Many of the topics most central to the social sciences involve nominal groupings or ordinal rankings. There are many cases in which a summary of a nominal or ordinal independent variable's effect, or the effect on a nominal or ordinal outcome, is needed and useful for interpretation. For example, for nominal or ordinal independent variables, a single summary measure is useful to compare the effect sizes of different variables in a single model or across multiple models, as with mediation. For nominal or ordinal dependent variables, there are often an overwhelming number of effects to examine and understanding the holistic effect of an independent variable or how effect sizes compare within or across models is difficult. In this project, we propose two new summary measures using marginal effects (MEs). For nominal and ordinal independent variables, we propose ME inequality as a summary measure of a nominal or ordinal independent variable's holistic effect. For nominal and ordinal outcome models, we propose a total ME measure that quantifies the comprehensive effect of an independent variable across all outcome categories. The added benefits of our methods are both intuitive and substantively meaningful effect size metrics and approaches that can be applied across a wide range of models, including linear, nonlinear, categorical, multilevel, longitudinal, and more.
{"title":"Inequality and Total Effect Summary Measures for Nominal and Ordinal Variables","authors":"Trenton D. Mize, Bing Han","doi":"10.15195/v12.a7","DOIUrl":"https://doi.org/10.15195/v12.a7","url":null,"abstract":"Many of the topics most central to the social sciences involve nominal groupings or ordinal rankings. There are many cases in which a summary of a nominal or ordinal independent variable's effect, or the effect on a nominal or ordinal outcome, is needed and useful for interpretation. For example, for nominal or ordinal independent variables, a single summary measure is useful to compare the effect sizes of different variables in a single model or across multiple models, as with mediation. For nominal or ordinal dependent variables, there are often an overwhelming number of effects to examine and understanding the holistic effect of an independent variable or how effect sizes compare within or across models is difficult. In this project, we propose two new summary measures using marginal effects (MEs). For nominal and ordinal independent variables, we propose ME inequality as a summary measure of a nominal or ordinal independent variable's holistic effect. For nominal and ordinal outcome models, we propose a total ME measure that quantifies the comprehensive effect of an independent variable across all outcome categories. The added benefits of our methods are both intuitive and substantively meaningful effect size metrics and approaches that can be applied across a wide range of models, including linear, nonlinear, categorical, multilevel, longitudinal, and more.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"62 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143192289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Forster and Neugebauer's (2024) invalidation study is invalid. Their conclusion that factorial survey (FS) experiments 'are not suited for studying hiring behavior' (P. 901) is unjustified, because their claim that they conducted a field experiment (FE) and FS with 'nearly identical' designs is false (P. 891). The two experiments included: (1) different factor levels (for three factors), (2) different unvalidated applicant names (to manipulate ethnicity), (3) different applicant photos, (4) different fixed factors (e.g., applicant stories about moving), and (5) different experimental settings (e.g., testing, instrumentation, and conditions of anonymity). In the current article, I discuss each of these major design differences and explain why it invalidates Forster and Neugebauer's (2024) comparison of their FE and FS findings. I conclude by emphasizing that social scientists are better served by asking why FE and FS findings sometimes differ than by assuming that any difference in findings across the experimental designs invalidates FS.
{"title":"Invalidating Factorial Survey Experiments Using Invalid Comparisons Is Bad Practice: Learning from Forster and Neugebauer (2024)","authors":"Justin T. Pickett","doi":"10.15195/v12.a5","DOIUrl":"https://doi.org/10.15195/v12.a5","url":null,"abstract":"Forster and Neugebauer's (2024) invalidation study is invalid. Their conclusion that factorial survey (FS) experiments 'are not suited for studying hiring behavior' (P. 901) is unjustified, because their claim that they conducted a field experiment (FE) and FS with 'nearly identical' designs is false (P. 891). The two experiments included: (1) different factor levels (for three factors), (2) different unvalidated applicant names (to manipulate ethnicity), (3) different applicant photos, (4) different fixed factors (e.g., applicant stories about moving), and (5) different experimental settings (e.g., testing, instrumentation, and conditions of anonymity). In the current article, I discuss each of these major design differences and explain why it invalidates Forster and Neugebauer's (2024) comparison of their FE and FS findings. I conclude by emphasizing that social scientists are better served by asking why FE and FS findings sometimes differ than by assuming that any difference in findings across the experimental designs invalidates FS.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"15 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143049805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In Forster and Neugebauer (2024), we examine to what extent a factorial survey (FS) on invitations of fictitious applicants can replicate the findings of a nearly identical field experiment conducted with the same employers. In addition to exploring the conditions under which FSs provide valid behavioral predictions, we varied the topic sensitivity and tested whether behavioral predictions were more accurate after filtering out respondents who provided socially desirable answers or did not exert sufficient effort in responding to FS vignettes. Across these conditions, the FS results did not align well with the real-world benchmark. We conclude that researchers must exercise caution when using FSs to study (hiring) behavior. In this rejoinder, we respond to the critique of our study by Pickett (2025).
{"title":"Validating Factorial Survey Experiments: Response to Comment","authors":"Andrea G. Forster, Martin Neugebauer","doi":"10.15195/v12.a6","DOIUrl":"https://doi.org/10.15195/v12.a6","url":null,"abstract":"In Forster and Neugebauer (2024), we examine to what extent a factorial survey (FS) on invitations of fictitious applicants can replicate the findings of a nearly identical field experiment conducted with the same employers. In addition to exploring the conditions under which FSs provide valid behavioral predictions, we varied the topic sensitivity and tested whether behavioral predictions were more accurate after filtering out respondents who provided socially desirable answers or did not exert sufficient effort in responding to FS vignettes. Across these conditions, the FS results did not align well with the real-world benchmark. We conclude that researchers must exercise caution when using FSs to study (hiring) behavior. In this rejoinder, we respond to the critique of our study by Pickett (2025).","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"10 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143049806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ruth Eva Jørgensen, Rosa Cheesman, Ole A. Andreassen, Torkild Hovde Lyngstad
There is a genetic component to divorce risk, but little is known about which and how genetically influenced traits are involved. This study makes three major contributions to address these gaps. First, we link genetic data from the Norwegian Mother, Father, and Child Cohort Study (MoBa) to population register data and estimate the total influence of common genetic variants on partnership dissolution (N = 121, 408). Then, we identify heritable traits associated with partnership dissolution using event-history analysis and a broad set of polygenic indices. Finally, we assess whether associations are robust to controls for confounding in within-sibling models. Significant heritability estimates were found for both females (h2SNP = 0.09; SE = 0.01; p < 0.0001) and males (h2SNP = 0.03; SE = 0.01; p < 0.0001). Genetic dispositions for educational attainment and other sociodemographic factors decrease the probability of partnership dissolution, whereas dispositions for internalizing symptoms and risk behavior increase the likelihood of partnership dissolution. Integrating genetics and sociodemographic approaches can shed new light on the causes of partnership dynamics by helping us understand what drives the selection processes throughout the life course.
离婚风险与遗传因素有关，但人们对离婚风险与哪些以及如何受遗传影响的特征有关知之甚少。本研究为填补这些空白做出了三大贡献。首先，我们将挪威母亲、父亲和儿童队列研究（MoBa）的遗传数据与人口登记数据联系起来，估算出常见遗传变异对伴侣关系解除的总体影响（N = 121，408）。然后，我们利用事件历史分析和一套广泛的多基因指数来确定与伴侣关系解除相关的遗传特征。最后，我们评估了在同胞模型中控制混杂因素后，相关性是否稳健。我们发现，女性（h2SNP = 0.09; SE = 0.01; p < 0.0001）和男性（h2SNP = 0.03; SE = 0.01; p < 0.0001）的遗传率估计值都很显著。教育程度的遗传倾向和其他社会人口因素会降低伴侣关系解体的可能性，而内化症状和危险行为的遗传倾向则会增加伴侣关系解体的可能性。将遗传学和社会人口学方法结合起来，可以帮助我们了解在整个生命过程中是什么驱动了选择过程，从而对伴侣关系动态的成因有新的认识。
{"title":"The Genetics of Partnership Dissolution","authors":"Ruth Eva Jørgensen, Rosa Cheesman, Ole A. Andreassen, Torkild Hovde Lyngstad","doi":"10.15195/v12.a4","DOIUrl":"https://doi.org/10.15195/v12.a4","url":null,"abstract":"There is a genetic component to divorce risk, but little is known about which and how genetically influenced traits are involved. This study makes three major contributions to address these gaps. First, we link genetic data from the Norwegian Mother, Father, and Child Cohort Study (MoBa) to population register data and estimate the total influence of common genetic variants on partnership dissolution (N = 121, 408). Then, we identify heritable traits associated with partnership dissolution using event-history analysis and a broad set of polygenic indices. Finally, we assess whether associations are robust to controls for confounding in within-sibling models. Significant heritability estimates were found for both females (h2SNP = 0.09; SE = 0.01; p < 0.0001) and males (h2SNP = 0.03; SE = 0.01; p < 0.0001). Genetic dispositions for educational attainment and other sociodemographic factors decrease the probability of partnership dissolution, whereas dispositions for internalizing symptoms and risk behavior increase the likelihood of partnership dissolution. Integrating genetics and sociodemographic approaches can shed new light on the causes of partnership dynamics by helping us understand what drives the selection processes throughout the life course.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"37 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142991091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The quality and stability of couple relationships have far-reaching consequences for the well-being of individual partners and patterns of family change. Although much research has compared the quality and stability of same-sex and different-sex relationships, the multidimensional nature of sexuality has received insufficient attention in this scholarship. Individuals in same-sex (different-sex) partnerships do not necessarily identify as gay/lesbian (straight) or report exclusive same-sex (different-sex) attraction—a phenomenon we term 'identity/attraction–partnership inconsistency.' By analyzing nationally representative longitudinal data collected between 2017 and 2022, we show that identity/attraction–partnership inconsistency is common among U.S. adults, ranging from 2 percent of men in different-sex partnerships to 41 percent of women in same-sex partnerships. Regression results show that such inconsistency is associated with lower relationship quality and higher relationship instability, and these negative ramifications are particularly pronounced among individuals, notably men, in different-sex partnerships. Our findings uncover the implications of multidimensional sexuality for relationship dynamics and outcomes given the rigid institutionalization of different-sex couplehood and the close normative regulation of men's heterosexuality. Our study highlights the importance of incorporating multiple dimensions of sexuality and their interplays into research on couple relationships and family change.
{"title":"Straight Jacket: The Implications of Multidimensional Sexuality for Relationship Quality and Stability","authors":"Yue Qian, Yang Hu","doi":"10.15195/v12.a3","DOIUrl":"https://doi.org/10.15195/v12.a3","url":null,"abstract":"The quality and stability of couple relationships have far-reaching consequences for the well-being of individual partners and patterns of family change. Although much research has compared the quality and stability of same-sex and different-sex relationships, the multidimensional nature of sexuality has received insufficient attention in this scholarship. Individuals in same-sex (different-sex) partnerships do not necessarily identify as gay/lesbian (straight) or report exclusive same-sex (different-sex) attraction—a phenomenon we term 'identity/attraction–partnership inconsistency.' By analyzing nationally representative longitudinal data collected between 2017 and 2022, we show that identity/attraction–partnership inconsistency is common among U.S. adults, ranging from 2 percent of men in different-sex partnerships to 41 percent of women in same-sex partnerships. Regression results show that such inconsistency is associated with lower relationship quality and higher relationship instability, and these negative ramifications are particularly pronounced among individuals, notably men, in different-sex partnerships. Our findings uncover the implications of multidimensional sexuality for relationship dynamics and outcomes given the rigid institutionalization of different-sex couplehood and the close normative regulation of men's heterosexuality. Our study highlights the importance of incorporating multiple dimensions of sexuality and their interplays into research on couple relationships and family change.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"61 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For the past three decades, scholars have conducted field experiments to examine gender-based hiring discrimination in the United States. However, these studies have produced mixed results. To further interpret these findings, we performed a meta-analysis of 37 audit studies conducted between 1990 and 2022. Using an aggregated sample of 243,202 fictitious job applications, the study finds no evidence of statistically significant gender discrimination at the study level. However, a series of more focused meta-analyses reveal important variations in the extent of discrimination by occupation type and applicant race. First, the gender composition of an occupation predicts gender bias in hiring. Second, the intersection of gender and race is critical—in female-dominated jobs, White female applicants receive more callbacks than their male counterparts, but Black female applicants experience no such benefit. The study contributes to the literature on labor market and gender (in)equality by synthesizing the findings of field experiments.
{"title":"Getting a Foot in the Door: A Meta-Analysis of U.S. Audit Studies of Gender Bias in Hiring","authors":"So Yun Park, Eunsil Oh","doi":"10.15195/v12.a2","DOIUrl":"https://doi.org/10.15195/v12.a2","url":null,"abstract":"For the past three decades, scholars have conducted field experiments to examine gender-based hiring discrimination in the United States. However, these studies have produced mixed results. To further interpret these findings, we performed a meta-analysis of 37 audit studies conducted between 1990 and 2022. Using an aggregated sample of 243,202 fictitious job applications, the study finds no evidence of statistically significant gender discrimination at the study level. However, a series of more focused meta-analyses reveal important variations in the extent of discrimination by occupation type and applicant race. First, the gender composition of an occupation predicts gender bias in hiring. Second, the intersection of gender and race is critical—in female-dominated jobs, White female applicants receive more callbacks than their male counterparts, but Black female applicants experience no such benefit. The study contributes to the literature on labor market and gender (in)equality by synthesizing the findings of field experiments.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"6 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142940260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although buyers in unregulated markets depend heavily on reputational information in the absence of state oversight, few studies examine how the riskiness of a good may condition reputational effects on prices. We capitalize on novel data on 10,465 illegal drug exchanges on one online 'darknet' illegal drug market and computational text analysis to evaluate how distinct types of legal and quality risks moderate reputational effects on illegal drug prices. Our results suggest that quality risk considerations are especially acute, where the effect of numeric sales ratings and the sentiment expressed in sales review text are both increased for non-prescription drugs and attenuated for prescription drugs. In contrast, we find limited evidence that legal risks moderate reputational effects on illegal drug prices. These results underscore the importance of quality risks in illegal purchasing decisions, identify quality risk as a determinant of reputational premiums for illegal drug prices, and shed light on how the riskiness of a specific good can guide economic action in unregulated trade settings.
{"title":"The Risk Creates the Reward: Reputational Returns to Legal and Quality Risks in Online Illegal Drug Trade","authors":"William Holtkamp, Scott Duxbury, Dana L. Haynie","doi":"10.15195/v12.a1","DOIUrl":"https://doi.org/10.15195/v12.a1","url":null,"abstract":"Although buyers in unregulated markets depend heavily on reputational information in the absence of state oversight, few studies examine how the riskiness of a good may condition reputational effects on prices. We capitalize on novel data on 10,465 illegal drug exchanges on one online 'darknet' illegal drug market and computational text analysis to evaluate how distinct types of legal and quality risks moderate reputational effects on illegal drug prices. Our results suggest that quality risk considerations are especially acute, where the effect of numeric sales ratings and the sentiment expressed in sales review text are both increased for non-prescription drugs and attenuated for prescription drugs. In contrast, we find limited evidence that legal risks moderate reputational effects on illegal drug prices. These results underscore the importance of quality risks in illegal purchasing decisions, identify quality risk as a determinant of reputational premiums for illegal drug prices, and shed light on how the riskiness of a specific good can guide economic action in unregulated trade settings.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"7 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142934844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"New OMB’s Race and Ethnicity Standards Will Affect How Americans Self-Identify","authors":"René D. Flores, Edward Telles, Ilana M. Ventura","doi":"10.15195/v11.a42","DOIUrl":"https://doi.org/10.15195/v11.a42","url":null,"abstract":"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.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"10 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142832034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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
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.
{"title":"The Diffusion and Reach of (Mis)Information on Facebook During the U.S. 2020 Election","authors":"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","doi":"10.15195/v11.a41","DOIUrl":"https://doi.org/10.15195/v11.a41","url":null,"abstract":"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.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"88 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
人口普查局宣布，根据2020年人口普查，多种族人口占美国人口的10.2%，引发了“多种族繁荣”的报告。就在一年前，统计局的美国社区调查（American Community Survey）估计他们的比例为3.4%。我们提供的证据表明，多种族的繁荣在很大程度上是一种统计上的错觉，这是由于方法论上的变化造成的，这种变化混淆了血统和身份，错误地将国籍与种族等同起来。在一种新的算法下，如果受访者在标记了一个种族后，列出了一个算法不认为属于该种族的“血统”，那么他们就会被自动重新编码为多种族。然而，起源和身份是不一样的；将两者混淆并没有改善种族统计数据。虚构的多种族繁荣凸显了官方统计数据在构建公众和社会科学理解方面的力量，以及在理论和实证实践中保持血统和身份不同的必要性。
{"title":"The Multiracial Complication: The 2020 Census and the Fictitious Multiracial Boom","authors":"Paul Starr, Christina Pao","doi":"10.15195/v11.a40","DOIUrl":"https://doi.org/10.15195/v11.a40","url":null,"abstract":"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. ","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"208 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142763365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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