claim to be and nothing else: a way of referring to recurring social patterns observed by researchers or laymen. In other words, the notion of ‘cultural patterns’ is a synthetic way of talking about phenomena emerging from complex processes, as sociologists have always done, but in a way that is much more compatible with the language and insights of cognitive science. Over the past two decades, psychologists have distinguished between two systems of thinking with different capabilities and processes (Evans, 2003, 2008; Kahneman, 2011; Kahneman & Frederick, 2002; Metcalfe & Mischel, 1999), which have been referred to as system 1 and system 2 (Stanovich & West, 2000). System 1 (S1), on the one hand, consists of high-capacity intuitive thinking, is based on associations acquired through experience and calculates information quickly and automatically. System 2 (S2), on the other hand, involves low-capacity reflective thinking, relies on rules acquired through culture or formal learning and calculates information in a relatively slow and controlled manner. The processes associated with these systems have been defined as type 1 (fast, automatic, unconscious) and type 2 (slow, conscious, controlled). This understanding of type 1 processing means that measurement approaches that focus exclusively on common indicators of automaticity increase the likelihood of capturing type 1 cognition but cannot exclude alternative processes. Rapid response, for example, suggests automatic processing, but can also be realised through the conscious and well-practised application of rules. However, alternative explanations disappear to the extent that respondents


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lack control over their answers (Gawronski & De Houwer, 2014). The level of intentional control thus provides a benchmark for evaluating different measurement strategies and, as we shall see, weakens the claim of some measures that purport to touch on the system or type 1 cognition. According to cognitive sociologists, cognitive schemata are best captured by type 1 cognition, revealing their distribution in a population and therefore allowing to identify cultural schemata. The methods discussed in this chapter cover both methods of analysis and elicitation of responses: 1. The model-based recursive partitioning analysis technique is a method that allows us to identify subsets of a population in terms of declination of a general model; 2. The technique of relational class analysis and correlation class analysis, a way of identifying shared cultural patterns between subjects in a population by analysing manifest variables of preferences or attitudes; 3. In the Concept Association Task, respondents are shown concepts related to a given topic two at a time and asked to indicate whether they are related. The necessary premise for using computational methods is that the development of the Internet has introduced new possibilities for data collection. Among several, the use of population-based online experiments is becoming popular. Although Internet-based interviews with representative samples of the population are still in their infancy, it is already possible to provide pictorial stimuli and films to random samples of respondents. The ability to exploit such dynamic data collection tools has expanded the methodological repertoire and inferential range of social scientists in many fields. Although population-based survey experiments were done by telephone or face-to-face long before the Internet-based interview emerged, the Internet has dramatically increased their potential. The many advances in digital interview technology present social science with the potential to introduce some of its most important hypotheses in virtual laboratories scattered across the nation. Whether evaluating theoretical hypotheses, examining the robustness of laboratory results, or testing empirical hypotheses of other varieties, the ability of social scientists to experiment on large and diverse groups of subjects allows them to address important social and behavioural phenomena more effectively and efficiently. Extending experiments to large samples, both national and international, increases the potential heterogeneity present in response to our treatments. Therefore, identifying and studying such heterogeneity is a crucial step in the world of online behavioural experiments. New analytical techniques have emerged in computational and computer sciences that are very promising to achieve this goal. One of the best examples of how social science can benefit from analytical approaches developed in computational methods is the development of model-based recursive partitioning.


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Model-Based Recursive Partitioning

New analysis techniques have emerged in the computational and computer sciences. One of the best examples of how social science can benefit from analytical approaches developed in the context of computational methods is the development of model-based recursive partitioning. This approach is an improvement on the use of classification and regression trees, the latter also being a method from the ‘algorithmic culture’ of modelling that has useful applications in the social sciences but which is essentially data-driven (Berk, 2006; Hand & Vinciotti, 2003). In summary, classification and regression trees are based on a purely data-driven paradigm. Without using a predefined statistical model, such algorithmic methods recursively search for groups of observations with similar values to the response variable by constructing a tree structure. They are very useful in data exploration and express their best utility in the context of very complex and large data sets. However, such techniques make no use of theory in describing a model of how the data were generated and are purely descriptive, although far superior to the ‘traditional’ descriptive statistics used in the social sciences when dealing with large datasets. Model-based recursive partitioning (Zeileis et al., 2008) represents a synthesis of a theoretical approach and a set of data-driven constraints for theory validation and further development. In summary, this approach works through the following steps. Firstly, a parametric model is defined to express a set of theoretical assumptions (e.g., through a linear regression). Second, this model is evaluated according to the recursive partitioning algorithm, which checks whether other important covariates that would alter the parameters of the initial model have been omitted. The same regression or classification tree structure is produced. This time, instead of partitioning by different patterns of the response variable, the pattern-based recursive partitioning finds different patterns of associations between the response variable and other covariates that have been previously specified in the parametric model. In other words, it creates different versions of the parametric model in terms of beta (β) estimation, depending on the different important values of the covariates. (For the technical aspects of how this is done, see Zeileis & Hornik, 2007.) In other words, the presence of splits indicates that the parameters of the initial theory-driven definition are unstable, and that the data are too heterogeneous to be explained by a single global model. The model does not describe the entire dataset.


Technical Details

Classification trees look for different patterns in the response variable based on the available covariates. Since the sample is divided into rectangular partitions defined by the values of the covariates and since the same covariate can be selected for several partitions, classification trees can also evaluate complex interactions, non-linear and non-monotonic patterns.


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The structure of the underlying data generation process is not specified in advance but is determined in an entirely data-driven manner. These are the key distinctions between classification and regression trees and classical regression models. The approaches differ, firstly, with respect to the functional form of the relationship which is limited, for example, to the linear influence of covariates in most parametric regression models and, secondly, with respect to the pre-specification of the model equation in parametric models. Historically, the basis for classification and regression trees was first developed in the 1960s as Automatic Interaction Detection (Morgan & Sonquist, 1963). Later, the most popular algorithms for classification and regression trees were developed by Quinlan (1993) and Breiman et al. (1984). Here we focus on a more recent framework by Hothorn, Hornik, and Zeileis (2006), which is based on the conditional inference theory developed by Strasser and Weber (1999). The main advantage of this approach is that it avoids two fundamental problems of previous classification and regression tree algorithms: variable selection bias and over-fitting (see, e.g., Strobl et al., 2009). Hothorn, Hornik, and Zeileis’ (2006) algorithm for recursive binary partitioning can be described in three steps: first, starting with the entire sample, the global null hypothesis that there is no relationship between any of the covariates and the response variable is assessed. If, on the one hand, no violation of the null hypothesis is detected, the procedure stops. If, on the other hand, a significant association is discovered, the variable with the largest association is chosen for splitting. Secondly, the best cut point in this variable is determined and used to split the sample into two groups according to the values of the selected covariate. Then the algorithm recursively repeats the first two steps in the subsamples until there is no more violation of the null hypothesis, or a minimum number of observations per node are reached. In the following, we briefly summarise which covariates can be analysed using classification and regression trees, how the variables are selected for splitting and how the cut point is chosen. Classification trees look for groups of similar response values with respect to a categorical dependent variable, while regression trees focus on continuous variables. Hothorn, Hornik, and Zeileis (2006) point out that their conditional inference framework can also be applied to ordinal and censored survival time situations and multivariate response variables. Within the resulting tree structure, all respondents with the same covariate values—represented graphically in a final node—obtain the same prediction for the response, i.e. the same class for categorical responses or the same value for continuous response variables. The next question is how the variables for potential splits are chosen and how the relevant cut points can be obtained. As described above, Hothorn, Hornik, and Zeileis (2006) provide a statistical framework for tests applicable to various data situations. In the recursive binary partitioning algorithm, each iteration is relative to a current data set (from the entire sample), where the variable with the highest association is selected by means of permutation tests as described below. The use of permutation tests makes it possible to evaluate the global null hypothesis H0 that none of the covariates has an influence on the dependent variable. If H0 is valid—in other words, if the independence between any of the covariates Zj ( j = 1,. . ., l) and the dependent variable Y cannot be rejected—the algorithm stops. Thus, the


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statistical test acts both for variable selection and as a stopping criterion. Otherwise, the strength of the association between the covariates and the response variable is measured in terms of p-value, which corresponds to the partial null hypothesis test that the specific covariate is not associated with the response. Thus, the variable with the smallest p-value is selected for the next split. The advantage of this approach is that the p-value criterion guarantees an unbiased selection of variables regardless of the measurement scales of the covariates (see, e.g., Hothorn, Hornik, & Zeileis, 2006; Strobl et al., 2009). Permutation tests are constructed by evaluating the test statistic for the data given under H0. Monte-Carlo or asymptotic approximations of the exact null distribution are used to calculate p-values (see Hothorn, Hornik, van de Wiel, & Zeileis, 2006; Hothorn, Hornik, & Zeileis, 2006; Strasser & Weber, 1999, for more details). After the variable for the split has been selected, we need a cut point within the range of the variable to find the subgroups that show the strongest difference in the response variable. In the procedure described here, the selection of the cut point is also based on the permutation test statistic: the idea is to calculate the two-sample test statistic for all potential splits within the covariate. In the case of continuous variables, it is reasonable to limit the studied splits to a percentage of potential cut points; in the case of ordinal variables, the order of the categories is taken into account. The resulting split lies where the binary separation of two data sets leads to the highest test statistic. This reflects the largest discrepancy in the response variable with respect to the two groups. In the case of missing data, the algorithm proceeds as follows: observations that have missing values in the currently evaluated covariate are ignored in the split decision, while the same observations are included in all other steps of the algorithm. The class membership of these observations can be approximated by means of the so-called surrogate variables (Hothorn, Hornik, & Zeileis, 2006). Model-based recursive partitioning was developed as an advancement of classification and regression trees. Both methods come from the field of machine learning, which is influenced by both statistics and computer science. The algorithmic logic behind classification and regression trees is described by Berk (2006, p. 263) as follows: ‘With algorithmic methods, there is no statistical model in the usual sense; no effort is made to represent how the data were generated. And no excuse is offered for the absence of a model’. There is a practical data analysis problem to be solved that is attacked directly with procedures designed specifically for this purpose. In this sense, classification and regression trees are purely data-driven and exploratory—and thus mark the opposite of the model specification theory-based approach that is prevalent in the empirical social sciences. The advanced modelbased recursive partitioning method, however, combines the advantages of both approaches: at first, a parametric model is formulated to represent a theory-driven research hypothesis. Then this parametric model is handed over to the model-based recursive partitioning algorithm that checks whether other relevant covariates have been omitted that would alter the model parameters of interest. Technically, the tree structure obtained from the classification and regression trees remains the same for model-based recursive partitioning.


G. A. Veltri

For the sake of explanation, in this example, we are using covariates of commonly observed variables but exactly the same can be done with latent variables derived from non-directly observable characteristics of individuals. For example, in Fig. 2.1, using data from a current study, we modelled (in a simplified manner using a linear regression model) the relationship between European parents’ risk perception of online dangers (dependent variable), their level of ‘digital skills’ (independent variable) and their children’s level of digital skills (another independent variable). We tested the significance of covariates such as age (of the child, coded in three groups), level of education (of the parents), age of the parents and country of residence. This model is visualised using a regression tree in which the upper part presents the divisions according to the different values of the covariates (e.g. division 1 is made using the covariate ‘country’ resulting in France, Italy, Poland and Spain, on the one hand, and Germany, the Netherlands, Sweden and the UK, on the other) while the lower part represents the dependent variable from the relationship and two independent variables expressed in two scatter-plots one after the other. The lower part shows the ‘local model’ (locally based on a subset of the original dataset) labelled as ‘node’: for example, node 4 is the model expressed by the parents of Italy and Poland aged 37 years or less (this is the division value for the age covariate in this case). The model-based recursive division finds different patterns of associations between the response variable and other covariates that have been pre-specified in the parametric model. Figure 2.1 shows how the relationship between the dependent variable and two independent variables changes considerably (in a statistically significant manner, as indicated by the p-values) in the different subdivisions of the sample of respondents. Clearly, the initial model is insufficient to explain this relationship without taking some of these covariates into account. For example, if the relationship between the dependent variable and each independent variable changes sign for certain partitions of the dataset represented by the subgroups, a one-size-fits-all approach is highly problematic. Figure 2.1 shows how different covariates produce divisions in the two country groups. Node 11 is an example of a different ‘local’ pattern of the relationship between parents’ risk perceptions, their digital skills and their children’s digital skills for Northern European parents with above-average education and 9–11-year-old children than for the others. The example also shows that, unlike classification and regression trees, the final nodes in the model-based recursive partitioning do not contain values of a response variable but represent a statistical model for each specific subpopulation. Between these groups, the estimated parameters of the common underlying model vary significantly, but the postulated basic functional form (here polynomial) stated by the researcher is fixed. Within the subgroups, there is no significant instability of parameters. Thus, the interpretation of a tree with no division is quite simple: there are no significant parameter instabilities in any of the covariates delivered to the algorithm. If, on the other hand, a tree structure is displayed, it reveals that the postulated model is not adequate to describe the entire sample. Parameter variation reveals structural

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Fig. 2.1 Example of recursive partitioning based on a theoretical model. The figure represents a decision tree in which elliptic shapes stand for a node of the tree. Each node of the tree is a split of the sample by a specific covariate, each shape also contains the p-value associated with that split. For example, node 1 is determined by the covariate ‘country’ with a p-value of