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In March 2024, the U.S. Office of Management and Budget (OMB) approved major changes to the ethnic and racial self-identification questions used by all federal agencies, including the U.S. Census Bureau. These modifications include merging the separate race and Hispanic ethnicity questions into a single combined question and adding a Middle Eastern and North African category. Government officials and researchers have requested evidence on how Americans might react to these changes. We conducted a survey experiment with a nationally representative sample of 7,350 adult Americans. Participants were randomly assigned to answer either the existing separate race and ethnicity questions or a combined question proposed by the OMB. We find that the combined question decreases the percentage of Americans identifying as white and as some other race. We identify the key mechanism driving these effects: Hispanics decrease their identification in other categories when a Hispanic category is available in the combined question format. This results in statistically significant decreases in key minority populations, including Afro-Latinos and indigenous Latinos.

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

René D. Flores: Department of Sociology, University of Chicago
E-mail: renedf@uchicago.edu

Edward Telles: Department of Sociology, University of California, Irvine
E-mail: e.telles@uci.edu

Ilana M. Ventura: NORC at the University of Chicago
E-mail: ventura-ilana@norc.org

Acknowledgements: We thank Maria Abascal, Constance Citro, Steven Pedlow, and Abigail Weitzman for their valuable comments and suggestions. YouGov staff provided expert data collection assistance. The Center for the Study of Race, Politics, and Society and the Neubauer Family Assistant Professors Program at the University of Chicago and the University of California at Irvine provided generous support. Flores thanks the Center for Advanced Study in the Behavioral Sciences at Stanford University for granting a year of leave. All errors are uniquely ours.

Competing Interest: The authors declare that there are no competing interests.

Reproducibility Package: A replication package containing all data and code used in this analysis is available through the Harvard Dataverse: https://doi.org/10.7910/DVN/NLDF3N.

Citation: Flores, D. René, Edward Telles, and Ilana M. Ventura. 2024. “New OMB’s Race and Ethnicity Standards Will Affect How Americans Self-Identify.” Sociological Science 11: 1147-1169.
Received: August 4, 2024
Accepted: October 21, 2024
Editors: Arnout van de Rijt, Vida Maralani
DOI: 10.15195/v11.a42

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

By Parker Webservices 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

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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.

This 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.

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

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

By Parker Webservices on December 3, 2024 in Articles

Paul Starr, Christina Pao

Sociological Science December 3, 2024
10.15195/v11.a40

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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.

This 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

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

By Parker Webservices on November 26, 2024 in Articles

Mana Nakagawa, Christine Min Wotipka, Elizabeth Buckner

Sociological Science November 12, 2024
10.15195/v11.a39

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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.

This 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

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

By Parker Webservices 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

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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.

This 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.

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

Gender Segregation and Decision-Making in Undergraduate Course-Taking

By Parker Webservices on November 8, 2024 in Articles

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

Sociological Science November 8, 2024
10.15195/v11.a37

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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.

This 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.

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

Social Status and the Moral Acceptance of Artificial Intelligence

By Parker Webservices on October 29, 2024 in Articles

Patrick Schenk, Vanessa A. Müller, Luca Keiser

Sociological Science October 29, 2024
10.15195/v11.a36

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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.

This 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).

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

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

By Parker Webservices on October 18, 2024 in Articles

Stephan Dochow-Sondershaus

Sociological Science October 18, 2024
10.15195/v11.a35

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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.

This 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.

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

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

By Parker Webservices on October 7, 2024 in Articles

Michael J. Rosenfeld

Sociological Science October 7, 2024
10.15195/v11.a34

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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.

This 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.

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

Life-Course Transitions and Political Orientations

By Parker Webservices on September 27, 2024 in Articles

Turgut Keskintürk

Sociological Science September 27, 2024
10.15195/v11.a33

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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.

This 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.