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How Do (Human) Child Welfare Workers Respond to Machine-Generated Risk Scores?

By on January 6, 2026 in Articles

Martin Eiermann, Maria Fitzpatrick, Katharine Sadowski, Christopher Wildeman

Sociological Science January 6, 2026
10.15195/v13.a1

Abstract

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Algorithmic risk scoring tools have been widely incorporated into governmental decision making, yet little is known about how human decision makers interact with machine-generated risk scores at the street level. We examined such human–machine interactions in the child welfare system, a high-stakes setting where caseworkers ascertain whether government interventions in family life are warranted. Using novel data—verbatim transcripts of caseworker discussions—we found that decision makers: (1) disregarded scores in the middle of the distribution while paying attention to extremely high or low risk scores and (2) rationalized divergences between human decisions and machine-generated scores by highlighting the algorithm’s overemphasis on historical data and specific risk factors and its lack of contextual knowledge. This meant that caseworkers were unlikely to modify their decisions so that they aligned with risk scores. However, we did not find evidence of principled resistance to algorithmic tools. Our findings advance research on such tools by specifying how human perceptions of the utility and limitations of novel technologies shape discretionary decision making by state officials; and they help to explain their uneven and potentially modest impact on the bureaucratic management of social vulnerability.
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Martin Eiermann: Department of Sociology, University of Wisconsin-Madison.
E-mail: meiermann@wisc.edu.
Maria Fitzpatrick: Books School of Public Policy, Cornell University; National Bureau of Economic Research.
E-mail: maria.d.fitzpatrick@cornell.edu.
Katharine Sadowski: Graduate School of Education, Stanford University.
E-mail: ksadow@stanford.edu.
Christopher Wildeman: Department of Sociology, Duke University; Sanford School of Public Policy, Duke University; ROCKWOOL Foundation Research Unit.
E-mail: christopher.wildeman@duke.edu.

Acknowledgments: The authors are grateful to Ruby Richards and Nicole Adams for feedback on earlier drafts of this manuscript and the Douglas County Department of Human Services for providing data throughout this project.

No supplemental materials.

Reproducibility Package: The terms of our Data Use Agreement with the Douglas County Department of Human Services (DCDHS) legally prohibit us from sharing the original data, which are temporarily stored on a secure Cornell University research server, cannot be shared externally, and must be destroyed at the end of the agreement period. These restrictions reflect the presence of highly sensitive child welfare data in verbatim transcripts of caseworker discussions. All analysis code and documentation of qualitative coding workflows are publicly available at OSF. Researchers with questions about Douglas County Decision Aide (DCDA) data that were generated during the randomized controlled trial may contact: Ruby Richards, Director of Human Services, Douglas County (303-688-4825).

  • Citation: Eiermann, Martin, Maria Fitzpatrick, Katharine Sadowski, and Christopher Wildeman. 2025. “How Do (Human) Child Welfare Workers Re- spond to Machine-Generated Risk Scores?” Sociological Science 13: 1-21.
  • Received: September 3, 2025
  • Accepted: November 14, 2025
  • Editors: Ari Adut, Jeremy Freese
  • DOI: 10.15195/v13.a1

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How Robust Are Country Rankings in Educational Mobility?

By on December 11, 2025 in Articles

Ely Strömberg, Per Engzell

Sociological Science December 11, 2025
10.15195/v12.a36

Abstract

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We investigate the impact of analytical choices on country comparisons in intergenerational educational mobility using a multiverse approach. A literature survey gives rise to 2,880 plausible ways of measuring educational mobility, which we apply to European Social Survey data from 16 countries. Although some countries consistently appear at the top or bottom of the mobility rankings, most show substantial variation. Beyond our methodological contribution, we report two substantive findings. First, some countries often characterized as low-mobility emerge as matching or surpassing the egalitarian Nordic countries, reinforcing the view that wider mobility differences cannot be attributed solely to the education system but must be sought elsewhere, such as the labor market. Second, the choice of parameter—such as regression coefficients, correlations, or categorical measures—is the single most influential factor that shifts country rankings. As different parameters carry distinct theoretical meanings, researchers should treat parameter choice not merely as a robustness check but as an opportunity to test and refine competing theories.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Ely Strömberg: Department of Sociology, University of Amsterdam.
E-mail: e.o.stromberg@uva.nl
Per Engzell: UCL Social Research Institute, University College London; Swedish Institute for Social Research, Stockholm University.
E-mail: p.engzell@ucl.ac.uk

Acknowledgments: Per Engzell acknowledges funding from the European Research Coun- cil, grant no. 101165962 (MaMo). Earlier versions of this work were presented at the 2023 Spring Meeting of the ISA Research Committee 28 on Social Stratification and Mobility (RC28) in Paris, the 2024 Conference of the European Consortium for Sociolog- ical Research (ECSR) in Barcelona, and in seminars at the Swedish Institute for Social Research (SOFI) and the Amsterdam Institute for Social Science Research (AISSR). For comments that improved the manuscript, we thank Editor-in-Chief Arnout van de Rijt, Deputy Editor Kristian Karlson, two external reviewers, as well as Adam Altmejd, Krzysztof Czarnecki, Harry Ganzeboom, Jan Helmdag, Mike Hout, Linda Kridahl, Liliya Leopold, Silke Schneider, Edvin Syk, Max Thaning, Jens-Peter Thomsen, An- dreas Videbæk Jensen, Kim Weeden, Herman van de Werfhorst, and Daniel Wilhelm. Any errors remain our own.

Supplemental Materials

Reproducibility Package: The microdata underlying our analyses are available to download from the European Social Survey. Code necessary to reproduce the results is available at: https://doi.org/10.17605/OSF.IO/VCDSX

  • Citation: Strömberg, Ely, Per Engzell. 2025. “How Robust Are Country Rankings in Educational Mobility?” Sociological Science 12: 891-922.
  • Received: July 9, 2025
  • Accepted: October 13, 2025
  • Editors: Arnout van de Rijt, Kristian B. Karlson
  • DOI: 10.15195/v12.a36

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The Causal Impact of Segregation on a Disparity: A Gap-Closing Approach

By on December 6, 2025 in Articles

Ian Lundberg

Sociological Science December 9, 2025
10.15195/v12.a35

Abstract

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Segregation—whether across schools, neighborhoods, or occupations—is regularly invoked as a cause of social and economic disparities. However, segregation is a complicated causal treatment: what do we mean when we appeal to a world in which segregation does not exist? One could take societal contexts as the unit of analysis and compare across societies with differing levels of segregation. In practice, it is more common for studies of segregation to take persons or households as the unit of analysis within a single societal context, focusing on what would happen if particular individuals were counterfactually assigned to social positions in a more equitable way. Taking this latter framework, this article shows how to study segregation as a cause. The first step is to theorize a counterfactual assignment rule: what would it mean to assign people to social positions equitably? The second step is to identify the causal effect of those social positions and simulate counterfactual outcomes. The third step is to interpret results as the impact of a unit-level (rather than society-level) intervention. A running example and empirical analysis illustrates the approach by studying the causal effect of occupational segregation on a racial health gap.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Ian Lundberg: Department of Sociology, UCLA.
E-mail: ianlundberg.org, ianlundberg@ucla.edu.

Acknowledgments: For helpful discussions and feedback relevant to this project, I thank Brandon Stewart, Matthew Salganik, Dalton Conley, Sara McLanahan, Rebecca Johnson, Gillian Slee, and participants in presentations at the Princeton Department of Sociology, the Cornell Center for the Study of Inequality, and the UCSF Department of Social and Behavioral Sciences, as well as the editor and anonymous reviewers. The author benefited from facilities and resources provided by the California Center for Population Research at UCLA (CCPR), which receives core support (P2C-HD041022) from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child Health & Human Development or the National Institutes of Health.

Supplemental Materials

Reproducibility Package: doi.org/10.7910/DVN/TB5Q4N.

  • Citation: Lundberg, Ian. 2025. “The Causal Impact of Segregation on a Disparity: A Gap-Closing Approach” Sociological Science 12: 871-890.
  • Received: July 15, 2025
  • Accepted: August 31, 2025
  • Editors: Arnout van de Rijt, Maria Abascal
  • DOI: 10.15195/v12.a35

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What You Need to Know When Estimating Monthly Impact Functions: Comment on Hudde and Jacob, “There’s More in the Data!”

By on December 4, 2025 in Articles

Josef Brüderl, Ansgar Hudde, Marita Jacob

Sociological Science December 4, 2025
10.15195/v12.a34

Abstract

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In life course research, it is common practice to analyze the effects of life events on outcomes. This is usually done by estimating “impact functions.” To date, most studies have estimated yearly impact functions. However, Hudde and Jacob (2023) (hereafter H&J) pointed out that most panel data sets include information on the month of events. Consequently, they proposed exploiting this information by estimating monthly impact functions. In this adversarial collaboration, we address two issues regarding H&J’s work. First, H&J did not provide sufficient guidance on how to estimate monthly impact functions. We will provide a step-by-step description of how to do so. Second, the procedure H&J proposed for smoothing monthly estimates produces confidence intervals (CIs) that are likely too narrow. This can lead to misleading conclusions. Therefore, we suggest using more appropriate bootstrapped CIs.
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Josef Brüderl: Department of Sociology, LMU Munich. E-mail: bruederl@lmu.de
Ansgar Hudde: Department of Sociology and Social Psychology, University of Cologne.
E-mail: hudde@wiso.uni-koeln.de
Marita Jacob: Department of Sociology and Social Psychology, University of Cologne.
E-mail: marita.jacob@uni-koeln.de

Acknowledgments: We thank Katrin Auspurg for her helpful comments. This article uses data from the German Family Panel pairfam, coordinated by Josef Brüderl, Sonja Drobniˇc, Karsten Hank, Johannes Huinink, Bernhard Nauck, Franz J. Neyer, and Sabine Walper. From 2004 to 2022, pairfam was funded as a priority program and a long-term project by the German Research Foundation (DFG).


Reproducibility Package: Stata replication code is available on the Open Science Framework (OSF), https://osf.io/kx9ne/ (file: “Monthly Impact Functions-Replication File.zip”). The replication file includes the prepared pairfam data that we used for all of our analyses. If you would like to reproduce our data preparation (also included in the replication file), you can order the pairfam data at https://www.pairfam.de/en/data/data-access/.

  • Citation: Brüderl, Josef, Ansgar Hudde, Marita Jacob. 2025. “What You Need to Know When Estimating Monthly Impact Functions: Comment on Hudde and Jacob, “There’s More in the Data!”” Sociological Science 12: 862-870.
  • Received: May 16, 2025
  • Accepted: August 31, 2025
  • Editors: Arnout van de Rijt, Kristian B. Karlson
  • DOI: 10.15195/v12.a34

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Pathways to Independence: The Dynamics of Parental Support in the Transition to Adulthood

By on November 25, 2025 in Articles

Ramina Sotoudeh, Ginevra Floridi

Sociological Science November 25, 2025
10.15195/v12.a33

Abstract

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In the United States, the financial and co-residential dependence of young adults on parents has increased for decades. This study provides the first comprehensive analysis of economic support trajectories, their contextual, family, and individual determinants, and temporal relation to other transition to adulthood milestones. Using data from the Panel Study of Income Dynamics’ Transition to Adulthood Study (2005–2021), we identify trajectories of financial and co-residential support between ages 18 and 28 and relate them to economic and partnership trajectories and events. We study how macro-economic crises (the Great Recession and COVID-19), family characteristics, and individual traits within sibships predict trajectory membership. We find three distinct pathways: first, prolonged education and financial support are more common among advantaged families and, within siblings, among those exposed to the Great Recession. Second, early employment and prolonged co-residence are the most prevalent among disadvantaged families and children. Third, economic independence through marriage is most common among white people living outside metropolitan areas.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Ramina Sotoudeh: Department of Sociology, Yale University and Department of Political
and Social Sciences, European University Institute.
E-mail: ramina.sotoudeh@yale.edu.
Ginevra Floridi: School of Social and Political Science, University of Edinburgh.
E-mail: Ginevra.Floridi@ed.ac.uk.

Acknowledgments: We acknowledge funding from British Academy/Leverhulme Small Research Grant SRG2324\240432. Versions of this article were presented at the European Population Conference in Edinburgh, Population Association of America Meeting in Washington DC, and PopDays in Cagliari. We are grateful for the helpful feedback that we received. We thank our parents for their economic and non-economic support throughout our lives and the U.S. highway system for providing us with ample time to discuss our ideas for this article.

Supplemental Materials

Reproducibility Package: Replication code for this article can be accessed here: https://github.com/raminasotoudeh/pathways_to_independence/tree/main

  • Citation: Sotoudeh, Ramina, Ginevra Floridi. 2025. “Pathways to Independence: The Dynamics of Parental Support in the Transition to Adulthood” Sociological Science 12: 833-861.
  • Received: July 9, 2025
  • Accepted: August 25, 2025
  • Editors: Arnout van de Rijt, Michael Rosenfeld
  • DOI: 10.15195/v12.a33

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Public Support for the Legalization of Undocumented Immigrants during the 2016 Presidential Campaign

By on November 21, 2025 in Articles

Mariano Sana

Sociological Science November 21, 2025
10.15195/v12.a32

Abstract

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I investigate whether the political ascent of Donald Trump, an adamant immigration restrictionist, during the 2016 presidential campaign was accompanied by decreasing support for the legalization of undocumented immigrants. Compiling survey data from 2012 to 2016, I show consistent support for legalization throughout the period. However, support was on the decline until Trump entered the presidential race in June 2015, rising thereafter. I use two Pew Research Center surveys, fielded in May 2015 and October 2016, to document that the increase in support for legalization was spearheaded by females, suburban residents, and self-identified Democrats. No demographic group, however defined, recorded a significant decline in their support for legalization. The political ascent of Donald Trump between mid-2015 and the presidential election of November 2016 was not associated with a decline in support for the legalization of undocumented immigrants but the opposite, consistent with similar trends recorded in Europe following the rise of right-wing parties. I discuss the implications of these findings for research on immigration attitudes.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Mariano Sana: Department of Sociology, Vanderbilt University.
E-mail: mariano.sana@vanderbilt.edu.

Acknowledgments: I benefited from comments and suggestions from Guy Stecklov, Jenny Trinitapoli, and Alex Weinreb as well as those of the editor and anonymous reviewers. My gratitude also goes to Yu-Ri Kim and Alyssa Davis for their research assistance.


Reproducibility Package: Data and code necessary for full replication are publicly available here: https://www.openicpsr.org/openicpsr/project/238445/version/V1/view. Original raw data were downloaded from the Roper iPoll database managed by the Public Opinion Research Archive at Cornell University (https://ropercenter.cornell.edu/ipoll/) and from the Pew Research Center (https://www.pewresearch.org/tools-and-datasets/).

  • Citation: Sana, Mariano. 2025. “Public Support for the Legalization of Undocumented Immigrants during the 2016 Presidential Campaign” Sociological Science 12: 804-832.
  • Received: August 18, 2025
  • Accepted: October 9, 2025
  • Editors: Ari Adut, Maria Abascal
  • DOI: 10.15195/v12.a32

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The Hardcore Brokers: Core-Periphery Structure and Political Representation in Denmark’s Corporate Elite Network

By on November 18, 2025 in Articles

Lasse Folke Henriksen, Jacob Aagard Lunding, Christoph Houman Ellersgaard, Anton Grau Larsen

Sociological Science November 18, 2025
10.15195/v12.a31

Abstract

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Who represents the corporate elite in democratic governance? In his seminal work on the corporate “inner circle,” Useem (1986) studied three network-related mechanisms from corporate interlocks that together shaped the ideology and political organization of American and British corporate elites during the postwar era in crucial ways: corporate brokerage, elite social cohesion, and network centrality. Subsequent research has found similar dynamics at play across a variety of democratic capitalist societies. However, all existing studies on corporate elite representation in democratic governance rest on analyses of the top ranks at very large corporations. We cast a wider net. Analyzing new population data on all members of corporate boards in the Danish economy (∼200,000 directors in ∼120,000 boards), we locate ∼1,500 directors who operate as brokers between local corporate networks and measure their network coreness using k-core detection. We find a highly connected network core of ∼275 directors, half of whom are affiliated with smaller companies or subsidiaries and then document the power of director coreness in predicting government committee attendance, a key form of political representation in Denmark’s social-corporatist model of governance. We find a large political premium for directors in very large companies but show that within the network core the gap between directors of smaller and large companies is closed, suggesting that the network core levels the playing field in corporate access to the legislative process.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Lasse Folke Henriksen: Department of Organization, Copenhagen Business School.
E-mail: lfh.ioa@cbs.dk
Jacob Aagard Lunding: Department of Social Sciences and Business, Roskilde University.
E-mail: jaagaard@ruc.dk
Christoph Houman Ellersgaard: Department of Organization, Copenhagen Business School.
E-mail: che.ioa@cbs.dk.
Anton Grau Larsen: Department of Social Sciences and Business, Roskilde University.
E-mail: agraul@ruc.dk

Acknowledgments: We would like to thank Leonard Seabrooke, Felix Bühlman, Donald Tomaskovic-Devey, Thomas Lyttelton, and Megan Neely for commenting on an earlier draft of this article. We also thank participants at the Political Economy Group Seminar at the Copenhagen Business School for engaging with an earlier draft. We are grateful to the Independent Research Fund Denmark (grant 5052-00143b), the Carlsberg Foundation (grant CF19-0175), and the Velux Foundation (grant 00048306) for generously supporting this research.

Supplemental Materials

Reproducibility Package: Because our data-use agreement prohibits direct sharing of our analytic data, we share only the analysis code here: https://github.com/JacobLunding/hardcore_brokers_replication. Interested parties may apply to Statistics Denmark (https://www.dst.dk/en/TilSalg/Forskningsservice/Dataadgang/) for access to the data (project 706264) and can run the full replication package from the folder named “/replication,” which includes all data generating steps of the analysis and the analytical code.

  • Citation: Henriksen, Lasse Folke, Jacob Aagard Lunding, Christoph Houman Ellersgaard, Anton Grau Larsen. 2025. “The Hardcore Brokers: Core-Periphery Structure and Political Representation in Denmark’s Corporate Elite Network” Sociological Science 12: 769-803.
  • Received: December 19, 2024
  • Accepted: September 24, 2025
  • Editors: Arnout van de Rijt, Michael Rosenfeld
  • DOI: 10.15195/v12.a31

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The Intergenerational Reach of Maternal Adverse Childhood Experiences: Associations with Children’s Emotional Support and Cognitive Stimulation

By on November 6, 2025 in Articles

Lawrence Stacey, Kristi Williams

Sociological Science November 6, 2025
10.15195/v12.a30

Abstract

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Adverse childhood experiences (ACEs)—such as abuse, neglect, and household dysfunction before age 18—pose substantial risks to individual health and well-being throughout life, but relatively less research has examined how ACEs are associated with parenting behaviors or children’s home environments. We use linked mother–child data from the National Longitudinal Survey of Youth 1979, a U.S. longitudinal cohort study, to investigate how maternal ACEs are associated with the emotional support and cognitive stimulation of children. Regression results demonstrate an inverse relationship between maternal ACE exposure and the degree of emotional support and cognitive stimulation in children’s home environments. Children born to mothers with four or more ACEs had, on average, 4.9 percentile-unit lower emotional support scores and 5.6 percentile-unit lower cognitive stimulation scores relative to mothers with no ACE exposure, net of maternal and child sociodemographic characteristics. Further results document the importance of emotional neglect and physical abuse, both of which were independently and negatively related to the emotional support and cognitive stimulation of children. Our article builds on a growing body of literature by documenting links between maternal ACE exposure and children’s home environments and by illuminating the lengthy intergenerational reach of parental ACEs.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Lawrence Stacey: Department of Sociology, Vanderbilt University.
E-mail: lawrence.stacey@vanderbilt.edu.
Kristi Williams: Department of Sociology, Ohio State University.
E-mail: williams.2339@osu.edu.

Acknowledgments: We wish to thank Melissa Alcaraz, John Casterline, Reanne Frank, Sarah Hayford, Jake Hays, and Alec Rhodes for feedback on an earlier draft of this article. We also wish to thank the editors of Sociological Science.

Supplemental Materials

Reproducibility Package: A replication package with instructions, data, and Stata code has been
made publicly available on the Open Science Framework (OSF): https://osf.io/gb29u/

  • Citation: Stacey, Lawrence, and Kristi Williams. 2025. “The Intergenerational Reach of Maternal
    Adverse Childhood Experiences: Associations with Children’s Emotional Support and Cognitive Stimulation” Sociological Science 12: 743-768.
  • Received: June 17, 2024
  • Accepted: April 24, 2025
  • Editors: Arnout van de Rijt, Michael Rosenfeld
  • DOI: 10.15195/v12.a30

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Wide Social Influence and the Emergence of the Unexpected: An Empirical Test Using Spotify Data

By on October 23, 2025 in Articles

Martin Arvidsson, Peter Hedström, Marc Keuschnigg

Sociological Science October 23, 2025
10.15195/v12.a29

Abstract

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Social-influence processes not only affect the rate at which behaviors spread but can also decouple adoption behavior from individual preferences, and thereby bring about unexpected collective outcomes that cannot be predicted on the basis of the initial likes and dislikes of the individuals involved. However, the conditions under which social influence can lead to such decoupling are not well understood. We identify a social-influence mechanism that widens individuals’ behavioral repertoires and breaks the link between individuals’ initial preferences and the collective outcomes they jointly bring about. We test the micro-level assumptions of the mechanism in the context of cultural choices on Spotify, combining topic modeling with traditional statistical matching to cultural change. agent-based simulation estimate peer-to-peer influence effects from digital trace data. We then use agent-based simulations to examine the macro-level consequences of “wide” social influence and its importance for explaining cultural change.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Martin Arvidsson: The Institute for Analytical Sociology, Linköping University. E-mail: martin.arvidsson@liu.se.
Peter Hedström: The Institute for Analytical Sociology, Linköping University. E-mail: peter.hedstrom@liu.se.
Marc Keuschnigg: The Institute for Analytical Sociology, Linköping University and Institute of Sociology, Leipzig University. E-mail: marc.keuschnigg@liu.se.

Acknowledgments: For helpful comments, we thank James Evans, Jacob Habinek, Mark Lutter, Arnout van de Rijt, and Duncan Watts. We are grateful for financial support from Riksbankens Jubileumsfond (M12-0301:1) and the Swedish Research Council (2013-7681, 2018-05170, 2019-00245, and 2024-01861). This research was carried out at the Swedish Excellence Center for Computational Social Science, which is also funded by the Swedish Research Council (2022-06611). Resources provided by the Swedish National Infrastructure for Computing (2024/22-1012) enabled computations.

Supplemental Materials

Reproducibility Package: A replication package has been deposited to OSF (https://osf.io/grsyt/?view_only=133867f728644ba596eb104890cb018f ) that contains code and data required to reproduce the results presented in the article.

  • Citation: Arvidsson, Martin, Peter Hedström, Marc Keuschnigg. 2025. “Wide Social Influence and the Emergence of the Unexpected: An Empirical Test Using Spotify Data.” Sociological Science 12: 715-742.
  • Received: December 16, 2024
  • Accepted: September 10, 2025
  • Editors: Ari Adut, Peter Bearman
  • DOI: 10.15195/v12.a29

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