{"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}
{"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
{"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}
{"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}
Mana Nakagawa, Christine Min Wotipka, Elizabeth Buckner
{"title":"Opportunities for Faculty Tenure at Globally Ranked Universities: Cross-National Differences by Gender, Fields, and Tenure Status","authors":"Mana Nakagawa, Christine Min Wotipka, Elizabeth Buckner","doi":"10.15195/v11.a39","DOIUrl":"https://doi.org/10.15195/v11.a39","url":null,"abstract":"Drawing on a unique data set of almost 12,000 faculty members from 52 globally ranked universities in four fields (sociology, biology, history, and engineering), this study describes and explains gender differences in tenure among faculty across 13 countries. In our sample, women comprise roughly one-third of all faculty and only 23 percent of tenured faculty, with significant variation across fields and countries. Findings from a series of multilevel regression analyses suggest support for a gender filter argument: women are less likely to be tenured overall and in every field. Opportunities for tenure also matter. In countries with very low- and high-tenure rates, women are much less likely to be tenured relative to men than in countries with pathways both into and upward in academia.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"3 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142718438","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}
David R. Schaefer, Sara I. Villalta, Victoria Vezaldenos, Adriana J. Umaña-Taylor
{"title":"Some Birds Have Mixed Feathers: Bringing the Multiracial Population into the Study of Race Homophily","authors":"David R. Schaefer, Sara I. Villalta, Victoria Vezaldenos, Adriana J. Umaña-Taylor","doi":"10.15195/v11.a38","DOIUrl":"https://doi.org/10.15195/v11.a38","url":null,"abstract":"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.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"11 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142601947","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}
Marissa E. Thompson, Tobias Dalberg, Elizabeth E. Bruch
{"title":"Gender Segregation and Decision-Making in Undergraduate Course-Taking","authors":"Marissa E. Thompson, Tobias Dalberg, Elizabeth E. Bruch","doi":"10.15195/v11.a37","DOIUrl":"https://doi.org/10.15195/v11.a37","url":null,"abstract":"Gender segregation across fields of study is a persistent problem in higher education. Although a large body of literature has illustrated both gendered patterns in major choice as well as overall gender segregation across academic majors, comparatively less attention has been paid to an important building block for gender inequality: college courses. In this study, we examine the process of how students choose courses and the implications for gender segregation. Drawing on a unique data set that includes individual-level consideration and choice data from an entire cohort of university students choosing their first college courses, we examine both gender segregation at the college course level as well as the extent to which individual decision-making processes are themselves gendered. We find that course gender composition serves as a screener at the consideration stage, which suggests that gender segregation in decision-making emerges at the outset of the choice process. Once a subset of considered options has been established, final choices are much less influenced by course gender compositions. Furthermore, we find that courses are much more gender-segregated, on average, than majors themselves, illustrating that segregation is occurring at a more microlevel than commonly studied. ","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"80 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142596601","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":"Social Status and the Moral Acceptance of Artificial Intelligence","authors":"Patrick Schenk, Vanessa A. Müller, Luca Keiser","doi":"10.15195/v11.a36","DOIUrl":"https://doi.org/10.15195/v11.a36","url":null,"abstract":"The morality of artificial intelligence (AI) has become a contentious topic in academic and public debates. We argue that AIs moral acceptance depends not only on its ability to accomplish a task in line with moral norms but also on the social status attributed to AI. Agent type (AI vs. computer program vs. human), gender, and organizational membership impact moral permissibility. In a factorial survey experiment, 578 participants rated the moral acceptability of agents performing a task (e.g., cancer diagnostics). We find that using AI is judged less morally acceptable than employing human agents. AI used in high-status organizations is judged more morally acceptable than in low-status organizations. No differences were found between computer programs and AI. Neither anthropomorphic nor gender framing had an effect. Thus, human agents in high-status organizations receive a moral surplus purely based on their structural position in a cultural status hierarchy regardless of their actual performance.","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"18 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541504","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}
Sociological SciencePub Date : 2024-01-01Epub Date: 2024-03-25DOI: 10.15195/v11.a10
Kristen Harknett, Charlotte O'Herron, Evelyn Bellew
{"title":"Can't Catch a Break: Intersectional Inequalities at Work.","authors":"Kristen Harknett, Charlotte O'Herron, Evelyn Bellew","doi":"10.15195/v11.a10","DOIUrl":"10.15195/v11.a10","url":null,"abstract":"<p><p>The labor market is the site of longstanding and persistent inequalities across race and gender groups in hiring, compensation, and advancement. In this paper, we draw on data from 13,574 hourly service-sector workers to extend the study of intersectional labor market inequalities to workers' experience on the job. In the service sector, where workers are regularly expected to be on their feet for long hours and to contend with workloads that are intense and unrelenting, regular break time is an essential component of job quality and general well-being. Yet, we find that Black women are less likely than their counterparts to get a break during their work shift. Although union membership and laws mandating work breaks are effective in increasing access to breaks for workers overall, they do not ameliorate the inequality Black women face in access to work breaks within the service sector. A sobering implication is that worker power and labor protections can raise the floor on working conditions but leave inequalities intact. Our findings also have implications for racial health inequalities, as the routine daily stress of service sector takes a disproportionate toll on the health of Black women.</p>","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"11 ","pages":"233-257"},"PeriodicalIF":2.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11062619/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140851315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sociological SciencePub Date : 2024-01-01Epub Date: 2024-08-09DOI: 10.15195/v11.a22
Won-Tak Joo, Felix Elwert, Martin D Munk
{"title":"Labor Market Consequences of Grandparenthood.","authors":"Won-Tak Joo, Felix Elwert, Martin D Munk","doi":"10.15195/v11.a22","DOIUrl":"10.15195/v11.a22","url":null,"abstract":"<p><p>Little is known about the labor market consequences of becoming a grandparent. We estimate grandparenthood effects on labor supply and earnings using detailed multigenerational data from Danish population registers. Results show that the consequences of grandparenthood are unequally distributed and starkly patterned. Becoming a grandparent reduces hours worked and income, especially for grandmothers, more so when the grandchild is born to a daughter, and most when the grandmother's daughter gives birth as a teenager. Grandfathers also experience a reduction in hours worked (but not income) from their daughter's teen birth, but the reduction is much smaller than among grandmothers. The effects of a daughter's teen birth are further amplified for low-income grandmothers. Our results imply that childbearing has multigenerational consequences that are structured by gendered caregiving, the caregiving needs of the parent generation, and the delegating capacity of the grandparent generation.</p>","PeriodicalId":22029,"journal":{"name":"Sociological Science","volume":"11 ","pages":"600-625"},"PeriodicalIF":2.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12097765/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144128719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}