Andrew Miles, Gordon Brett, Salwa Khan, Yagana Samim
Dual-process perspectives have made substantial contributions to our understanding of behavior, but fundamental questions about how and when deliberate and automatic cognition shape action continue to be debated. Among these are whether automatic or deliberate cognition is ultimately in control of behavior, how often each type of cognition controls behavior in practice, and how the answers to each of these questions depends on the individual in question. To answer these questions, sociologists need methodological tools that enable them to directly test competing claims. We argue that this aim will be advanced by (a) using a particular type of data known as response conflict data and (b) analyzing those data using multinomial processing tree models. We illustrate the utility of this approach by reanalyzing three samples of data from Miles et al. (2019) on behaviors related to politics, morality, and race.
{"title":"Testing Models of Cognition and Action Using Response Conflict and Multinomial Processing Tree Models","authors":"Andrew Miles, Gordon Brett, Salwa Khan, Yagana Samim","doi":"10.15195/v10.a4","DOIUrl":"https://doi.org/10.15195/v10.a4","url":null,"abstract":"Dual-process perspectives have made substantial contributions to our understanding of behavior, but fundamental questions about how and when deliberate and automatic cognition shape action continue to be debated. Among these are whether automatic or deliberate cognition is ultimately in control of behavior, how often each type of cognition controls behavior in practice, and how the answers to each of these questions depends on the individual in question. To answer these questions, sociologists need methodological tools that enable them to directly test competing claims. We argue that this aim will be advanced by (a) using a particular type of data known as response conflict data and (b) analyzing those data using multinomial processing tree models. We illustrate the utility of this approach by reanalyzing three samples of data from Miles et al. (2019) on behaviors related to politics, morality, and race.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"42 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167462","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}
Gaël Le Mens, Balázs Kovács, Michael T. Hannan, Guillem Pros
Social scientists have long been interested in understanding the extent to which the typicalities of an object in concepts relate to its valuations by social actors. Answering this question has proven to be challenging because precise measurement requires a feature-based description of objects. Yet, such descriptions are frequently unavailable. In this article, we introduce a method to measure typicality based on text data. Our approach involves training a deep-learning text classifier based on the BERT language representation and defining the typicality of an object in a concept in terms of the categorization probability produced by the trained classifier. Model training allows for the construction of a feature space adapted to the categorization task and of a mapping between feature combination and typicality that gives more weight to feature dimensions that matter more for categorization. We validate the approach by comparing the BERT-based typicality measure of book descriptions in literary genres with average human typicality ratings. The obtained correlation is higher than 0.85. Comparisons with other typicality measures used in prior research show that our BERT-based measure better reflects human typicality judgments.
{"title":"Using Machine Learning to Uncover the Semantics of Concepts: How Well Do Typicality Measures Extracted from a BERT Text Classifier Match Human Judgments of Genre Typicality?","authors":"Gaël Le Mens, Balázs Kovács, Michael T. Hannan, Guillem Pros","doi":"10.15195/v10.a3","DOIUrl":"https://doi.org/10.15195/v10.a3","url":null,"abstract":"Social scientists have long been interested in understanding the extent to which the typicalities of an object in concepts relate to its valuations by social actors. Answering this question has proven to be challenging because precise measurement requires a feature-based description of objects. Yet, such descriptions are frequently unavailable. In this article, we introduce a method to measure typicality based on text data. Our approach involves training a deep-learning text classifier based on the BERT language representation and defining the typicality of an object in a concept in terms of the categorization probability produced by the trained classifier. Model training allows for the construction of a feature space adapted to the categorization task and of a mapping between feature combination and typicality that gives more weight to feature dimensions that matter more for categorization. We validate the approach by comparing the BERT-based typicality measure of book descriptions in literary genres with average human typicality ratings. The obtained correlation is higher than 0.85. Comparisons with other typicality measures used in prior research show that our BERT-based measure better reflects human typicality judgments.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"41 4","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167463","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}
Scholars have long proposed that gender inequalities in wages are narrowed by organizational policies to advance gender equality. Using cross-sectional data, scarce previous research has found an association between gender wage inequalities and these organizational policies, but it remains unclear whether this correlation represents a causal effect. We provide first evidence on this topic by using longitudinal linked employer–employee data covering almost 1,500 firms and nearly one million employee observations in Germany. We investigate whether and how organizational policies affect gender gaps using firm fixed-effects regressions. Our results show that organizational policies reduce the gender wage gap by around nine percent overall. Investigating channels, we show that this effect is entirely driven by advancing women already employed at a given firm, whereas we find no effect on firms' composition and wages of new hires. Furthermore, we show that our findings are not driven by potential sources of bias, such as reverse causality.
{"title":"Do Organizational Policies Narrow Gender Inequality? Novel Evidence from Longitudinal Employer–Employee Data","authors":"Florian Zimmermann, Matthias Collischon","doi":"10.15195/v10.a2","DOIUrl":"https://doi.org/10.15195/v10.a2","url":null,"abstract":"Scholars have long proposed that gender inequalities in wages are narrowed by organizational policies to advance gender equality. Using cross-sectional data, scarce previous research has found an association between gender wage inequalities and these organizational policies, but it remains unclear whether this correlation represents a causal effect. We provide first evidence on this topic by using longitudinal linked employer–employee data covering almost 1,500 firms and nearly one million employee observations in Germany. We investigate whether and how organizational policies affect gender gaps using firm fixed-effects regressions. Our results show that organizational policies reduce the gender wage gap by around nine percent overall. Investigating channels, we show that this effect is entirely driven by advancing women already employed at a given firm, whereas we find no effect on firms' composition and wages of new hires. Furthermore, we show that our findings are not driven by potential sources of bias, such as reverse causality.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"40 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167468","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}
This article introduces the concept of multiple, layered, and interacting histories, which opens four new avenues of research. We can ask which types of institutions or events, such as states, religions, or war, are more likely to leave a historical legacy. We can also explore why only certain states, religions, or wars leave legacies. We can compare the consequences of older and newer layers of history, such as of a series of successor states. Finally, these layers may interact with each other by preserving, neutralizing, or amplifying each other's effects. To illustrate these new research avenues, I use measurements of value orientations as well as generalized trust from the European Social Survey as dependent variables. New data on the history of states as well as the wars fought since 1500 are combined with existing data on the medieval policies of the Church, all coded at the level of 411 European regions. A series of regression models suggests that the political history of states is more consequential for contemporary attitudes than medieval religious policies or wars, that older layers of states can be as impactful as more recent ones, that interactions between layers are frequent, and that modern nation-states are more likely to leave a legacy than other types of polities.
{"title":"Layered Legacies. How Multiple Histories Shaped the Attitudes of Contemporary Europeans","authors":"Andreas Wimmer","doi":"10.15195/v10.a1","DOIUrl":"https://doi.org/10.15195/v10.a1","url":null,"abstract":"This article introduces the concept of multiple, layered, and interacting histories, which opens four new avenues of research. We can ask which types of institutions or events, such as states, religions, or war, are more likely to leave a historical legacy. We can also explore why only certain states, religions, or wars leave legacies. We can compare the consequences of older and newer layers of history, such as of a series of successor states. Finally, these layers may interact with each other by preserving, neutralizing, or amplifying each other's effects. To illustrate these new research avenues, I use measurements of value orientations as well as generalized trust from the European Social Survey as dependent variables. New data on the history of states as well as the wars fought since 1500 are combined with existing data on the medieval policies of the Church, all coded at the level of 411 European regions. A series of regression models suggests that the political history of states is more consequential for contemporary attitudes than medieval religious policies or wars, that older layers of states can be as impactful as more recent ones, that interactions between layers are frequent, and that modern nation-states are more likely to leave a legacy than other types of polities.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"37 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50167473","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}
{"title":"Marginal Odds Ratios: What They Are, How to Compute Them, and Why Sociologists Might Want to Use Them","authors":"K. Karlson, Ben Jann","doi":"10.15195/v10.a10","DOIUrl":"https://doi.org/10.15195/v10.a10","url":null,"abstract":"","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"1 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66863599","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 decades, researchers have sought to understand the separate contributions of age, period, and cohort (APC) on a wide range of outcomes. However, a major challenge in these efforts is the linear dependence among the three time scales. Previous methods have been plagued by either arbitrary assumptions or extreme sensitivity to small variations in model specification. In this article, we present an alternative method that achieves partial identification by leveraging additional information about subpopulations (or strata) such as race, gender, and social class. Our first goal is to introduce the cross-strata linearized APC (CSL-APC) model, a re-parameterization of the traditional APC model that focuses on cross-group variations in effects instead of overall effects. Similar to the traditional model, the linear cross-strata APC effects are not identified. The second goal is to show how Fosse and Winship’s (2019) bounding approach can be used to address the identification problem of the CSL-APC model, allowing one to partially identify cross-group differences in effects. This approach often involves weaker assumptions than previously used techniques and, in some cases, can lead to highly informative bounds. To illustrate our method, we examine differences in temporal effects on wages between men and women in the United States.
{"title":"Cross-Group Differences in Age, Period, and Cohort Effects: A Bounding Approach to the Gender Wage Gap","authors":"Ohjae Gowen, Ethan Fosse, Christopher Winship","doi":"10.15195/v10.a26","DOIUrl":"https://doi.org/10.15195/v10.a26","url":null,"abstract":": For decades, researchers have sought to understand the separate contributions of age, period, and cohort (APC) on a wide range of outcomes. However, a major challenge in these efforts is the linear dependence among the three time scales. Previous methods have been plagued by either arbitrary assumptions or extreme sensitivity to small variations in model specification. In this article, we present an alternative method that achieves partial identification by leveraging additional information about subpopulations (or strata) such as race, gender, and social class. Our first goal is to introduce the cross-strata linearized APC (CSL-APC) model, a re-parameterization of the traditional APC model that focuses on cross-group variations in effects instead of overall effects. Similar to the traditional model, the linear cross-strata APC effects are not identified. The second goal is to show how Fosse and Winship’s (2019) bounding approach can be used to address the identification problem of the CSL-APC model, allowing one to partially identify cross-group differences in effects. This approach often involves weaker assumptions than previously used techniques and, in some cases, can lead to highly informative bounds. To illustrate our method, we examine differences in temporal effects on wages between men and women in the United States.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136301589","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}
J. Larrègue, Frédéric Lebaron, H. Perdry, N. Robette
A N article recently published in Sociological Science explored cultural tastes and practices in Denmark using a behavioral genetic lens (Jæger and Møllegaard 2022). Using data from monozygotic and dizygotic twins, the authors concluded that shared familial environments mattered less than genetic factors, thus questioning the soundness of established sociological theorizations of cultural inequalities, including Bourdieu’s Distinction (P. 266). After a close methodological and conceptual examination, our main conclusion is that social scientists should lend little credence to the claims put forth by Jæger and Møllegaard, which fall short of the methodological and conceptual standards habitually upheld in both sociology and behavior genetics. This is true whether we selectively focus
{"title":"Eurythmics or Xenakis? Cultural Tastes (Are Not Made of Genes): Comment on Jæger and Møllegaard, “Where Do Cultural Tastes Come From? Genes, Environments, or Experiences”","authors":"J. Larrègue, Frédéric Lebaron, H. Perdry, N. Robette","doi":"10.15195/v10.a15","DOIUrl":"https://doi.org/10.15195/v10.a15","url":null,"abstract":"A N article recently published in Sociological Science explored cultural tastes and practices in Denmark using a behavioral genetic lens (Jæger and Møllegaard 2022). Using data from monozygotic and dizygotic twins, the authors concluded that shared familial environments mattered less than genetic factors, thus questioning the soundness of established sociological theorizations of cultural inequalities, including Bourdieu’s Distinction (P. 266). After a close methodological and conceptual examination, our main conclusion is that social scientists should lend little credence to the claims put forth by Jæger and Møllegaard, which fall short of the methodological and conceptual standards habitually upheld in both sociology and behavior genetics. This is true whether we selectively focus","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"1 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66863869","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}
: Wealth plays an important role in social stratification but the results that can be obtained when analyzing wealth as a predictor variable depend on modeling decisions. Although wealth consists of multiple components it is often operationalized as net worth. Moreover, wealth effects are likely non-linear, but the functional form is often unknown. To overcome these problems, we propose to 1) split up net worth into gross wealth and debt and evaluate their joint effect and 2) use non-parametric Generalized Additive Models. We show in a simulation study that this approach describes systematic wealth differences in more detail and overfits less to random variation in the data than standard approaches. We then apply the approach to re-analyze wealth gaps in educational attainment in the US. We find that the operationalization of wealth as net worth results in a misclassification of which children have the best and the worst educational prospects. Not negative net worth is associated with the worst educational prospects but only the combination of low gross wealth and low debt. The most advantaged group are not only children with high net worth but all children with high gross wealth independent of the households’ amount of debt.
{"title":"Why Net Worth Misrepresents Wealth Effects and What to Do About It","authors":"Jascha Dräger, Klaus Pforr, Nora Müller","doi":"10.15195/v10.a19","DOIUrl":"https://doi.org/10.15195/v10.a19","url":null,"abstract":": Wealth plays an important role in social stratification but the results that can be obtained when analyzing wealth as a predictor variable depend on modeling decisions. Although wealth consists of multiple components it is often operationalized as net worth. Moreover, wealth effects are likely non-linear, but the functional form is often unknown. To overcome these problems, we propose to 1) split up net worth into gross wealth and debt and evaluate their joint effect and 2) use non-parametric Generalized Additive Models. We show in a simulation study that this approach describes systematic wealth differences in more detail and overfits less to random variation in the data than standard approaches. We then apply the approach to re-analyze wealth gaps in educational attainment in the US. We find that the operationalization of wealth as net worth results in a misclassification of which children have the best and the worst educational prospects. Not negative net worth is associated with the worst educational prospects but only the combination of low gross wealth and low debt. The most advantaged group are not only children with high net worth but all children with high gross wealth independent of the households’ amount of debt.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135360361","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}
: Research on ethnic segregation in schools regularly assumed that ethnic homophily—the tendency to befriend same-ethnic peers, above and beyond other mechanisms of tie formation—is associated with salient ethnic boundaries. We devise a more direct test of this assumption based on a novel measure of ethno-racial group perceptions. In a network study of more than 3000 students in 39 schools of a metropolitan region in Germany, we asked students to indicate which cliques they perceived in their school grade and to describe these groups in their own words. We find that ethno-racial labels are more likely directed at larger cliques that include a higher share of Muslim students or more students with stronger ethnic identification. Still, ethno-racial labels are rarely employed, both absolutely and relative to other modes of classification. Moreover, net ethnic segregation in friendships (“ethnic homophily”) and the reverse pattern in dislike relations (“ethnic heterophobia”) are not associated with a more frequent use of ethno-racial labels. Our results have substantive and methodological implications for the study of social networks and diversity in educational settings.
{"title":"The Ethnic Lens: Social Networks and the Salience of Ethnicity in the School Context","authors":"Clemens Kroneberg, Mark Wittek","doi":"10.15195/v10.a22","DOIUrl":"https://doi.org/10.15195/v10.a22","url":null,"abstract":": Research on ethnic segregation in schools regularly assumed that ethnic homophily—the tendency to befriend same-ethnic peers, above and beyond other mechanisms of tie formation—is associated with salient ethnic boundaries. We devise a more direct test of this assumption based on a novel measure of ethno-racial group perceptions. In a network study of more than 3000 students in 39 schools of a metropolitan region in Germany, we asked students to indicate which cliques they perceived in their school grade and to describe these groups in their own words. We find that ethno-racial labels are more likely directed at larger cliques that include a higher share of Muslim students or more students with stronger ethnic identification. Still, ethno-racial labels are rarely employed, both absolutely and relative to other modes of classification. Moreover, net ethnic segregation in friendships (“ethnic homophily”) and the reverse pattern in dislike relations (“ethnic heterophobia”) are not associated with a more frequent use of ethno-racial labels. Our results have substantive and methodological implications for the study of social networks and diversity in educational settings.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135650206","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}
: Understanding how outcomes for biracial individuals compare with those for their monora-cial peers is critical for understanding how patterns of racial inequality in the contemporary United States might be shifting. Yet, we know very little about the life chances of biracial individuals because of limitations in most available data sources. In this article, I utilize American Community Survey data from 2010 to 2019 to examine the risk of being clearly behind expected grade among biracial and monoracial K-12 students, helping to fill a gap in our understanding. With large sample sizes for most biracial groups, I am able to estimate grade retention risk for biracial students with enough precision to differentiate even modest differences in risk relative to monoracial groups. The results indicate that for most biracial groups, biracial students have risk similar to their lower-risk monoracial constituent group. Although biracial students tend to have favorable family resource characteristics, controlling for these characteristics does little to change the overall placement of their outcomes.
{"title":"Differences in the Risk of Grade Retention for Biracial and Monoracial Students in the United States, 2010 to 2019","authors":"A. Gullickson","doi":"10.15195/v10.a13","DOIUrl":"https://doi.org/10.15195/v10.a13","url":null,"abstract":": Understanding how outcomes for biracial individuals compare with those for their monora-cial peers is critical for understanding how patterns of racial inequality in the contemporary United States might be shifting. Yet, we know very little about the life chances of biracial individuals because of limitations in most available data sources. In this article, I utilize American Community Survey data from 2010 to 2019 to examine the risk of being clearly behind expected grade among biracial and monoracial K-12 students, helping to fill a gap in our understanding. With large sample sizes for most biracial groups, I am able to estimate grade retention risk for biracial students with enough precision to differentiate even modest differences in risk relative to monoracial groups. The results indicate that for most biracial groups, biracial students have risk similar to their lower-risk monoracial constituent group. Although biracial students tend to have favorable family resource characteristics, controlling for these characteristics does little to change the overall placement of their outcomes.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"1 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66863812","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：