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

By on November 12, 2024 in Articles

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

Sociological Science November 12, 2024
10.15195/v11.a38

Abstract

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

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

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

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

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

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

Supplemental Materials

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

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


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

By on March 24, 2023 in Articles

Xuege (Cathy) Lu, Shinan Wang, Letian Zhang

Sociological Science March 24, 2023
10.15195/v10.a7

Abstract

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Why do people engage with similar others despite ample opportunities to interact with dissimilar others? We argue that adversity or setbacks may have a stronger deteriorative effect on ties made up of dissimilar individuals, prompting people to give up on such ties more easily, which, over the long run, results in people forming ties with similar others. We examine this argument in the context of Association of Tennis Professionals tournaments, using data on 9,669 unique doubles pairs involving 1,812 unique players from 99 countries from 2000 to 2020. We find that doubles pairs with players from different countries are more likely to dissolve after a setback, especially if those countries lack social trust and connections with one another; this reality further contributes to the individual player’s increased tendency to collaborate with same-country players in the next tournament. Our study has direct implications for interventions for diversity and inclusion.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

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

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

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

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

Supplemental Material

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


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Estimating Homophily in Social Networks Using Dyadic Predictions

By on August 2, 2021 in Articles

George Berry, Antonio Sirianni, Ingmar Weber, Jisun An, Michael Macy

Sociological Science August 2, 2021
10.15195/v8.a14

Abstract

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Predictions of node categories are commonly used to estimate homophily and other relational properties in networks. However, little is known about the validity of using predictions for this task. We show that estimating homophily in a network is a problem of predicting categories of dyads (edges) in the graph. Homophily estimates are unbiased when predictions of dyad categories are unbiased. Node-level prediction models, such as the use of names to classify ethnicity or gender, do not generally produce unbiased predictions of dyad categories and therefore produce biased homophily estimates. Bias comes from three sources: sampling bias, correlation between model errors and node degree, and correlation between node-level model errors along dyads. We examine three methods for estimating homophily: predicting node categories, predicting dyad categories, and a hybrid “ego–alter” approach. This analysis indicates that only the dyadic prediction approach is unbiased, whereas the node-level approach produces both high bias and high overall error. We find that node-level classification performance is not a reliable indicator of accuracy for homophily. Although this article focuses on a particular version of homophily, results generalize to heterophilous cases and other dyadic measures. We conclude with suggestions for research design. Code for this article is available at https://github.com/georgeberry/autocorr.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

George Berry: Department of Sociology, Cornell University
E-mail: geb97@cornell.edu

Antonio Sirianni: Department of Sociology, Dartmouth College
E-mail: antonio.d.sirianni@dartmouth.edu

Ingmar Weber: Qatar Computing Research Institute
E-mail: iweber@hbku.edu.qa

Jisun An: School of Computer and Information Systems, Singapore Management University
E-mail: jisun.an@acm.org

Michael Macy: Department of Sociology, Cornell University
E-mail: mwm14@cornell.edu

Acknowledgments: We thank Thomas Davidson, Mario Molina, Pablo Barberá, Christopher Cameron, Rebecca A. Johnson, Benjamin Cornwell, and Steven Strogatz; participants in the 2020 American Sociological Association section on Mathematical Sociology; the members of the Cornell Social Dynamics Lab; and the members of the Dartmouth Junior Faculty Writing Group for helpful comments and discussions.

Supplemental Material

  • Citation: Berry, George, Antonio Sirianni, Ingmar Weber, Jisun An, and Michael Macy. 2021. “Estimating Homophily in Social Networks Using Dyadic Predictions.” Sociological Science 8: 285-307.
  • Received: January 24, 2021
  • Accepted: April 4, 2021
  • Editors: Jesper Sørensen, Filiz Garip
  • DOI: 10.15195/v8.a14


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Identity Override: How Sexual Orientation Reduces the Rigidity of Racial Boundaries

By on November 7, 2018 in Articles

Adam L. Horowitz, Charles J. Gomez

Sociological Science, November 7, 2018
10.15195/v5.a28

Abstract
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Although most Americans have limited interpersonal relations with different-race others, interracial ties are notably more common among gay, lesbian, and bisexual (GLB) individuals. Departing from the modal explanation of intergroup relations theories, which suggests that individual propensities for between-group interactions are driven by demographic groups’ physical location relative to one another, we show that, beyond propinquity, GLB interraciality is spiked through active identification as GLB. We evaluate full romantic/sexual partnership histories along with friendship network racial compositions for respondents in a large, nationally representative sample. We show that GLBs have a greater likelihood and frequency than heterosexuals of forming multiple types of interracial ties and also that this effect applies only to those who actively identify as GLB and not to those who engage in same-sex relations but do not identify as GLB. This discovery refines theories of intergroup relations, isolating how identification serves as a mediating mechanism that can heighten the propensity for intergroup interaction. We argue that active identification with a group that crosses racial boundaries spurs overriding the rigidity of intergroup borders that otherwise dissuade interpersonal diversity.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Adam L. Horowitz: The Edmond J. Safra Center for Ethics, Tel Aviv University, and Center for Comparative Studies in Race and Ethnicity, Stanford University
E-mail: ahorowitz@stanford.edu

Charles J. Gomez: Department of Sociology, Queens College, City University of New York.
E-mail: charles.gomez@qc.cuny.edu

Acknowledgements: The authors would like to acknowledge the valuable feedback provided by Monica McDermott, Michael Rosenfeld, Morris Zelditch, Jr., Tomás Jiménez, and Louis Mittel. Adam Horowitz and Charles Gomez made equivalently consequential contributions to this article, and authorship should be considered equal.

  • Citation: Horowitz, Adam L., and Charles J. Gomez. 2018. “Identity Override: How Sexual Orientation Reduces the Rigidity of Racial Boundaries.” Sociological Science 5: 669-693.
  • Received: July 3, 2018
  • Accepted: August 6, 2018
  • Editors: Mario Small
  • DOI: 10.15195/v5.a28


February 2019

This article has been updated after a reader discovered and brought to the authors’ attention a coding error with a control variable. Add Health codes two responses for declining to report income as 9999998 and 9999996. In the original analyses, these responses were not treated as missing. This authors have corrected the error and rerun the analyses, which are presented in the current version.

The most consequential results of this correction are as follows:

  • The number of respondents in the analytical sample changed from 10,721 to 10,281 (p. 674)
  • The descriptive statistics in Table 1 have changed due to the change in sample size. In addition, due to the recoding of income for some respondents to missing, the descriptive statistics for income at the bottom of the table have changed.
  • The correlations reported in Table 2 have changed.
  • Point estimates for coefficients and standard errors for the models reported in Table 3-6 have changed. These changes generally do not involve changes in statistical significance, and are generally not consequential for the interpretations offered, with the following exceptions:
    • In Table 5, the effect of “GLB” in the “All other race” column is no longer significant at the p<.05 letter. As a result, the text on p. 679 has been changed to say "GLBs are estimated to select four [previously: five] of six friendship network composition categories over “all your race" at significantly higher rates than are heterosexuals."
    • In Table 6, the effect of “Less than High School” in the “Almost all other races” column is no longer statistically significant.

The originally published version of the paper is available here.


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Network Evolution and Social Situations

By on July 5, 2018 in Articles

Per Block

Sociological Science, July 5, 2018
10.15195/v5.a18

Abstract
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Studying the evolution of friendship networks has a long tradition in sociology. Multiple micromechanisms underlying friendship formation have been discovered, the most pervasive being reciprocity, transitivity, and homophily. Although each mechanism is studied in depth on its own, their relation to one another is rarely analyzed, and a theoretical framework that integrates research on all of them does not exist. This article introduces a friendship evolution model, which proposes that each micromechanism is related to interactions in different social situations. Based on this model, decreasing returns to embedding in multiple mechanisms are hypothesized. Complete social network data of adolescents and statistical network models are used to test these hypotheses. Results show a consistently negative interaction in line with the formulated model. The consequences of this negative relation between the network evolution mechanisms are explored in a simulation study, which suggests that this is a strong determinant of network-level integration and segregation.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Per Block: Department of Humanities, Social and Political Sciences, ETH Zürich
E-mail: per.block@gess.ethz.ch

Acknowledgements: This work greatly benefited from discussions with and advice from Zsofia Boda, James Hollway, Janne Jonsson, Isabel Raabe, Tom Snijders, Christoph Stadtfeld, Christian Steglich, Andras Vörös, as well as comments by the attendees of the Sunbelt Conference in Redondo Beach, the International Network of Analytical Sociologists (INAS) conference in Boston, the Sociology seminar in Groningen, and the Nuffield Network Seminar. This work was partially carried out at the University of Oxford and benefited from a scholarship from Nuffield College.

Supplemental Material

  • Citation: Block, Per. 2018. “Network Evolution and Social Situations.” Sociological Science 5:402-431.
  • Received: April 30, 2018
  • Accepted: May 16, 2018
  • Editors: Jesper Sørensen, Olav Sorenson
  • DOI: 10.15195/v5.a18

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Predicting Altruistic Behavior and Assessing Homophily: Evidence from the Sisterhood

By on October 3, 2016 in Articles

Michael J. Vernarelli

Sociological Science, October 3, 2016
DOI 10.15195/v3.a38

Abstract

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The persistence of altruism throughout the evolutionary process has been explained by some on the basis of assortation, which requires the ability to detect dispositional altruism in others and voluntary interaction, resulting in altruism homophily. Numerous studies have identified the ability to detect dispositional altruism in strangers, but few have investigated this ability and altruism homophily in social networks. The purpose of this study is to provide additional evidence with regard to the ability to detect dispositional altruism among individuals who have repeated interactions in a collegiate social organization and the extent of altruism homophily. The results indicate that individuals possess an ability to predict dispositional altruism as measured by behavior in the dictator game and that this ability is a function of social closeness. However, the study does not support the hypothesis of an assortation process that results in altruism homophily.

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

Michael J. Vernarelli: Department of Economics, Rochester Institute of Technology
Email: mjvgss@rit.edu

Acknowledgements: I would like to thank Brent Simpson, Jeffrey Wagner, Audrey Smerbeck, John Edlund, and Gregory DeAngelo for their comments and suggestions on earlier drafts of the paper. Jesper Sørensen made suggestions that were incorporated in the final version of the manuscript. Yosef Boutakov and Matthew Kehoe assisted with data collection. Jonathan Stone assisted with data collection in the pilot study.

Supplemental Material

  • Citation: Vernarelli, Michael J. 2016. “Predicting Altruistic Behavior and Assessing Homophily: Evidence from the Sisterhood.” Sociological Science 3: 889-909.
  • Received: May 25, 2016
  • Accepted: June 30, 2016
  • Editors: Jesper Sørensen, Gabriel Rossman
  • DOI: 10.15195/v3.a38


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