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Men’s Labor-Market Decline and the Rising Correlation between Spouses’ Earnings in the United States

By on August 20, 2026 in Articles

Yifan Shen

Sociological Science August 20, 2026
10.15195/v13.a39

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This study examines the role of deterioration in men’s labor-market conditions in explaining the rising correlation between spouses’ earnings in the United States. Prior research treats the growth of married women’s employment as the primary driver of this trend, leaving men’s declining economic position largely unexamined. Drawing on U.S. Census and American Community Survey data from 1960 to 2019 covering 722 commuting zones, I apply two-way fixed-effects models and a shift–share instrumental-variable design that exploits local variation in exposure to Chinese import competition across male- and female-intensive industries. Both approaches indicate that deterioration in men’s labor-market conditions raises the spousal earnings correlation within local labor markets, with the increase concentrated among couples with children. The pattern is class-stratified: where men’s conditions worsen, mothers’ work hours rise among those married to higher-earning men but little among those married to lower-earning men. This rising correlation thus reflects not only the growth of wives’ employment but also the unequally distributed capacity of families to adapt to men’s labor-market decline—an adaptation that itself amplifies inequality between households.

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Yifan Shen: Division of Social Science, The Hong Kong University of Science and Technology.
E-mail: yifanshen@ust.hk


Supplemental Materials

Reproducibility Package: The replication package contains the Stata code that reproduces every table and figure from the IPUMS census/ACS microdata, all third-party input data, and documentation describing how to download the IPUMS microdata (samples and variables) required as input data. It is available at https://doi.org/10.3886/E251260V1


  • Citation: Shen, Yifan. 2026. “Men’s Labor-Market Decline and the Rising Correlation between Spouses’ Earnings in the United States” Sociological Science 13:1018-1045.
  • Received: May 13, 2026
  • Accepted: July 21, 2026
  • Editors: Arnout van de Rijt, Michael Rosenfeld
  • DOI: 10.15195/v13.a39


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Access to Higher Education and Support for Meritocracy: Effort, Skill, and Education as Components of Merit

By on August 18, 2026 in Articles

Hye Won Kwon, Jani Erola

Sociological Science August 18, 2026
10.15195/v13.a38

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Prior research has emphasized perceptions of effort-based meritocracy (i.e., the descriptive belief that hard work leads to success), noting a rising trend in meritocratic beliefs across countries. The current study proposes focusing on three components of merit—effort, skill, and education — and on a less-examined form of meritocratic beliefs: support for meritocracy (i.e., the prescriptive belief that society should distribute rewards based on merit). Analyzing the 2009 International Social Survey Programme data, this study demonstrates the role of higher education in shaping heterogeneity in support for meritocracy. College-educated individuals seem to reject effort-based meritocracy while strongly supporting skill- and education-based meritocracy. In addition, the gap between the college-educated and the non-college-educated in supporting education-based meritocracy is larger in countries with broader access to higher education. These findings suggest that people may refer to different dimensions of meritocracy when supporting or disapproving “meritocracy,” calling for refined policy interventions to reduce social inequalities.

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Hye Won Kwon: Department of Sociology, Ewha Womans University.
E-mail: hwkwonsoc@ewha.ac.kr.

Jani Erola: INVEST Research Flagship Center, University of Turku.
E-mail: jani.erola@utu.fi.

Acknowledgments: This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2024S1A5A8020262). We gratefully acknowledge the Research Council of Finland flagship funding (INVEST, decision number 320162) and Academy Professor’s funding (STRATEQ, decision number 371741). Direct Correspondence to Hye Won Kwon (E-mail: hwkwonsoc@ewha.ac.kr).


Supplemental Materials

Reproducibility Package: A reproducibility package that includes codes and macro-level data is available at https://github.com/INVEST-flagship/Kwon-Erola-2026. The ISSP 2009 survey data cannot be uploaded to publicly available locations, because the data can be accessed only after the user registration through the GESIS portal. The ISSP 2009 data are available via the GESIS portal: https://www.gesis.org/en/issp/data-and-documentation/
social-inequality/2009.


  • Citation: Kwon, Hye Won, Jani Erola. 2026. “Access to Higher Education and Support for Meritocracy: Effort, Skill, and Education as Components of Merit” Sociological Science 13: 997-1017.
  • Received: August 5, 2025
  • Accepted: July 5, 2026
  • Editors: Ari Adut, Nan Dirk de Graaf
  • DOI: 10.15195/v13.a38


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Decoupling Inequality and Stratification in the American Wealth Distribution, 1989–2022

By on August 11, 2026 in Articles

Jake Burchard, Lisa A. Keister

Sociological Science August 11, 2026
10.15195/v13.a37

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Wealth inequality in the United States has grown substantially in recent decades, yet it remains unclear whether wealth has become more stratified along socially salient, group-based lines. Insofar as intragroup solidarities and intergroup antagonisms depend on the extent to which groups are arranged into minimally overlapping, hierarchically ordered strata within the wealth distribution, stratification is sociologically important independently of inequality. Using Survey of Consumer Finances data from 1989 to 2022 and a nonparametric, rank-based stratification metric, we examine trends in wealth stratification across multiple axes of social difference, including racialized group membership, age, education, employment-based class, and marital status. We find that stratification declined along several dimensions, with education being the main exception. Decomposition analyses show that these dimensions differ not only by the level of stratification they exhibit over time but also by where in the distribution stratification is primarily generated and by the relative contributions of housing and nonhousing wealth. These findings underscore the importance of wealth composition and distributional location in shaping stratification and encourage scholars to explore how wealth accumulation may harden or weaken group boundaries.

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


Jake Burchard: Department of Sociology, Duke University.
E-mail: jake.burchard@duke.edu.

Lisa A. Keister: Department of Sociology, Duke University; Sanford School of Public Policy, Duke University.
E-mail: lkeister@duke.edu.

Acknowledgments: We thank the editors and two anonymous external reviewers for their comments and suggestions. We also thank Jianyu Hong for research assistance.

Funding: This research received support from the Population Dynamics Research Infrastructure Program award to the Duke Population Research Center (P2C HD065563) at Duke University by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.


Supplemental Materials

Reproducibility Package: Data and code to reproduce all results reported in the paper are available at: https://gitlab.oit.duke.edu/jkb83/decoupling-inequality-and-stratification-replication-package.


  • Citation: Burchard, Jake, and Lisa A. Keister. 2026. “Decoupling Inequality and Stratification in the American Wealth Distribution, 1989–2022” Sociological Science 13: 971-996.
  • Received: April 27, 2026
  • Accepted: June 23, 2026
  • Editors: Ari Adut, Ray Reagans
  • DOI: 10.15195/v13.a37


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Quantities of Interest for Interactions and the Pitfalls of Assuming Linear Treatment Effects

By on August 6, 2026 in Articles

Josep Serrano-Serrat

Sociological Science August 6, 2026
10.15195/v13.a36

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Although quantitative social sciences often rely on estimating models in which treatment effects vary across groups, researchers rarely specify which causal quantity they aim to estimate or justify their empirical modeling choices. This article makes two contributions. First, it clarifies the distinct quantities of interest when studying interactions: comparisons at different treatment intensities (the difference in conditional average marginal effects) and comparisons at similar intensities (what I term the average interactive partial effect). When treatment effects are nonlinear and treatment distributions differ across groups, these quantities diverge. Second, the article assesses estimation strategies to estimate these quantities. It demonstrates that linear interaction models produce biased estimates of either quantity when treatment effects are nonlinear and explores two alternatives that explicitly accommodate such nonlinearities. This article is accompanied by an R package that implements these approaches. Through simulations, stylized examples, and an empirical application, the article shows that explicitly defining the quantity of interest and selecting appropriate models is essential for valid interaction analysis.

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


Josep Serrano-Serrat: Institute for Public Goods and Policies (IPP), Spanish National Research Council (CSIC).
E-mail: j.serrano.serrat@csic.es.

Acknowledgments: An earlier version of this article was presented at the 2024 Annual Meeting of the American Political Science Association in Philadelphia and the 2025 Annual Conference of the Swiss Political Science Association in Genève. I am grateful to Cesc Amat, Ignacio Jurado, Patrick W. Kraft, Sergi Martínez, and Marco Steenbergen for their valuable comments and suggestions, which substantially improved the article. I also thank Felix Elwert, as Editor of Sociological Methods & Research, Arnout van de Rijt, as Editor of Sociological Science, and an anonymous reviewer for their insightful feedback and constructive guidance throughout the revision process.


Supplemental Materials

Reproducibility Package: All code necessary to replicate this study is available in an OSF repository at https://osf.io/8tx6g/.


  • Citation: Serrano-Serrat, Josep. 2026. “Quantities of Interest for Interactions and the Pitfalls of Assuming Linear Treatment Effects” Sociological Science 13:945-970.
  • Received: March 11, 2026
  • Accepted: June 23, 2026
  • Editors: Arnout van de Rijt, Kristian B. Karlson
  • DOI: 10.15195/v13.a36


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Bending the Heckman Curve: Competing Declines in Learning Capacity and Skill Relevance Over the Life Course

By on August 4, 2026 in Articles

João M. Souto-Maior, Mitchell L. Stevens

Sociological Science August 4, 2026
10.15195/v13.a35

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The Heckman curve has powerfully influenced social policy by providing mathematical support for the concentration of human-capital investments early in the life course. The canonical model behind this curve derives a single relationship for aggregate human capital and does not address how return trajectories vary across skill types. We extend the canonical mathematical framework to derive skill-specific return trajectories, incorporating two key parameters governing declines in (a) human capacity to learn and (b) skill relevance over the life course. Our microfoundation model implies that the shape of return trajectories depends on the relative magnitudes of these two declines, indicating a trade-off: although early investments may be more efficient due to declining human learning capacity, they risk misalignment with future labor market needs. Depending on the targeted skill, investments in adult workers might more effectively align with evolving skill content. We illustrate this result with numerical simulations using empirically plausible parameter ranges and selected skill profiles. Our work suggests that optimal investment timing may be skill-dependent, and identifies empirical questions that can better inform human-capital policy in a time of rapid technological change and lengthening lifespans.

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


João M. Souto-Maior: Stanford Center on Longevity and Graduate School of Education, Stanford University.
E-mail: joao.msoutomaior@gmail.com.

Mitchell L. Stevens: Graduate School of Education and Stanford Center on Longevity, Stanford University.
E-mail: stevens4@stanford.edu.

Acknowledgments: This paper is part of the project “Education and Learning for Longer Lives,” sponsored by the Stanford Center on Longevity (SCL) in 2025–2026. We thank the SCL’s Futures Fellows and New Map of Life Postdoctoral Fellows for the contexts in which this work germinated. We are especially grateful to Bernardo Mackenna, Chris Heitzig, Leon Marbach, and Arik Lifschitz for written feedback, and to Matt Sigelman for valuable advice. Earlier versions of this work benefited from critical feedback (all in 2025) in Stanford’s Pathways Network Seminar and Inequality Workshop, the SCL Fellows Seminar, the Sociological Science Annual Conference, and the International Network of Analytical Sociology Conference. Any errors are our own.


Supplemental Materials

Data and code availability statement: This paper does not use external data. Full replication code for numerical simulations and figures available at: https://github.com/joaosoutomaior/competing-declines-code.


  • Citation: Souto-Maior, João M., and Mitchell L. Stevens. 2026. “Bending the Heckman Curve: Competing Declines in Learning Capacity and Skill Relevance Over the Life Course” Sociological Science 13: 915-944.
  • Received: April 9, 2026
  • Accepted: June 16, 2026
  • Editors: Stephen Vaisey, Herman van de Werfhorst
  • DOI: 10.15195/v13.a35


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Categorical Engagement and the Contingent Nature of Typicality Effects

By on July 28, 2026 in Articles

Alex Tyulyupo, Balázs Kovács

Sociological Science July 28, 2026
10.15195/v13.a34

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Market categories can favor typical members over atypical ones, yet this “categorical imperative” operates inconsistently across contexts. We argue that typicality effects depend on how evaluators engage with categories during search. Using behavioral simulation in which participants search a large database of companies for competitors, we distinguish between searches that explicitly invoke industry classifications and those using alternative methods, and measure goal-category congruence through semantic alignment between evaluators’ objectives and the categories they employ. We find that typical companies become more likely to be selected in category-based searches; other searches produce no typicality effects. Among category-based searches, goal-category congruence moderates the effect: typicality strongly predicts selection when goals and categories misalign but becomes irrelevant when they align well. These findings identify a specific microprocess through which categorical effects become contingent, offering a process-level explanation for variation documented across audiences, producer characteristics, and evaluation contexts.

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Alex Tyulyupo: Yale School of Management, Yale University.
E-mail: alex.tyulyupo@yale.edu.

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

Acknowledgments: We thank Ceclin Begbie and Robert Bartholomew for their management of the behavioral lab. We thank Maciej Workiewicz, Elisa Operti, and Stoyan Sgourev for their input. We gratefully acknowledge financial support from the Yale School of Management. We benefited from feedback received at the 2025 Nagymaros Conference and the Yale School of Management OBID seminar.


Supplemental Materials

Reproducibility Package: De-identified, model-ready data and code for reproducing all statistical tables and figures are available at (https://doi.org/10.17605/OSF.IO/6Z8RS). Raw Crunchbase records, company and venture descriptions, and participant-identifying information are not shared because of data-use and confidentiality restrictions.


  • Citation: Tyulyupo, Alex, and Kovács, Balázs. 2026. “Categorical Engagement and the Contingent Nature of Typicality Effects” Sociological Science 13:884-914.
  • Received: May 6, 2026
  • Accepted: June 23, 2026
  • Editors: Ari Adut, Clayton Childress
  • DOI: 10.15195/v13.a34


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Information Diets Are More Diverse in Attention Than in Engagement

By on July 21, 2026 in Articles

Christopher Barrie, Aybuke Atalay, Alia ElKattan

Sociological Science July 21, 2026
10.15195/v13.a33

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What political content do we pay attention to online? Diverse political information is essential for democratic competence, yet online media raises concerns about fragmented information diets. Research on selective exposure highlights how social media can foster ideological echo chambers, while other studies emphasize incidental exposure to diverse viewpoints. A critical measurement challenge is that public platform traces often observe engagement (e.g., likes or shares) more readily than lower-visibility forms of attention—i.e., what users notice or choose to read without necessarily interacting publicly. In this study, we address this gap with a social media clone platform that separately records attention and engagement. We ran the study in both the United Kingdom (once) and the United States (thrice). Across both contexts, we found that the ideology-engagement association is significantly larger than the ideology-attention association. This underscores the importance of measuring attention, rather than solely engagement, to accurately assess the diversity of online information diets.

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


Christopher Barrie: Department of Sociology, New York University.
E-mail: cb5691@nyu.edu

Aybuke Atalay: Department of Politics and International Relations, University of Edinburgh.
E-mail: aybuke.atalay@ed.ac.uk

Alia ElKattan: Department of Politics, New York University.
E-mail: alia.elkattan@nyu.edu

Acknowledgments: We thank audiences at the NYU Center for Social Media and Politics for their feedback on earlier versions of this paper. This research was supported by a British Academy/Leverhulme Small Research Grant (SRG2223 230865). OpenAI GPT-4o and GPT-5 and Anthropic Claude (Sonnet 4.5) were used for code, code review, and manuscript redrafting. The authors declare no competing interests. Corresponding author: Christopher Barrie (cb5691@nyu.edu).


Supplemental Materials

Reproducibility Package: Data, code, documentation, and replication materials necessary to re-produce the empirical and simulation results reported in this article are available at https://github.com/cjbarrie/smclone.


  • Citation: Barrie, Christopher, Aybuke Atalay, and Alia ElKattan. 2026. “Information Diets Are More Diverse in Attention Than in Engagement” Sociological Science 13: 864-883.
  • Received: April 9, 2026
  • Accepted: June 8, 2026
  • Editors: Ari Adut, Kieran Healy
  • DOI: 10.15195/v13.a33


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A Roadmap for Inequality Research: Transparency, Intersectionality, and Multiple Measures of Race

By on July 9, 2026 in Articles

Emma Williams-Baron, Aliya Saperstein

Sociological Science July 9, 2026
10.15195/v13.a32

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Most quantitative studies of U.S. inequality rely on single measures of race and do not transparently describe them. However, inconsistencies between measures can yield conclusions that differ both substantively and statistically. We ask: when faced with multiple ways to categorize respondents, how should researchers choose? We conduct intersectional analyses of five inequality outcomes, using the 1979 National Longitudinal Survey of Youth, which offers several measures of self-identification and external classification. Strikingly, we find the survey’s screener race variable, ubiquitous in prior research, is never empirically preferred based on model fit across outcomes spanning the labor market (wages, salary, and unemployment), health (depression), and education (school discipline). Instead, the top-performing measure varies by gender, outcome, and fit statistic. The range of potential researcher decisions and the absence of a clear gold-standard highlights the need for greater transparency and more thoughtful decision-making when researchers operationalize race—whether racial categorization is central to the analysis or included primarily as a control variable. To that end, we offer a roadmap of key considerations inequality researchers can consult when designing their approach.

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Emma Williams-Baron: Department of Sociology, Stanford University. E-mail: emmajwb@stanford.edu.
Aliya Saperstein: Department of Sociology, Stanford University. E-mail: asaper@stanford.edu.

Acknowledgments: We are grateful to our colleagues in the gender and inequality workshops at Stanford University for their helpful comments and suggestions, and to Steve McClaskie for responding to inquiries about the NLSY. Previous versions of this paper were presented at the 2024 American Sociological Association annual meeting and at a 2023 conference on racial inequality in education research hosted by NWEA in Portland, OR. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1656518. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.


Supplemental Materials

Reproducibility Package: Data and code for reproducing the results presented in this article are publicly
available in an Open Science Framework repository here: https://doi.org/10.17605/OSF.IO/K3RZT. Data may also be accessed through the NLSY Investigator site at: https://www.nlsinfo.org/investigator.


  • Citation: Williams-Baron, Emma, Aliya Saperstein. 2026. “A Roadmap for Inequality Research: Transparency, Intersectionality, and Multiple Measures of Race” Sociological Science 13: 825-863.
  • Received: September 20, 2025
  • Accepted: May 18, 2026
  • Editors: Arnout van de Rijt, Kristian B. Karlson
  • DOI: 10.15195/v13.a32


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Leveraging Genomic Data to Document Within-Race Attractiveness Penalties Among Black Americans

By on July 7, 2026 in Articles

Beza Taddess, Luyin Zhang, Sam Trejo

Sociological Science July 7, 2026
10.15195/v13.a31

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In recent years, scholars of racial inequality have increasingly sought to move beyond simply quantifying discrete racial disparities and instead measure social stratification as a function of continuous racialized characteristics that vary both within and between racial groups. In this article, we draw on a sample of genotyped respondents from the Add Health study and construct genetic similarity proportions, individual-level measures that correlate with racialized physical features that vary across the expansive family tree of humanity (skin tone, facial structure, hair texture, etc.). We then investigate the relationship between these proportions and interviewer-rated physical attractiveness among self-identified Black Americans (N=2,087). Our findings highlight the existence of substantial attractiveness penalties related to having higher levels of Sub-Saharan African (as opposed to European) genetic similarity.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.


Beza Taddess: Department of Sociology, Princeton University. E-mail: bt7304@princeton.edu
Luyin Zhang: Office of Population Research, Princeton University. E-mail: luyin.zhang@princeton.edu
Sam Trejo: Department of Sociology and Office of Population Research, Princeton University. E-mail: samtrejo@princeton.edu

Acknowledgments: We are grateful to Dalton Conley, Filiz Garip, Iain Mathieson, Ellis Monk, and Marissa Thompson for helpful comments. This research uses data from Add Health, funded by grant P01 HD31921 (Harris) from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), with cooperative funding from 23 other federal agencies and foundations. Add Health is currently directed by Robert A. Hummer and funded by the National Institute on Aging cooperative agreements U01 AG071448 (Hummer) and U01AG071450 (Hummer and Aiello) at the University of North Carolina at Chapel Hill. Add Health was designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill. No direct support was received from grant P01 HD31921 for this analysis. Information on obtaining Add Health data is available on the project website. Send correspondence to Sam Trejo, samtrejo@princeton.edu.

Significance Statement: This study provides new evidence on how racialized physical features shape social experiences within a single self-identified racial group. By using genetic similarity proportions—genetic ancestry measures that correlate with physical traits such as skin tone and facial structure—the authors show that Black Americans with higher levels of Sub-Saharan African genetic similarity are systematically rated as less physically attractive. These results reveal a form of racialized disadvantage that operates within racial categories and is not captured by typical survey measures and help explain why traditional surveys report relatively small Black–White attractiveness gaps (whereas real-world behavior shows much larger differences). More broadly, the study offers genetic similarity proportions as a new tool for exploring processes of racialization in contemporary society.


Supplemental Materials

Reproducibility Package: All results needed to evaluate the conclusions in the article are present in the article and/or the Supplementary Materials. All syntax files needed to replicate our main text analyses are available at the following link: https://github.com/luyin-z/attractiveness_penalties. We utilized the restricted Add Health survey and genotype data, which can be accessed by researchers via application at https://data.cpc.unc.edu/projects/2/view.


  • Citation: Taddess, Beza, Luyin Zhang, and Sam Trejo. 2026. “Leveraging Genomic Data to Document Within-Race Attractiveness Penalties Among Black Americans” Sociological Science 13: 802-824.
  • Received: March 24, 2026
  • Accepted: May 13, 2026
  • Editors: Ari Adut, Ellis Monk
  • DOI: 10.15195/v13.a31


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The Double Bind of Precarious Work: Creating Need and Undermining Support

By on July 1, 2026 in Articles

Tyler Woods, Kristen Harknett, Daniel Schneider

Sociological Science July 2, 2026
10.15195/v13.a30

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For most adults in the United States, participation in the labor force is a normative expectation and a pre-requisite for social acceptance and inclusion. Yet, the conditions of low-wage work can breed social isolation by interfering with supportive social ties at and outside of work. Drawing on survey data from The Shift Project, we examine the complex interplay between precarious working conditions and supportive social ties and illuminate a vicious cycle faced by low-wage workers. Precarious work schedule conditions are associated with reduced perceptions of support from social ties and act as a mechanism through which precarious working conditions take a toll on worker well-being. Further, those with precarious work schedules are less likely to benefit from the buffering effect of social support that attenuates the negative consequences of unstable and unpredictable schedules on well-being. Our findings demonstrate negative externalities of precarious working conditions for social support and reveal the double bind of precarious work: schedule instability undermines workers’ social support while simultaneously heightening the need for it.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.


Tyler Woods: Harvard Kennedy School. E-mail: tyler.woods@bain.com.
Kristen Harknett: University of California, Berkeley, Department of Sociology. E-mail: kharknett@berkeley.edu.
Daniel Schneider: Harvard Kennedy School. E-mail: dschneider@hks.harvard.edu.

Acknowledgments: We gratefully acknowledge support from the National Institute on Aging (Grant Nos. R01AG066898 and R56AG081273), the National Institute for Occupational Safety and Health (Grant No. U19OH012293), the Bill and Melinda Gates Foundation (Grant Nos. INV-002665 and INV-016942), the Robert Wood Johnson Foundation (Award No. 74528), and the W.T. Grant Foundation (Grant No. 188043). The findings and conclusions contained within are those of the authors and do not necessarily reflect the positions or policies of these foundations. The authors received excellent research support from Kevin Bruey, Connor Williams, and Alessandra Soto.


Supplemental Materials

Reproducibility Package: Information on accessing the administrative register data and all code used in the analysis is available at: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/
OEGXOW.


  • Citation: Woods, Tyler, Kristen Harknett, and Daniel Schneider. 2026. “The Double Bind of Precarious Work: Creating Need and Undermining Support” Sociological Science 13: 772-801.
  • Received: January 5, 2026
  • Accepted: April 28, 2026
  • Editors: Stephen Vaisey, Michael Rosenfeld
  • DOI: 10.15195/v13.a30


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