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The Diffusion and Reach of (Mis)Information on Facebook During the U.S. 2020 Election

By on December 11, 2024 in Articles

Sandra González-Bailón, David Lazer, Pablo Barberá, William Godel, Hunt Allcott, Taylor Brown, Adriana Crespo-Tenorio, Deen Freelon, Matthew Gentzkow, Andrew M. Guess, Shanto Iyengar, Young Mie Kim, Neil Malhotra, Devra Moehler, Brendan Nyhan, Jennifer Pan, Carlos Velasco Rivera, Jaime Settle, Emily Thorson, Rebekah Tromble, Arjun Wilkins, Magdalena Wojcieszak, Chad Kiewiet de Jonge, Annie Franco, Winter Mason, Natalie Jomini Stroud, Joshua A. Tucker

Sociological Science December 11, 2024
10.15195/v11.a41

Abstract

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Social media creates the possibility for rapid, viral spread of content, but how many posts actually reach millions? And is misinformation special in how it propagates? We answer these questions by analyzing the virality of and exposure to information on Facebook during the U.S. 2020 presidential election. We examine the diffusion trees of the approximately 1 B posts that were re-shared at least once by U.S.-based adults from July 1, 2020, to February 1, 2021. We differentiate misinformation from non-misinformation posts to show that (1) misinformation diffused more slowly, relying on a small number of active users that spread misinformation via long chains of peer-to-peer diffusion that reached millions; non-misinformation spread primarily through one-to-many affordances (mainly, Pages); (2) the relative importance of peer-to-peer spread for misinformation was likely due to an enforcement gap in content moderation policies designed to target mostly Pages and Groups; and (3) periods of aggressive content moderation proximate to the election coincide with dramatic drops in the spread and reach of misinformation and (to a lesser extent) political content.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Sandra González-Bailón: lead author with control rights; Annenberg School for Communication, University of Pennsylvania
E-mail: sandra.gonzalez.bailon@asc.upenn.edu

David Lazer: lead author with control rights; Network Science Institute, Northeastern University
E-mail: d.lazer@northeastern.edu

Pablo Barberá: lead Meta author; Meta
E-mail: us2020research@meta.com

William Godel: lead Meta author; Meta
E-mail: us2020research@meta.com

Hunt Allcott: Environmental and Energy Policy Analysis Center, Stanford University
E-mail: allcott@stanford.edu

Taylor Brown: Meta
E-mail: us2020research@meta.com

Adriana Crespo-Tenorio: Meta
E-mail: us2020research@meta.com

Deen Freelon: Annenberg School for Communication, University of Pennsylvania
E-mail: dfreelon@upenn.edu

Matthew Gentzkow: Department of Economics, Stanford University
E-mail: gentzkow@stanford.edu

Andrew M. Guess: Department of Politics and School of Public and International Affairs, Princeton University
E-mail: aguess@princeton.edu

Shanto Iyengar: Department of Political Science, Stanford University
E-mail: siyengar@stanford.edu

Young Mie Kim: School of Journalism and Mass Communication, University of Wisconsin-Madison
E-mail: ymkim5@wisc.edu

Neil Malhotra: Graduate School of Business, Stanford University
E-mail: neilm@stanford.edu

Devra Moehler: Meta
E-mail: us2020research@meta.com

Brendan Nyhan: Department of Government, Dartmouth College
E-mail: nyhan@dartmouth.edu

Jennifer Pan: Department of Communication, Stanford University
E-mail: jp1@stanford.edu

Carlos Velasco Rivera: Meta
E-mail: us2020research@meta.com

Jaime Settle: Department of Government, William & Mary
E-mail: jsettle@wm.edu

Emily Thorson: Department of Political Science, Syracuse University
E-mail: ethorson@gmail.com

Rebekah Tromble: School of Media and Public Affairs and Institute for Data, Democracy, and Politics, The George Washington University
E-mail: rtromble@email.gwu.edu

Arjun Wilkins: Meta
E-mail: us2020research@meta.com

Magdalena Wojcieszak: Department of Communication, University of California, Davis Center for Excellence in Social Science, University of Warsaw
E-mail: mwojcieszak@ucdavis.edu

Chad Kiewiet de Jonge: Meta research lead; Meta
E-mail: us2020research@meta.com

Annie Franco: Meta research lead; Meta
E-mail: us2020research@meta.com

Winter Mason: Meta research lead; Meta
E-mail: us2020research@meta.com

Natalie Jomini Stroud: co-last author and academic research lead; Moody College of Communication and Center for Media Engagement, University of Texas at Austin
E-mail: tstroud@austin.utexas.edu

Joshua A. Tucker: co-last author and academic research lead; Wilf Family Department of Politics and Center for Social Media and Politics, New York University
E-mail: joshua.tucker@nyu.edu

Acknowledgements: The Facebook Open Research and Transparency (FORT) team provided substantial support in executing the overall project. We are grateful for support on various aspects of project management from Chaya Nayak, Sadaf Zahedi, Lama Ahmad, Akshay Bhalla, Clarice Chan, Andrew Gruen, Bennet Hillenbrand, Pamela McLeod, and Dáire Rice; engineering and research management from Da Li and Itamar Rosenn; engineering from Yuxi Chen, Shiyang Chen, Tegan Lohman, Robert Pyke, and Yixin Wan; data engineering from Suchi Chintha, John Cronin, Devanshu Desai, Vikas Janardhanan, Yann Kiraly, Xinyi Liu, Anastasiia Molchanov, Sandesh Pellakuru, Akshay Tiwari, Chen Xie, and Beixian Xiong; data science and research from Hannah Connolly-Sporing; academic partnerships from Rachel Mersey, Michael Zoorob, Lauren Harrison, Simone Aisiks, Yair Rubinstein, and Cindy Qiao; privacy and legal assessment from Kamila Benzina, Frank Fatigato, John Hassett, Subodh Iyengar, Payman Mohassel, Ali Muzaffar, Ananth Raghunathan and Annie Sun; and content design from Caroline Bernard, Jeanne Breneman, Denise Leto, and Melanie Jennings. NORC at the University of Chicago partnered with Meta on this project to conduct the fieldwork with the survey participants. We are particularly grateful for the partnership of NORC Principal Investigator J.M. Dennis and NORC Project Director Margrethe Montgomery.

Supplemental Materials

Reproducibility Package: Deidentified data and analysis code from this study are deposited in the Social Media Archive at ICPSR, part of the University of Michigan Institute for Social Research. The data are available for university IRB-approved research on elections or to validate the findings of this study. ICPSR will receive and vet all applications for data access. Access through the ICPSR Archive ensures that the data and code are used only for the purposes for which they were created and collected. The code would also be more difficult to navigate separately from the data, which is why both are housed in the same space. Website: https://socialmediaarchive.org/collection/US2020.

  • Citation: González-Bailón, Sandra, David Lazer, Pablo Barberá et al. 2024. “The Diffusion and Reach of (Mis)Information on Facebook During the U.S. 2020 Election.” Sociological Science 11: 1124-1146.
  • Received: September 9, 2024
  • Accepted: October 24, 2024
  • Editors: Arnout van de Rijt, Cristobal Young
  • DOI: 10.15195/v11.a41


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The Multiracial Complication: The 2020 Census and the Fictitious Multiracial Boom

By on December 3, 2024 in Articles

Paul Starr, Christina Pao

Sociological Science December 3, 2024
10.15195/v11.a40

Abstract

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The Census Bureau set off reports of a “multiracial boom” when it announced that, according to the 2020 census, multiracial people accounted for 10.2 percent of the U.S. population. Only the year before, the bureau’s American Community Survey had estimated their share as 3.4 percent. We provide evidence that the multiracial boom was largely a statistical illusion resulting from methodological changes that confounded ancestry with identity and mistakenly equated national origin with race. Under a new algorithm, respondents were auto-recoded as multiracial if, after marking a single race, they listed an “origin” that the algorithm did not recognize as falling within that race. However, origins and identity are not the same; confounding the two did not improve racial statistics. The fictitious multiracial boom highlights the power of official statistics in framing public and social-science understanding and the need to keep ancestry and identity distinct in both theory and empirical practice.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Paul Starr: Sociology Department, Princeton University
E-mail: starr@princeton.edu

Christina Pao: Sociology Department, Princeton University
E-mail: christina.pao@princeton.edu

Acknowledgements: Presentations by Ricardo Lowe and colleagues helped inform the empirical strategy in our article. We also thank participants in the May 2024 Conference of the American Association for Public Opinion Research for their responses to our research.

Reproducibility Package: R code for replication is available on the Open Science Framework (OSF), https://osf.io/8ebup/?view_only=67a953b996684d128c9384d4841ed1c5. Data are available from IPUMS USA (Ruggles et al. 2024): https://usa.ipums.org/usa/index.shtml

  • Citation: Starr, Paul, and Christina Pao. 2024. “The Multiracial Complication: The 2020 Census and the Fictitious Multiracial Boom.” Sociological Science 11: 1107-1123.
  • Received: September 17, 2024
  • Accepted: October 21, 2024
  • Editors: Ari Adut, Michael Rosenfeld
  • DOI: 10.15195/v11.a40


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Opportunities for Faculty Tenure at Globally Ranked Universities: Cross-National Differences by Gender, Fields, and Tenure Status

By on November 26, 2024 in Articles

Mana Nakagawa, Christine Min Wotipka, Elizabeth Buckner

Sociological Science November 12, 2024
10.15195/v11.a39

Abstract

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Drawing on a unique data set of almost 12,000 faculty members from 52 globally ranked universities in four fields (sociology, biology, history, and engineering), this study describes and explains gender differences in tenure among faculty across 13 countries. In our sample, women comprise roughly one-third of all faculty and only 23 percent of tenured faculty, with significant variation across fields and countries. Findings from a series of multilevel regression analyses suggest support for a gender filter argument: women are less likely to be tenured overall and in every field. Opportunities for tenure also matter. In countries with very low- and high-tenure rates, women are much less likely to be tenured relative to men than in countries with pathways both into and upward in academia.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Mana Nakagawa: Global DEI & People Development, Meta
E-mail: mananakagawa@alumni.stanford.edu

Christine Min Wotipka: Graduate School of Education, Stanford University
E-mail: cwotipka@stanford.edu

Elizabeth Buckner: Ontario Institute for Studies in Education, University of Toronto
E-mail: elizabeth.buckner@utoronto.ca

Acknowledgements: We wish to thank Francisco O. Ramirez, JohnW. Meyer, Woody Powell, Eric Bettinger, Shelley Correll, Evan Schofer, Lisa Yiu, and the members of the Stanford Comparative Workshop and the Clayman Institute for Gender Research at Stanford University for their helpful feedback and guidance. We appreciate the research and editorial assistance provided by Nozomi Nakajima, Cassandra Hsinyu Lin, Isabela Freire Rietmeijer, and Juetzinia Kazmer-Murillo. An earlier version of this article was presented at the Annual Meeting of the Comparative and International Education Society in 2019. The first author received funding from the Institute of Education Sciences through predoctoral training grant #R305B090016 and the Clayman Institute for Gender Research Graduate Dissertation Fellowship.

Reproducibility Package: A replication package with all original data and codes is available at https://doi.org/10.25740/yj064dj4349.

  • Citation: Nakagawa, Mana, Christine Min Wotipka, and Elizabeth Buckner. 2024. “Opportunities for Faculty Tenure at Globally Ranked Universities: Cross-National Differences by Gender, Fields, and Tenure Status.” Sociological Science 11: 1084-1106.
  • Received: July 26, 2024
  • Accepted: October 21, 2024
  • Editors: Ari Adut, Nan Dirk de Graaf
  • DOI: 10.15195/v11.a39


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Some Birds Have Mixed Feathers: Bringing the Multiracial Population into the Study of Race Homophily

By on November 12, 2024 in Articles

David R. Schaefer, Sara I. Villalta, Victoria Vezaldenos, Adriana J. Umaña-Taylor

Sociological Science November 12, 2024
10.15195/v11.a38

Abstract

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Research on race homophily in the United States has yet to meaningfully include the growing multiracial population. The present study confronts this challenge by drawing upon recent conceptualizations of race as a multidimensional construct. In aligning this insight with current understandings of homophily, we identify and address several open questions about the origins of race homophily—namely regarding the possibility of peer influence on racial identity and network selection based on multiple facets of race. Data are from 3,036 youth in two large U.S. high schools with sizable proportions of mixed-race students. Using a stochastic actor-oriented model, we find that students choose friends based on similarity across multiple dimensions of racial identity and that peer influence operates to reinforce multiracial youths’ racial self-classification rather than to induce change. This points to a system where race homophily arises through multiple selection mechanisms and is reinforced by pressure toward conformity.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

David R. Schaefer: Department of Sociology, University of California, Irvine
E-mail: drschaef@uci.edu

Sara I. Villalta: Department of Sociology, Loyola Marymount University
E-mail: sara.villalta@lmu.edu

Victoria Vezaldenos: Combined Program in Education and Psychology, University of Michigan
E-mail: toriavez@umich.edu

Adriana J. Umaña-Taylor: Graduate School of Education, Harvard University
E-mail: adriana_umana-taylor@gse.harvard.edu

Acknowledgements: This research was supported by grants from the National Science Foundation (SES No. 1918162, PI: Schaefer; BCS No. 1625277, PI: Umaña-Taylor). We express our appreciation to Jessica Collett, Deja Goodwin, Andrew Penner, and Aliya Saperstein for helpful comments on an earlier draft.

Supplemental Materials

Reproducibility Package: A replication package is available at: https://doi.org/10.7910/DVN/VOK1UI.

  • Citation: Schaefer, R. David, Sara I. Villalta, Victoria Vezaldenos, and Adriana J. Umaña-Taylor. 2024. “Some Birds Have Mixed Feathers: Bringing the Multiracial Population into the Study of Race Homophily.” Sociological Science 11: 1046-1083.
  • Received: April 30, 2024
  • Accepted: August 28, 2024
  • Editors: Ari Adut, Andreas Wimmer
  • DOI: 10.15195/v11.a38


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Gender Segregation and Decision-Making in Undergraduate Course-Taking

By on November 8, 2024 in Articles

Marissa E. Thompson, Tobias Dalberg, Elizabeth E. Bruch

Sociological Science November 8, 2024
10.15195/v11.a37

Abstract

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Gender segregation across fields of study is a persistent problem in higher education. Although a large body of literature has illustrated both gendered patterns in major choice as well as overall gender segregation across academic majors, comparatively less attention has been paid to an important building block for gender inequality: college courses. In this study, we examine the process of how students choose courses and the implications for gender segregation. Drawing on a unique data set that includes individual-level consideration and choice data from an entire cohort of university students choosing their first college courses, we examine both gender segregation at the college course level as well as the extent to which individual decision-making processes are themselves gendered. We find that course gender composition serves as a screener at the consideration stage, which suggests that gender segregation in decision-making emerges at the outset of the choice process. Once a subset of considered options has been established, final choices are much less influenced by course gender compositions. Furthermore, we find that courses are much more gender-segregated, on average, than majors themselves, illustrating that segregation is occurring at a more microlevel than commonly studied.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Marissa E. Thompson: Department of Sociology, Columbia University
E-mail: marissa.thompson@columbia.edu

Tobias Dalberg: Department of Education, Uppsala University
E-mail: tobias.dalberg@edu.uu.se

Elizabeth E. Bruch: Department of Sociology, University of Michigan and the Santa Fe Institute
E-mail: ebruch@umich.edu

Acknowledgements: This research was supported in part by the Institute of Education Sciences through grants R305B140009 (to Stanford University) and R305B170015 (to the University of Michigan). Results, information, and opinions solely represent the analysis, information, and opinions of the authors and are not endorsed by, or reflect the views or positions of, the grantors. In addition, we would like to thank Tom DiPrete, Sonia Giebel, Monique Harrison, Kaylee Matheny, Michelle Niemann, Mitchell Stevens, and members of the Curricular Structure & Choice Lab (at the University of Michigan) and the Pathways Network for generous feedback and comments on earlier versions of this project. We would also like to acknowledge and thank Sorathan (Tum) Chaturapruek for his work in developing the course selection tool used in this study and Andreas Paepcke for his generous help with procuring and structuring the data.

Supplemental Materials

Reproducibility Package: Code for this study is available through the Open Science Framework: https://osf.io/ya3t8/. Due to the fact that the data includes potentially identifiable information, as well as to protect the anonymous case institution and students involved, the underlying data and the identity of the case university cannot be made public. Author access to the data was facilitated through the Pathways Network, which has an institutional relationship and data use agreement for access to the data. Questions about data access and requirements should be directed to Pathways Director, Professor Mitchell Stevens (stevens4@stanford.edu) at the Stanford University Graduate School of Education. Access to the data is at the discretion of the anonymous case university on a case-by-case basis, and data may not be available to external researchers. For more details on the specific course search platform leveraged in this study, see Chaturapruek et al. (2021).

  • Citation: Thompson, E. Marissa, Tobias Dalberg, Elizabeth E. Bruch. 2024. “Gender Segregation and Decision-Making in Undergraduate Course-Taking.” Sociological Science 11: 1017-1045.
  • Received: August 10, 2024
  • Accepted: October 6, 2024
  • Editors: Ari Adut, Maria Abascal
  • DOI: 10.15195/v11.a37


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Social Status and the Moral Acceptance of Artificial Intelligence

By on October 29, 2024 in Articles

Patrick Schenk, Vanessa A. Müller, Luca Keiser

Sociological Science October 29, 2024
10.15195/v11.a36

Abstract

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The morality of artificial intelligence (AI) has become a contentious topic in academic and public debates. We argue that AI’s moral acceptance depends not only on its ability to accomplish a task in line with moral norms but also on the social status attributed to AI. Agent type (AI vs. computer program vs. human), gender, and organizational membership impact moral permissibility. In a factorial survey experiment, 578 participants rated the moral acceptability of agents performing a task (e.g., cancer diagnostics). We find that using AI is judged less morally acceptable than employing human agents. AI used in high-status organizations is judged more morally acceptable than in low-status organizations. No differences were found between computer programs and AI. Neither anthropomorphic nor gender framing had an effect. Thus, human agents in high-status organizations receive a moral surplus purely based on their structural position in a cultural status hierarchy regardless of their actual performance.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Patrick Schenk: Department of Sociology, University of Lucerne
E-mail: patrick.schenk@unilu.ch

Vanessa A. Müller: Department of Sociology, University of Lucerne
E-mail: vanessa.mueller2@unilu.ch

Luca Keiser: gfs.bern
E-mail: luca.keiser@gfsbern.ch

Acknowledgements: We thank Gabriel Abend, Michael Sauder, the editor of Sociological Science, and an anonymous reviewer for their valuable comments. Earlier versions of this article were presented at the Congress of the Academy of Sociology in Bern, Switzerland, and the Conference of the European Sociological Association in Porto, Portugal.

Funding: This study was funded by the Swiss National Science Foundation (grant number 100017_200750/1).

Supplemental Materials

Reproducibility Package: A reproduction package with data, codebook, and statistical code is available through the following link: https://doi.org/10.5281/zenodo.13850548.

  • Citation: Schenk, Patrick, Vanessa A. Müller, Luca Keiser. 2024. “Social Status and the Moral Acceptance of Artificial Intelligence.” Sociological Science 11: 989-1016.
  • Received: August 20, 2024
  • Accepted: September 29, 2024
  • Editors: Ari Adut, Stephen Vaisey
  • DOI: 10.15195/v11.a36


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Hunkering Down or Catching Up? No Long-Term Effect of Ethnic Minority Share on Neighborhood Contacts

By on October 18, 2024 in Articles

Stephan Dochow-Sondershaus

Sociological Science October 18, 2024
10.15195/v11.a35

Abstract

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This study reexamines the relationship between the coexistence of distinct ethno-cultural groups and social connectedness. Although previous research suggests a negative association between neighborhood-level ethnic diversity or ethnic minority shares and individual integration, alternative theoretical perspectives propose that integration can occur equally well in neighborhoods with distinct ethnic groups but may require more time. Moreover, the causal nature of the observed negative relationship is unclear due to potential confounding biases related to neighborhood selection. To address these issues, this study presents a framework for estimating the longitudinal effects of neighborhood ethnic composition on social ties with neighbors. The objective is to estimate the differences in neighborly contacts between individuals in low- and high-minority share neighborhoods, under a counterfactual scenario where all households stay in their neighborhood for the same period. The findings challenge previous research by showing that the ethnic composition does not impact the quality of neighborly contacts. In addition, residing in a neighborhood for five years significantly enhances social connectivity, regardless of ethnic composition. These results suggest that reduced cohesion in areas with higher minority presence may be due to other factors such as socioeconomic disadvantage and housing instability.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Stephan Dochow-Sondershaus: Department of Sociology, University of Copenhagen
E-mail: stdo@soc.ku.dk

Acknowledgements: I would like to express my gratitude to Michael Windzio, Merlin Schaeffer, Celine Teney, and Jan Goebel for their invaluable support and feedback on this article. I am also thankful to the Bremen International Graduate School of Social Sciences for providing the necessary resources to complete this work. In addition, I appreciate the valuable feedback from participants at the 2021 Conference of the German Academy of Sociology, the 2022 German Socio-Economic Panel User Conference, and the 2024 Conference of the Nordic Sociological Association. Finally, I am grateful to Philipp Kaminsky, Christine Kurka, and Michaela Engelmann at the DIW in Berlin for providing a supportive work environment and for their uplifting spirit.

Supplemental Materials

Reproducibility Package: Stata and R code for replication is available on the author’s Open Science Framework page (https://doi.org/10.17605/OSF.IO/RCFN4). The datasets were made available by the German Socio-Economic Panel (SOEP) Study at the German Institute for Economic Research (DIW) in Berlin. The SOEP data can be requested after signing a data assignment contract (https://www.diw.de/en/diw_01.c.601584.en/data_access.html). For more information, visit https://doi.org/10.5684/soep.core.v36eu. The Microm-SOEP dataset for neighborhood data is provided by and accessible to researchers at the German Institute for Economic Research (DIW) in Berlin.

  • Citation: Dochow-Sondershaus, Stephan. 2024. “Hunkering Down or Catching Up? No Long-Term Effect of Ethnic Minority Share on Neighborhood Contacts.” Sociological Science 11: 965-988.
  • Received: April 10, 2024
  • Accepted: September 21, 2024
  • Editors: Arnout van de Rijt, Maria Abascal
  • DOI: 10.15195/v11.a35


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The Surprising Decline of Workplace Sexual Harassment Incidence in the U.S. Federal Workforce

By on October 7, 2024 in Articles

Michael J. Rosenfeld

Sociological Science October 7, 2024
10.15195/v11.a34

Abstract

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U.S. Merit Systems Protection Board (USMSPB) surveys document a decline of more than 50 percent between 1987 and 2016 in the percentage of women working for the federal government who have been sexually harassed (narrowly or broadly defined) in the prior two years. This decline has been underappreciated due to the infrequency of USMSPB surveys and the delayed release of the USMSPB report based on the 2016 survey. The decline in workplace sexual harassment of women has taken place across all federal agencies and at all workplace gender balances. While, in 1987, there was a strong positive correlation between male predominance in the workplace and women’s report of sexual harassment, this association was greatly diminished by 2016. The formerly substantial gender divide in attitudes toward sexual harassment was also mostly diminished by 2016. By extrapolating the USMSPB surveys of federal workers to the entire U.S. workforce, I estimate that 4.8 million U.S. women were harassed at work in 2016 (using a narrow definition of harassment) and 7.6 million U.S. women were harassed at work in 1987 when the female workforce was substantially smaller. More than 700 women were sexually harassed at work in the United States in 2016 for every sexual harassment complaint filed with the Equal Employment Opportunity Commission. The observed decline in sexual harassment has implications for theories about law and social change.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Michael J. Rosenfeld: Stanford University
E-mail: mrosenfe@stanford.edu

Acknowledgements: The idea of this article started from discussions with research assistant Camilla Camargo about a research project comparing the history of coworker dating with workplace sexual harassment. Research assistant Jasleen Gosal excavated some obscure aspects of the history of federal government agencies training programs with respect to sexual harassment. Thanks to the staff at the Merit Systems Protection Board who answered many questions about surveys and data. The following people gave feedback on earlier drafts of the article: Hannah Tessler, Alisa Feldman, Michaela Simmons, Amy Hontalas, Kimberly Higuera, Justine Tinkler, and the Stanford Graduate Family Workshop. A previous version of these results was presented at the Population Association of America Conference in 2024.

Funding: None.

Supplemental Materials

Reproducibility Package: All original data, codes, and analysis are available at OpenICPSR, https://doi.org/10.3886/E209051V1.

  • Citation: Rosenfeld, J. Michael. 2024. “The Surprising Decline of Workplace Sexual Harassment Incidence in the U.S. Federal Workforce.” Sociological Science 11: 934-964.
  • Received: July 24, 2024
  • Accepted: September 13, 2024
  • Editors: Ari Adut, Kristen Schilt
  • DOI: 10.15195/v11.a34


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Life-Course Transitions and Political Orientations

By on September 27, 2024 in Articles

Turgut Keskintürk

Sociological Science September 27, 2024
10.15195/v11.a33

Abstract

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Do life-course transitions in adulthood shape political orientations? One framework suggests that life events expose people to new information, allowing actors to assess their political beliefs and preferences in response to these social experiences. An alternative framework suggests that the link between one’s life-course position and personal politics may be ambiguous, and early experiences should be more informative for political orientations. In this article, I use four household surveys across three countries and 40 items on political beliefs and preferences to test whether lifecourse transitions change one’s political orientations. In doing this, I employ difference-in-differences models to identify the effects of six life transitions across family and work domains on a wide variety of propositional survey items. I find that life-course transitions have no substantive influence on political orientations, and the general findings are not sensitive to differences in political interest or the age at which individuals experience these life events.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Turgut Keskintürk: Department of Sociology, Duke University
E-mail: turgut.keskinturk@duke.edu

Acknowledgements: I thank Stephen Vaisey, Craig Rawlings, and Christopher Wildeman for their extensive feedback on different versions of this manuscript, and Andrés Castro Araújo, Kevin Kiley, and the participants of the Worldview Lab at the Kenan Institute for Ethics at Duke University for their thoughtful comments on the project.

Supplemental Materials

Reproducibility Package: The code to reproduce the full set of analyses and instructions on how to access the household surveys are provided at https://osf.io/hu3yj/.

  • Citation: Keskintürk, Turgut 2024. “Life-Course Transitions and Political Orientations” Sociological Science 11: 907-933.
  • Received: July 3, 2024
  • Accepted: September 10, 2024
  • Editors: Arnout van de Rijt, Jeremy Freese
  • DOI: 10.15195/v11.a33


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Factorial Survey Experiments to Predict Real-World Behavior: A Cautionary Tale from Hiring Studies

By on September 24, 2024 in Articles

Andrea G. Forster, Martin Neugebauer

Sociological Science September 24, 2024
10.15195/v11.a32

Abstract

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Factorial surveys (FSs) are increasingly used to predict real-world decisions. However, there is a paucity of research assessing whether these predictions are valid and, if so, under what conditions. In this preregistered study, we sent out N = 3,002 applications to job vacancies in Germany and measured real-world responses. Eight weeks later, we presented nearly identical applicant profiles to the same employers as a part of an FS. To explore the conditions under which FSs provide valid behavioral predictions, we varied the topic sensitivity and tested whether behavioral predictions were more successful after filtering out respondents who gave socially desirable answers or did not exert sufficient effort when answering FS vignettes. Across conditions, the FS results did not correspond well with the real-world benchmark. We conclude that researchers must exercise caution when using FSs to study (hiring) behavior.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Andrea G. Forster: Utrecht University, Heidelberglaan 8, 3584 CS Utrecht, The Netherlands
E-mail: a.g.forster@uu.nl

Martin Neugebauer: Karlsruhe University of Education, Bismarckstr. 10, 76133 Karlsruhe, Germany
E-mail: martin.neugebauer@ph-karlsruhe.de

Acknowledgements: Both authors contributed equally to this study. We would like to thank Lukas Zielinski, Stefan Gunzelmann, Tim Skroblien, Pablo Neitzsch, and Franz Geiger for their help with the design of the experiments and the collection of the data. Furthermore, we would like to thank Katrin Auspurg, Annabell Daniel, Tamara Gutfleisch, Knut Petzold, and Katharina Stückradt as well as 16 professional experts (recruiters and job councelors) for their feedback on our experimental design and materials. Finally, we would like to thank the participants of ECSR 2022, ACES 2022, DGS 2022, the ISOL paper seminar, the Research Colloquium Sociology (University of Bern), and the Research Colloquium Analytical Sociology (LMU Munich) for their feedback on earlier versions of this article. This research was funded by the German Federal Ministry of Education grant number 16PX21011.

Supplemental Materials

Reproducibility Package: The code and data needed to reproduce the analyses are available at the Open Science Framework: https://osf.io/x2tcp/.

  • Citation: Forster, G. Andrea and Martin Neugebauer. 2024. “Factorial Survey Experiments to Predict Real-World Behavior: A Cautionary Tale from Hiring Studies.” Sociological Science 11: 886-906.
  • Received: April 26, 2024
  • Accepted: August 23, 2024
  • Editors: Arnout van de Rijt, Stephen Vaisey
  • DOI: 10.15195/v11.a32


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Decomposing Heterogeneity in Inequality of Educational Opportunities: Family Income and Academic Performance in Brazilian Higher Education

By on September 10, 2024 in Articles

Adriano S. Senkevics, Rogério J. Barbosa, Flavio Carvalhaes, Carlos A. Costa Ribeiro

Sociological Science September 10, 2024
10.15195/v11.a31

Abstract

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Access to higher education depends on the interaction between social origins and academic performance: background resources boost academic skills; but even when controlling for performance, privileged students are more likely to make ambitious choices and further transitions. Recent literature has shown that inequality in educational choices is heterogeneous across countries. However, it is still not well understood how different institutional designs within countries may affect the workings of those effects and how they can strengthen or weaken the inequality of educational opportunities. Using high-quality register data from the Brazilian higher education system, our work contributes to this understanding by investigating how SES and performance interact and drive students’ choice between three different tracks: not entering higher education, entering the private system, or entering the public system. We developed a strategy to encompass multinomial choices and decompose the inequalities into primary and secondary effects. Using the Shapley Value decomposition strategy, we correct an intrinsic asymmetry that biased previous results. Our findings suggest affluent students enjoy dual advantages: high exam performance amplifies access to public universities (indirect effect) and family resources offset subpar performance, ensuring private university access (direct effect). We found no signs of multiplicative advantages.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Adriano S. Senkevics: National Institute for Educational Studies and Research, Ministry of Education of Brazil
E-mail: adriano.senkevics@alumni.usp.br

Rogério J. Barbosa: Institute of Social and Political Studies, State University of Rio de Janeiro
E-mail: rogerio.barbosa@iesp.uerj.br

Flavio Carvalhaes: Department of Sociology, Federal University of Rio de Janeiro
E-mail: flaviocarvalhaes@gmail.com

Carlos A. Costa Ribeiro: Institute of Social and Political Studies, State University of Rio de Janeiro
E-mail: carloscr@iesp.uerj.br

Acknowledgements: We extend our gratitude to the editors and reviewers for their insightful suggestions. We are thankful to Marcelo Medeiros, Thomas DiPrete, and Scott Davies, as well as the School of International and Public Affairs and the Institute of Latin American Studies at Columbia University and the Ontario Institute for Studies in Education at the University of Toronto for their hospitality during the authors’ visit. Special thanks go to the National Institute for Educational Studies and Research (INEP) for granting access to the restricted microdata. We are also appreciative of the financial support provided by Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro – FAPERJ (grants E-26/201.343/2021 and 010.002639/2019); Conselho Nacional de Desenvolvimento Tecnológico – CNPq (grant 400786/2016-8); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – CAPES (grant 88887.368106/2019-00); and Pro-Ciência from the State University of Rio de Janeiro – UERJ.

Supplemental Materials

Reproducibility Package: The replication package is available at https://osf.io/pru32/; however, due to the use of restricted microdata from INEP’s Protected Data Access Service, it does not enable the replication of the full results as the data set is subject to specific limitations.

  • Citation: Senkevics, Adriano S., Rogério J. Barbosa, Flavio Carvalhaes, and Carlos A. Costa Ribeiro. 2024. “Decomposing Heterogeneity in Inequality of Educational Opportunities: Family Income and Academic Performance in Brazilian Higher Education.” Sociological Science 11: 854-885.
  • Received: November 26, 2023
  • Accepted: April 19, 2024
  • Editors: Arnout van de Rijt, Jeremy Freese
  • DOI: 10.15195/v11.a31


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Prosociality Beyond In-Group Boundaries: A Lab-in-the-Field Experiment on Selection and Intergroup Interactions in a Multiethnic European Metropolis

By on September 6, 2024 in Articles

Delia Baldassarri, Johanna Gereke, Max Schaub

Sociological Science September 6, 2024
10.15195/v11.a30

Abstract

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How does prosocial behavior extend beyond in-group boundaries in multiethnic societies? The differentiation of Western societies presents an opportunity to understand the tension between societal pressures that push people outside the comfort zones of their familiar networks to constructively interact with unknown diverse others and the tendency toward homophily and in-group favoritism. We introduce a three-step model of out-group exposure that includes macrostructural conditions for intergroup encounters and microlevel dynamics of intergroup selection and interaction. Using lab-in-the-field experiments with a large representative sample of Italian natives and immigrants from the multiethnic city of Milan, we find that, when pushed to interact with non-coethnics, Italians generally treat them similarly to how they treat coethnics and value signs of social and market integration. However, when given the opportunity to select their interaction partners, Italians favor coethnics over immigrants. Taken together, these results help reconcile classical findings concerning the positive effects of intergroup contact with evidence documenting the persistence of out-group discrimination in selection processes.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Delia Baldassarri: Julius Silver, Roslyn S. Silver, and Enid Silver Winslow Professor, Department of Sociology, New York University and Senior Researcher, Dondena Center, Bocconi University
E-mail: delia.b@nyu.edu

Johanna Gereke: Postdoctoral Research Fellow, Mannheim Centre for European Social Research, University of Mannheim
E-mail: johanna.gereke@uni-mannheim.de

Max Schaub: Assistant Professor, Department of Political Science, University of Hamburg
E-mail: max.schaub@uni-hamburg.de

Acknowledgements: We are grateful to Maria Abascal, Shannon Rieger, Merlin Schaeffer, Nan Zhang, and Diego Gambetta as well as several seminar participants for their valuable comments. Funding from ERC Starting Grant 639284. Direct correspondence to Delia Baldassarri, 383 Lafayette Street, Department of Sociology, New York University, New York, NY, 10012 (delia.b@nyu.edu).

Supplemental Materials

Reproducibility Package: Data and code for replication are available at OSF https://osf.io/3rzgj.

  • Citation: Baldassarri, Delia, Johanna Gereke, and Max Schaub. 2024. “Prosociality Beyond In-Group Boundaries: A Lab-in-the-Field Experiment on Selection and Intergroup Interactions in a Multiethnic European Metropolis.” Sociological Science 11: 815-853.
  • Received: June 14, 2024
  • Accepted: August 5, 2024
  • Editors: Arnout van de Rijt, Ray Reagans
  • DOI: 10.15195/v11.a30


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Housework as a Woman's Job? What Looks Like Gender Ideologies Could Also Be Stereotypes

By on September 3, 2024 in Articles

Katrin Auspurg, Sabine Düval

Sociological Science September 3, 2024
10.15195/v11.a29

Abstract

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We question the validity of standard measures of gender ideology. When asked about “men” and “women” in general, respondents may imagine women (men) with lower (higher) labor market resources. Therefore, standard measures may conflate gender ideologies (injunctive norms) with stereotypical beliefs (descriptive norms). We test this hypothesis with an experiment in the German family panel pairfam: ∼1,200 respondents rated the appropriate division of housework in ∼3,700 hypothetical couples. By gradually adding information about labor market resources, we were able to override respondents’ stereotypical beliefs. We find that with more information, even “traditional” respondents support egalitarian housework arrangements. The main difference between “traditional” and “egalitarian” respondents is not in their ideologies (as previously thought), but in their interpretation of vague items. This leads us to conclude that standard measures overestimate traditional gender ideologies. Our study also illustrates how varying the amount of information can help identify respondents’ implicit beliefs.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Katrin Auspurg: Department of Sociology, LMU Munich
E-mail: katrin.auspurg@lmu.de

Sabine Düval: German Youth Institute (DJI)
E-mail: dueval@dji.de

Acknowledgements: We thank the participants of the Conference of the European Survey Research Association (ESRA) in 2019, the Annual Meeting of the American Sociological Association (ASA) in 2019, the pairfam User Conference in 2019, and the seminar on “Analytical Sociology: Theory and Empirical Applications” at at the Venice International University in 2018 for helpful suggestions. We are also grateful for comments on an earlier version we received from Josef Brüderl. We used data from the German Family Panel pairfam, coordinated by Josef Brüderl, Sonja Drobniè, Karsten Hank, Johannes Huinink, Bernhard Nauck, Franz J. Neyer, and Sabine Walper. From 2004 to 2022, pairfam was funded as priority program and long-term project by the German Research Foundation (DFG). Sabine Düval worked on the manuscript and data analysis mainly during her PhD studies at the LMU Munich. Part of this work was done while Katrin Auspurg was a Visiting Fellow at the European University Institute (EUI) in Florence.

Supplemental Materials

Reproducibility Package: The data we used (pairfam data release 10.0) can be accessed here: https://www.pairfam.de/en/data/data-access. Our replication files (Stata dofiles and data on response times not included in the pairfam release) are available on the following OSF platform: https://osf.io/3fqw9 (Auspurg and Düval 2024).

  • Citation: Auspurg, Katrin, and Sabine Düval. 2024. “Housework as a Woman’s Job?: What Looks Like Gender Ideologies Could Also Be Stereotypes.” Sociological Science 11: 789-814.
  • Received: September 21, 2023
  • Accepted: February 22, 2024
  • Editors: Arnout van de Rijt, Maria Abascal
  • DOI: 10.15195/v11.a29


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Examining Attitudes toward Asians throughout the COVID-19 Pandemic with Repeated Cross-Sectional Survey Experiments

By on August 30, 2024 in Articles

Yao Lu, Neeraj Kaushal, Xiaoning Huang, S. Michael Gaddis, Ariela Schachter

Sociological Science August 30, 2024
10.15195/v11.a28

Abstract

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This study examines how COVID-induced and general attitudes toward Asians have changed over the course of the pandemic using nationally representative survey experiments in 2020 and 2022. First, we measured COVID-induced anti-Asian attitudes as the effect of a treatment reminding respondents of the pandemic on whether respondents would be willing to live or work with someone who is East or South Asian. The results suggest that the COVID-19 treatment worsened attitudes toward East and South Asians in the social domain and toward East Asians in the economic domain in 2020, but not in 2022. Second, we measured change in general attitudes toward Asians by comparing the control group responses in 2020 and 2022. The results demonstrate that, over the same period, general attitudes toward Asians have not improved despite growing attention toward anti-Asian biases. This finding underscores the persistence of general negative attitudes toward Asians beyond the immediate context of the pandemic and the ongoing imperative to actively address deeply ingrained biases against Asians.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Yao Lu: Department of Sociology, Columbia University
E-mail: yl2479@columbia.edu

Neeraj Kaushal: School of Social Work, Columbia University
E-mail: nk464@columbia.edu

Xiaoning Huang: Feinberg School of Medicine, Northwestern University
E-mail: jack.huang@northwestern.edu

S. Michael Gaddis: Research and Policy Partnerships, NWEA
E-mail: michael.gaddis@nwea.org

Ariela Schachter: Washington University in St. Louis
E-mail: ariela@wustl.edu

Acknowledgements: We thank Tiffany Huang, Jennifer Lee, and participants of the Experimental Design Workshop at Columbia University, and the Asia and Asian America Working Group at University of Pennsylvania for their helpful comments. This research was funded by the National Institute of Child Health and Human Development (1R21HD105183), the Columbia Population Research Center, the Institute for Social and Economic Research and Policy, the Center for Pandemic Research, and the Weatherhead East Asian Institute at Columbia University.

Supplemental Materials

Replication Package: Study materials can be found at the Open Science Framework https://osf.io/a6ewy/.

  • Citation: Lu, Yao, Neeraj Kaushal, Xiaoning Huang, S. Michael Gaddis, and Ariela Schachter. 2024. “Examining Attitudes toward Asians throughout the COVID-19 Pandemic with Repeated Cross-Sectional Survey Experiments.” Sociological Science 11:777-788.
  • Received: October 27, 2023
  • Accepted: March 16, 2024
  • Editors: Ari Adut, Maria Abascal
  • DOI: 10.15195/v11.a28


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Teacher Bias in Assessments by Student Ascribed Status: A Factorial Experiment on Discrimination in Education

By on August 27, 2024 in Articles

Carlos J. Gil-Hernández, Irene Pañeda-Fernández, Leire Salazar, Jonatan Castaño Muñoz

Sociological Science August 27, 2024
10.15195/v11.a27

Abstract

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Teachers are the evaluators of academic merit. Identifying if their assessments are fair or biased by student-ascribed status is critical for equal opportunity but empirically challenging, with mixed previous findings. We test status characteristics beliefs, statistical discrimination, and cultural capital theories with a pre-registered factorial experiment on a large sample of Spanish pre-service teachers (n = 1, 717). This design causally identifies, net of ability, the impact of student-ascribed characteristics on teacher short- and long-term assessments, improving prior studies’ theory testing, confounding, and power. Findings unveil teacher bias in an essay grading task favoring girls and highbrow cultural capital, aligning with status characteristics and cultural capital theories. Results on teachers’ long-term expectations indicate statistical discrimination against boys, migrant origin, and working-class students under uncertain information. Unexpectedly, ethnic discrimination changes from teachers favoring native origin in long-term expectations to migrant origin in short-term evaluations, suggesting compensatory grading. We discuss the complex roots of discrimination in teacher assessments as an educational (in)equality mechanism.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Carlos J. Gil-Hernández∗: Department of Statistics, Computer Science, Applications, University of Florence
∗Corresponding author, E-mail: carlos.gil@unifi.it

Irene Pañeda-Fernández: WZB Berlin Social Science Center
E-mail: irene.paneda@wzb.eu

Leire Salazar: Institute for Public Goods and Policies, Consejo Superior de Investigaciones Científicas
E-mail: leire.salazar@cchs.csic.es

Jonatan Castaño Muñoz: Departamento de Didática y Organización Educativa, Universidad de Sevilla
E-mail: jcastanno@us.es

Acknowledgements: This project has been funded through the JRC Centre for Advanced Studies and the project Social Classes in the Digital Age (DIGCLASS). Jonatan Castaño Muñoz acknowledges the support of a) the ‘Ramón y Cajal’ grant RYC2020-030157 funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”; and b) University of Seville “VI University research plan” (VI plan propio de investigación). We thank Lilian Weikert, William Foley, Zbigniew Karpiñski, David Martínez de Lafuente, Alberto López, and Mario Spiezio for their valuable feedback and support. We also thank the participants at the following venues where we presented earlier versions of the article: the ‘Experiments on Social Inequality’ Workshop at Sciences Po-LIEPP, the ‘Colloquium of the Migration and Diversity Department’ at the WZB Berlin Social Science Centre, the ECSR Thematic Conference ‘Effort and Social Inequality’ and ‘2024 IC3JM Conference’ at Carlos III-Juan March Institute of Social Sciences, the FES ‘Inequality and Social Stratification Committee Workshop’ in Oviedo, the ‘Education and Social Inequalities Seminar’ at University of Sevilla, the ‘CLIC Seminar Series’ at the European University Institute, the SISEC conference in Cagliari, and the FES National Congress in Sevilla.

Supplemental Materials

Replication Package: Data and replication code are publicly accessible at the GitHub repository: https://zenodo.org/doi/10.5281/zenodo.12666534. The hypotheses and research design were publicly pre-registered with a pre-analysis plan (PAP) before data collection and analysis at the Open Science Foundation repository: https://doi.org/10.17605/OSF.IO/DZB3S.

  • Citation: J. Gil-Hernández, Carlos, Irene Pañeda-Fernández, Leire Salazar, Jonatan Castaño Muñoz, 2024. “Teacher Bias in Assessments by Student Ascribed Status: A Factorial Experiment on Discrimination in Education” Sociological Science 11: 743-776.
  • Received: January 6, 2024
  • Accepted: July 9, 2024
  • Editors: Ari Adut, Stephen Vaisey
  • DOI: 10.15195/v11.a27


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Algorithmic Risk Scoring and Welfare State Contact Among US Children

By on August 23, 2024 in Articles

Martin Eiermann

Sociological Science August 23, 2024
10.15195/v11.a26

Abstract

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Predictive Risk Modeling (PRM) tools are widely used by governing institutions, yet research on their effects has yielded divergent findings with low external validity. This study examines how such tools influence child welfare governance, using a quasi-experimental design and data from more than one million maltreatment investigations in 121 US counties. It demonstrates that the adoption of PRM tools reduced maltreatment confirmations among Hispanic and Black children but increased such confirmations among high-risk and low-SES children. PRM tools did not reduce the likelihood of subsequent maltreatment confirmations; and effects were heterogeneous across counties. These findings demonstrate that the use of PRM tools can reduce the incidence of state interventions among historically over-represented minorities while increasing it among poor children more generally. However, they also illustrate that the impact of such tools depends on local contexts and that technological innovations do not meaningfully address chronic state interventions in family life that often characterize the lives of vulnerable children.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Martin Eiermann: Department of Sociology, Duke University
E-mail: martin.eiermann@duke.edu.

Acknowledgements: The author thanks Olivia Kim and Henry Zapata for invaluable research assistance, and thanks Garrett Baker, Alexandra Gibbons, Sarah Sernaker, and Christopher Wildeman for constructive feedback.

Replication Package: Access to restricted-use NCANDS data can be requested through the National Data Archive on Child Abuse and Neglect (NDACAN). Other data and replication code are available at: https://osf.io/dq3xp/.

  • Citation: Eiermann, Martin. 2024. “Algorithmic Risk Scoring and Welfare State Contact Among US Children” Sociological Science 11: 707-742.
  • Received: May 20, 2024
  • Accepted: July 2, 2024
  • Editors: Arnout van de Rijt, Maria Abascal
  • DOI: 10.15195/v11.a26


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Status Ambiguity and Multiplicity in the Selection of NBA Awards

By on August 20, 2024 in Articles

Peter McMahan, Eran Shor

Sociological Science August 20, 2024
10.15195/v11.a25

Abstract

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Sociologists of culture have long noted that contrasting cultural frames can lead to status ambiguity and status multiplicity. We explore these phenomena in the domain of professional sports by first replicating and then extending and challenging recently published findings on selections for the National Basketball Association (NBA) All-Star game. Relying on a large data set that includes more than 10,000 player–years, we show that accounting for better-justified performance measures reduces but does not nullify the effects of status cumulative advantage on All-Star selections. However, when replacing All-Star selections with a less ambiguous measure (selections to All-NBA teams), we no longer find evidence of decoupling between player performance and award nomination. From this we conclude that cumulative status advantage only affects selection when voters view factors other than statistical performance as legitimate, perhaps even desired, selection criteria. These findings have relevance for our understanding of status evaluations beyond professional sports, including in domains as diverse as the film industry, the performing arts, literature, politics, and the sciences.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Peter McMahan: Department of Sociology, McGill University
Email: peter.mcmahan@mcgill.ca

Eran Shor: Department of Sociology, McGill University
Email: eran.shor@mcgill.ca

Supplemental Material

Replication Package: Reproduction package is available at https://github.com/mcmahanp/nba_status.

  • Citation: McMahan, Peter, and Eran Shor. 2024. “Status ambiguity and multiplicity in the selection of NBA awards.” Sociological Science 11: 680-706.
  • Received: January 5, 2024
  • Accepted: June 2, 2024
  • Editors: Ari Adut, Ray Reagans
  • DOI: 10.15195/v11.a25


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Unemployment Insurance and the Family: Heterogeneous Effects of Benefit Generosity on Reemployment and Economic Precarity

By on August 16, 2024 in Articles

Ursina Kuhn, Debra Hevenstone, Leen Vandecasteele, Samin Sepahniya, Dorian Kessler

Sociological Science August 16, 2024
10.15195/v11.a24

Abstract

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We investigate how unemployment insurance generosity impacts reemployment and economic precarity by family type. With Swiss longitudinal administrative data and a regression discontinuity design using potential benefit duration, we examine differences between single households and primary and secondary or equal earners, as well as differences by gender and presence of children. Less generous unemployment insurance (shorter potential benefit duration) speeds up reemployment for all family types during the period with benefit cuts whereas longer-term effects are stronger for single households, secondary and equal earners, and those without children. Economic precarity increases for singles, single-parents, and primary earners during the period with lower benefits though there are no long-term effects. We argue that those with higher financial responsibility (i.e., primary earners or those with children) face pressure to find jobs irrespective of benefit generosity whereas those with lower financial responsibility (i.e., secondary or equal earners and those without children) have more capacity to react.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Ursina Kuhn: Social Work, Bern University of Applied Sciences. Swiss Centre of Expertise in the Social Sciences (FORS)
E-mail: ursina.kuhn@fors.unil.ch

Debra Hevenstone: SocialWork, Bern University of Applied Sciences
E-mail: debra.hevenstone@bfh.ch

Leen Vandecasteele: Swiss Centre of Expertise in Life Course Research (LIVES), Faculty of Social and Political Sciences, University of Lausanne
E-mail: leen.vandecasteele@unil.ch

Samin Sepahniya: Social Work and Health, University of Applied Sciences and Arts Northwestern Switzerland
E-mail: samin.sepahniya@fhnw.ch

Dorian Kessler: Social Work, Bern University of Applied Sciences
E-mail: dorian.kessler@bfh.ch

Acknowledgements: This article was written as part of the project Family Models and Unemployment (grant number 176371) funded by the Swiss National Science Foundation (SNSF). We would like to acknowledge the SNSF project “Coupled Inequalities. Trends and Welfare State Differences in the Role of Partner’s Socio-Economic Resources for Employment Careers” (grant number 100017_182406) and the Swiss Centre of Expertise in Life Course Research (LIVES) for fruitful collaboration and exchange. We thank the anonymous reviewers for their valuable comments which helped to clarify the paper. We also thank the SNSF for open access funding of this article.

Supplemental Material

Replication Package: The code for data analysis, data description, and instructions on how data can be requested for replication is provided on SwissUbase. https://doi.org/10.25597/tm2k-jf98

  • Citation: Kuhn, Ursina, Debra Hevenstone, Leen Vandecasteele, Samin Sepahniya and Dorian Kessler. 2024. “Unemployment Insurance and the Family: Heterogeneous Effects of Benefit Generosity on Reemployment and Economic Precarity.” Sociological Science 11: 649-679.
  • Received: July 4, 2024
  • Accepted: March 18, 2024
  • Editors: Ari Adut, Vida Maralani
  • DOI: 10.15195/v11.a24


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