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Drawing on individual-level full-population data from Sweden, spanning four decades, we investigate the joint growth of income inequality and income segregation. We study Sweden as a “least likely” case comparison with the United States, given Sweden’s historically low levels of inequality and its comprehensive welfare state. Against the background of U.S.-based scholarship documenting a close link between inequality and segregation, our study provides an important insight into the universality of this relationship. Using entropy-based segregation measures, we analyze trends and patterns of income segregation between and within income groups along different sociodemographic dimensions—migration background and family type. Our findings reveal that growing income inequality in the last 30 years has been accompanied by a sharp uptake in income segregation, especially for the bottom quartile of the income distribution who are facing increasing isolation. Income segregation is most extensive for individuals with children in the household, among whom it has increased at a higher rate than those without children. Interestingly, income segregation is lower among non-Western minorities than among majority-group Swedes. We conclude that changes to the welfare state, liberalization of the housing market, and rapid demographic changes have led Sweden onto a path that is difficult to distinguish from that taken by the United States.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Selcan Mutgan: Department of Management and Engineering, Institute for Analytical Sociology, Linköping University
E-mail: selcan.mutgan@liu.se

Jonathan J. B. Mijs: Department of Sociology, Boston University; Department of Public Administration and Sociology, Erasmus University Rotterdam
E-mail: mijs@bu.edu

Acknowledgments: We would like to thank Maria Brandén, Jackelyn Hwang, Peter Hedström, and Jaap Nieuwenhuis for helpful feedback and comments on earlier versions of this manuscript. For their parts in the research on which the results are based, S.M. received funding from the Swedish Research Council (Vetenskapsrådet), grant numbers DNR 340-2013-5460, 445-2013-7681, and DNR 2020-02488, and J.J.B.M. received funding from a Marie Skłodowska-Curie Individual Fellowship, EU Commission Horizon 2020 grant number 88296, and a Veni grant (number VI.Veni.201S.003) from the Dutch Research Council.

Citation: Mutgan, Selcan, and Jonathan J. B. Mijs. 2023. “Income Inequality and Residential Segregation in ‘Egalitarian’ Sweden: Lessons from a Least Likely Case.” Sociological Science 10:374-402.
Received: December 9, 2022
Accepted: January 14, 2023
Editors: Ari Adut, Cristobal Young
DOI: 10.15195/v10.a12

Recreating a Plausible Future: Combining Cultural Repertoires in Unsettled Times

By Parker Webservices on May 3, 2023 in Articles

Shira Zilberstein, Michèle Lamont, Mari Sanchez

Sociological Science May 3, 2023
10.15195/v10.a11

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This article analyzes how young adults draw on cultural resources to understand their identities, aspirations, and goals when taken-for-granted scripts of success are perceived as less desirable or achievable. Drawing on pragmatism, we propose the concept of “plausible futures” to capture how people rearrange elements within cultural repertoires as a practical and moral project to define their identities, aspirations, and goals. We draw on interviews with 80 college students concerning how they understand their future aspirations, including how they define personal success and broader social goals, when they face unpredictability in, and dissatisfaction with, achieving dominant meritocratic and socioeconomic ideals. We find that respondents combine elements from four cultural repertoires to work toward and envision their future: the American dream and neoliberalism, the therapeutic culture, ordinary cosmopolitanisms, and a “Gen Z” cohort narrative. The combining of elements from each repertoire enables a hybrid set of cultural tools that hold to tenets of hard work and self-reliance while accommodating the quest for greater recognition and inclusion. We show that respondents combine cultural elements based on their ability to connect elements to futures perceived as viable and valuable.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Shira Zilberstein: Department of Sociology, Harvard University
E-mail: szilberstein@fas.harvard.edu

Michèle Lamont: Department of Sociology, Harvard University
E-mail: mlamont@wjh.harvard.edu

Mari Sanchez: Department of Sociology, Harvard University
E-mail: mjsanchez@g.harvard.edu

Acknowledgments: Michèle Lamont acknowledges a residential fellowship at the Russell Sage Foundation (2019–20) and a Carnegie Fellowship (2019–21). The authors thank the other members of the research team: Laura Adler, Jonathan Cook, Elena Ayala-Hurtado, Nicole Letourneau, Derek Robey, and Priya Thelapurath. We also thank Lisa Albert and Kathleen Hoover for their technical assistance. This article benefited from comments from members of the American Sociological Association panel on Between Collapse and Utopia; the Culture workshop at New York University; the Race, Ethnicity, and Migration Workshop at Columbia University; and the Comparative Inequality and Inclusion Cluster, Culture and Social Analysis Workshop, and “Inside the Sausage Factory” workshop at Harvard University. We thank the following colleagues for their comments: Francesca Polletta, Manja Klemencic, Ann Mische, and Elena Ayala-Hurtado.

Citation: Zilberstein, Shira, Michèle Lamont, and Mari Sanchez. 2023. “Recreating a Plausible Future: Combining Cultural Repertoires in Unsettled Times.” Sociological Science 10: 348-373.
Received: August 27, 2022
Accepted: March 14, 2023
Editors: Ari Adut, Stephen Vaisey
DOI: 10.15195/v10.a11

Marginal Odds Ratios: What They Are, How to Compute Them, and Why Sociologists Might Want to Use Them

By Parker Webservices on April 27, 2023 in Articles

Kristian Bernt Karlson, Ben Jann

Sociological Science April 27, 2023
10.15195/v10.a10

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As sociologists are increasingly turning away from using odds ratios, reporting average marginal effects is becoming more popular. We aim to restore the use of odds ratios in sociological research by introducing marginal odds ratios. Unlike conventional odds ratios, marginal odds ratios are not affected by omitted covariates in arbitrary ways. Marginal odds ratios thus behave like average marginal effects but retain the relative effect interpretation of the odds ratio. We argue that marginal odds ratios are well suited for much sociological inquiry and should be reported as a complement to the reporting of average marginal effects. We define marginal odds ratios in terms of potential outcomes, show their close relationship to average marginal effects, and discuss their potential advantages over conventional odds ratios. We also briefly discuss how to estimate marginal odds ratios and present examples comparing marginal odds ratios with conventional odds ratios and average marginal effects.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Kristian Bernt Karlson: Department of Sociology, University of Copenhagen
E-mail: kbk@soc.ku.dk

Ben Jann: Institute of Sociology, University of Bern
E-mail: ben.jann@unibe.ch

Acknowledgments: We thank the following for invaluable comments and feedback: Tim Liao, Mike Hout, Rudolf Farys, and Jesper Fels Birkelund, as well as participants at the Hans Schadee Research Methods Center Seminar on November 3, 2022, at Trento University; the Seminar on Analytical Sociology on November 14–17, 2022, at Venice International University; and the 2022 Swiss Stata Meeting on November 18, 2022, at University of Bern. For Kristian Bernt Karlson, the research leading to the results presented in this article has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 851293). Replication materials for the examples reported in this article are available here: https://osf.io/xkre6/.

Citation: Karlson, Kristian Bernt, and Ben Jann. 2023. “Marginal Odds Ratios: What They Are, How to Compute Them, and Why Sociologists Might Want to Use Them.” Sociological Science 10: 332-347.
Received: January 31, 2023
Accepted: February 17, 2023
Editors: Arnout van de Rijt, Stephen Vaisey
DOI: 10.15195/v10.a10

From Social Alignment to Social Control: Reporting the Taliban in Afghanistan

By Parker Webservices on April 17, 2023 in Articles

Patrick Bergemann, Austin L. Wright

Sociological Science April 17, 2023
10.15195/v10.a9

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In many settings, witnesses can report wrongdoing to internal authorities such as officials within an organization or to external authorities such as the police. We theorize this decision of where to report as rooted in the policing of group boundaries, as the use of different reporting channels symbolically affirms or disaffirms affiliation with different social categories. As such, both witnesses and other social actors have an interest in where witnesses report. We evaluate this theory using villagers’ reporting of illegal Taliban activity in Afghanistan in 2017 and 2018, where witnesses could report externally (e.g., to the national police) or internally (e.g., to village elders). We show how responses to wrongdoing arose from the interaction between self and others’ attitudes toward the Taliban, and we reveal how reporting can be simultaneously punitive for the wrongdoer and affiliative for the category to which the wrongdoer belongs.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Patrick Bergemann: Paul Merage School of Business, University of California, Irvine
E-mail: pbergema@uci.edu

Austin L. Wright: Harris School of Public Policy, The University of Chicago
E-mail: austinlw@uchicago.edu

Acknowledgments: The authors are grateful to the U.S. Military for granting access to the survey materials used in this study. A particular debt of gratitude is owed to Phil Eles, senior research scientist at NATO, for providing continued support for this research and related projects. The authors would also like to thank Amanda Sharkey and Daniel Karell for their helpful comments. This article benefited from presentations at the Comparative Research Workshop at Yale University and at the Paul Merage School of Business at the University of California, Irvine.

Citation: Bergemann, Patrick, and Austin L. Wright. 2023. “From Social Alignment to Social Control: Reporting the Taliban in Afghanistan.” Sociological Science 10: 286-331.
Received: January 12, 2023
Accepted: February 19, 2023
Editors: Ari Adut, Andreas Wimmer
DOI: 10.15195/v10.a9

Homophily, Setbacks, and the Dissolution of Heterogeneous Ties: Evidence from Professional Tennis

By Parker Webservices on March 24, 2023 in Articles

Xuege (Cathy) Lu, Shinan Wang, Letian Zhang

Sociological Science March 24, 2023
10.15195/v10.a7

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Why do people engage with similar others despite ample opportunities to interact with dissimilar others? We argue that adversity or setbacks may have a stronger deteriorative effect on ties made up of dissimilar individuals, prompting people to give up on such ties more easily, which, over the long run, results in people forming ties with similar others. We examine this argument in the context of Association of Tennis Professionals tournaments, using data on 9,669 unique doubles pairs involving 1,812 unique players from 99 countries from 2000 to 2020. We find that doubles pairs with players from different countries are more likely to dissolve after a setback, especially if those countries lack social trust and connections with one another; this reality further contributes to the individual player’s increased tendency to collaborate with same-country players in the next tournament. Our study has direct implications for interventions for diversity and inclusion.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Xuege (Cathy) Lu: Carlson School of Management, University of Minnesota
E-mail: xuegelu@umn.edu

Shinan Wang: Kellogg School of Management, Northwestern University
E-mail: shinan.wang@kellogg.northwestern.edu

Letian Zhang: Harvard Business School
E-mail: lzhang@hbs.edu

Acknowledgments: We thank Alice (Can) Wang for excellent research assistance. Our data and replication code can be found via https://osf.io/x23ay/?view_only=9521ee27707944fa80004f0561372943.

Citation: Lu, Xuege (Cathy), Shinan Wang, and Letian Zhang. 2023. “Homophily, Setbacks, and the Dissolution of Heterogeneous Ties: Evidence from Professional Tennis.” Sociological Science 10: 227-250.
Received: September 28, 2022
Accepted: December 12, 2022
Editors: Arnout van de Rijt, Andreas Wimmer
DOI: 10.15195/v10.a7

Ethno-nationalism and Right-Wing Extremist Violence in the United States, 2000 through 2018

By Parker Webservices on March 20, 2023 in Articles

Susan Olzak

Sociological Science March 20, 2023
10.15195/v10.a6

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Influential studies of right-wing extremist violence offer evidence that such violence is motivated by grievances intensified by a perceived loss in status or by economic dislocations. This article moves away from an emphasis on grievances by turning to theories of ethno-nationalism and group conflict. Ethno-nationalism is in part driven by attitudes of dominant groups favoring ethnic exclusion, whereas group threat theories explain that ethnic diversity increases the salience of ethnic boundaries and fuels a collective response to group threat. Such threats encourage violence to contain this threat and restore dominance. Exclusionary attitudes and support for expanded gun rights in America further legitimize a culture of ethno-nationalism that encourages violent acts. I test these arguments with data from the Pew Research Center, the Southern Poverty Law Center, and the Extremist Crime Database on right-wing violence. The state-level and county-level results support the claim that rising ethnic diversity raises the rate and volume of right-wing violence significantly. State-level results also find that rising memberships in the National Rifle Association increase the rate of right-wing violence significantly.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Susan Olzak: Stanford University
E-mail: olzak@stanford.edu

Acknowledgments: The author thanks Trent Steidley, Holly Hansen, and Stephen C. Nemeth for providing some of the data used in this study. The author is grateful to Bart Bonikowski, Mike Hannan, Doug McAdam, Rory McVeigh, Sarah A. Soule, Andy Walder, and Nella Van Dyke for providing helpful suggestions and criticisms on earlier drafts.

Citation: Olzak, Susan. 2023. “Ethno-nationalism and Right-Wing Extremist Violence in the United States, 2000 through 2018.” Sociological Science 10:197-226.
Received: August 17, 2022
Accepted: December 8, 2022
Editors: Ari Adut, Peter Bearman
DOI: 10.15195/v10.a6

Dissecting the Lexis Table: Summarizing Population-Level Temporal Variability with Age–Period–Cohort Data

By Parker Webservices on March 13, 2023 in Articles

Ethan Fosse

Sociological Science March 13, 2023
10.15195/v10.a5

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Since Norman Ryder’s (1965) classic essay on cohort analysis was published more than a half century ago, scores of researchers have attempted to uncover the separate effects of age, period, and cohort (APC) on a wide range of outcomes. However, rather than disentangling period effects from those attributable to age or cohort, Ryder’s approach is based on distinguishing intra-cohort trends (or life-cycle change) from inter-cohort trends (or social change), which, together, constitute comparative cohort careers. Following Ryder’s insights, in this article I show how to formally summarize population-level temporal variability on the Lexis table. In doing so, I present a number of parametric expressions representing intra- and inter-cohort trends, intra-period differences, and Ryderian comparative cohort careers. To aid the interpretation of results, I additionally introduce a suite of novel visualizations of these model-based summaries, including 2D and 3D Lexis heat maps. Crucially, the Ryderian approach developed in this article is fully identified, complementing (but not replacing) conventional approaches that rely on theoretical assumptions to parse out unique APC effects from unidentified models. This has the potential to provide a common base of knowledge in a literature often fraught with controversy. To illustrate, I analyze trends in social trust in the U.S. General Social Survey from 1972 to 2018.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Ethan Fosse: Department of Sociology, University of Toronto
E-mail: ethan.fosse@utoronto.ca

Acknowledgments: The author thanks Jessica Harris, Sebastien Parker, and Christopher Winship.

Citation: Fosse, Ethan. 2023. “Dissecting the Lexis Table: Summarizing Population-Level Temporal Variability with Age–Period–Cohort Data.” Sociological Science 10:
150-196.
Received: April 7, 2022
Accepted: May 9, 2022
Editors: Arnout van de Rijt, Richard Breen
DOI: 10.15195/v10.a5

Testing Models of Cognition and Action Using Response Conflict and Multinomial Processing Tree Models

By Parker Webservices on March 7, 2023 in Articles

Andrew Miles, Gordon Brett, Salwa Khan, and Yagana Samim

Sociological Science March 07, 2023
10.15195/v10.a4

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Dual-process perspectives have made substantial contributions to our understanding of behavior, but fundamental questions about how and when deliberate and automatic cognition shape action continue to be debated. Among these are whether automatic or deliberate cognition is ultimately in control of behavior, how often each type of cognition controls behavior in practice, and how the answers to each of these questions depends on the individual in question. To answer these questions, sociologists need methodological tools that enable them to directly test competing claims. We argue that this aim will be advanced by (a) using a particular type of data known as response conflict data and (b) analyzing those data using multinomial processing tree models. We illustrate the utility of this approach by reanalyzing three samples of data from Miles et al. (2019) on behaviors related to politics, morality, and race.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Andrew Miles: Department of Sociology, University of Toronto
E-mail: andrew.miles@utoronto.ca

Gordon Brett: Department of Sociology, University of Toronto
E-mail: gordon.brett@alum.utoronto.ca

Salwa Khan: Department of Sociology, University of Toronto
E-mail: slw.khan@mail.utoronto.ca

Yagana Samim: Department of Sociology, University of Toronto
E-mail: yagana.samim@mail.utoronto.ca

Acknowledgments: We wish to thank the reviewers and editors at Sociological Science for their helpful comments.

Citation: Miles, Andrew, Gordon Brett, Salwa Khan, and Yagana Samim. 2023. “Testing Models of Cognition and Action Using Response Conflict and Multinomial Processing Tree Models.” Sociological Science 10: 118-149.
Received: September 23, 2022
Accepted: November 22, 2022
Editors: Arnout van de Rijt, Werner Raub
DOI: 10.15195/v10.a4

Using Machine Learning to Uncover the Semantics of Concepts: How Well Do Typicality Measures Extracted from a BERT Text Classifier Match Human Judgments of Genre Typicality?

By Parker Webservices on March 3, 2023 in Articles

Gaël Le Mens, Balázs Kovács, Michael T. Hannan, Guillem Pros

Sociological Science March 3, 2023
10.15195/v10.a3

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Social scientists have long been interested in understanding the extent to which the typicalities of an object in concepts relate to its valuations by social actors. Answering this question has proven to be challenging because precise measurement requires a feature-based description of objects. Yet, such descriptions are frequently unavailable. In this article, we introduce a method to measure typicality based on text data. Our approach involves training a deep-learning text classifier based on the BERT language representation and defining the typicality of an object in a concept in terms of the categorization probability produced by the trained classifier. Model training allows for the construction of a feature space adapted to the categorization task and of a mapping between feature combination and typicality that gives more weight to feature dimensions that matter more for categorization. We validate the approach by comparing the BERT-based typicality measure of book descriptions in literary genres with average human typicality ratings. The obtained correlation is higher than 0.85. Comparisons with other typicality measures used in prior research show that our BERT-based measure better reflects human typicality judgments.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Gaël Le Mens: Department of Economics and Business, Universitat Pompeu Fabra (UPF), Barcelona School of Economics, and UPF Barcelona School of Management, Barcelona, Spain
E-mail: gael.le-mens@upf.edu

Balázs Kovács: School of Management, Yale University, New Haven, CT, USA
E-mail: balazs.kovacs@yale.edu

Michael T. Hannan: Graduate School of Business, Stanford University, Stanford, CA, USA
E-mail: hannan@stanford.edu

Guillem Pros: Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Spain
E-mail: guillem.pros@upf.edu

Acknowledgments: We are grateful to Jerker Denrell, Amir Goldberg, Greta Hsu, Thorbjørn Knudsen, Cecilia Nunes, and Phanish Puranam for discussion of ideas developed in this article and for the detailed feedback we received from them on the earlier versions. We thank conference participants at the 2021 and 2022 Nagymaros Conferences for valuable feedback and discussion. G. Le Mens and G. Pros received financial support from ERC Consolidator Grant #772268 from the European Commission. G. Le Mens also received financial support from grant PID2019-105249GBI00/ AEI/10.13039/501100011033 from the Spanish Ministerio de Ciencia, Innovacion y Universidades (MCIU) and the Agencia Estatal de Investigacion (AEI) and from the BBVA Foundation Grant G999088Q. B. Kovács was supported by Yale School of Management. M. Hannan was supported by the Stanford Graduate School of Business. Data, material, and analysis code for all analyses are available online at https://osf.io/ta273/. We encourage readers to download the shared folder and use the code to compute BERT typicality on their own data sets.

Citation: Le Mens, Gaël, Balázs Kovács, Michael T. Hannan, and Guillem Pros. 2023. “Using Machine Learning to Uncover the Semantics of Concepts: How Well Do Typicality Measures Extracted from a BERT Text Classifier Match Human Judgments of Genre Typicality?” Sociological Science 10: 82-117.
Received: September 28, 2022
Accepted: November 9, 2022
Editors: Ari Adut, Filiz Garip
DOI: 10.15195/v10.a3

Do Organizational Policies Narrow Gender Inequality? Novel Evidence from Longitudinal Employer–Employee Data

By Parker Webservices on February 28, 2023 in Articles

Florian Zimmermann, Matthias Collischon

Sociological Science February 28, 2023
10.15195/v10.a2

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Scholars have long proposed that gender inequalities in wages are narrowed by organizational policies to advance gender equality. Using cross-sectional data, scarce previous research has found an association between gender wage inequalities and these organizational policies, but it remains unclear whether this correlation represents a causal effect. We provide first evidence on this topic by using longitudinal linked employer–employee data covering almost 1,500 firms and nearly one million employee observations in Germany. We investigate whether and how organizational policies affect gender gaps using firm fixed-effects regressions. Our results show that organizational policies reduce the gender wage gap by around nine percent overall. Investigating channels, we show that this effect is entirely driven by advancing women already employed at a given firm, whereas we find no effect on firms’ composition and wages of new hires. Furthermore, we show that our findings are not driven by potential sources of bias, such as reverse causality.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Florian Zimmermann: Corresponding author. Institut für Arbeitsmarkt-und Berufsforschung (IAB), Research Department PASS; FAU Erlangen-Nuremberg
E-mail: florian.zimmermann@iab.de

Matthias Collischon: Institut für Arbeitsmarkt-und Berufsforschung (IAB), Research Department PASS
E-mail: matthias.collischon2@iab.de

Acknowledgments: We thank Ann-Christin Bächmann, Dana Müller, and Michael Oberfichtner for their helpful comments.