Identification in Interaction: Racial Mirroring between Interviewers and Respondents.

Previous research has established that people shift their identities situationally and may come to subconsciously mirror one another. We explore this phenomenon among survey interviewers in the 2004-2018 General Social Survey by drawing on repeated measures of racial identification collected after each interview. We find not only that interviewers self-identify differently over time but also that their response changes cannot be fully explained by several measurement-error related expectations, either random or systematic. Rather, interviewers are significantly more likely to identify their race in ways that align with respondents' reports. The potential for affiliative identification, even if subconscious, has a range of implications for understanding race-of-interviewer effects, the social construction of homophily, and for how we consider causality in studies of race and racial inequality more broadly.

Within-job gender pay inequality in 15 countries.

Extant research on the gender pay gap suggests that men and women who do the same work for the same employer receive similar pay, so that processes sorting people into jobs are thought to account for the vast majority of the pay gap. Data that can identify women and men who do the same work for the same employer are rare, and research informing this crucial aspect of gender differences in pay is several decades old and from a limited number of countries. Here, using recent linked employer-employee data from 15 countries, we show that the processes sorting people into different jobs account for substantially less of the gender pay differences than was previously believed and that within-job pay differences remain consequential.

Placing Racial Classification in Context.

This article extends previous research on place-based patterns of racial categorization by linking it to sociological theory that posits subnational variation in cultural schemas and applying regression techniques that allow for spatial variation in model estimates. We use data from a U.S. restricted-use geocoded longitudinal survey to predict racial classification as a function of both individual and county characteristics. We first estimate national average associations, then turn to spatial-regime models and geographically weighted regression to explore how these relationships vary across the country. We find that individual characteristics matter most for classification as "Black," while contextual characteristics are important predictors of classification as "White" or "Other," but some predictors also vary across space, as expected. These results affirm the importance of place in defining racial boundaries and suggest that U.S. racial schemas operate at different spatial scales, with some being national in scope while others are more locally situated.

Exploring international gender differences in mathematics self-concept.

This study provides an international perspective on mathematics by examnnng mathematics self-concept, achievement, and the desire to enter a career involving mathematics among eighth graders in 49 countries. Using data from the Trends in International Mathematics and Science Study, this study shows that self-concept in mathematics is more closely related to the desire to enter a career using mathematics than achievement is. Further, while gender differences in mathematics self-concept are smaller in more egalitarian countries, both girls and boys have lower mathematics self-concepts and less interest in mathematics careers in these countries. These findings reveal a policy paradox: policies aimed at training the next generation of STEM professionals often highlight the need to close the gender gap, but countries with smaller gender gaps have fewer boys and girls interested in mathematics-intensive careers. We conclude by highlighting the importance of disentangling instrumental and expressive aspects of gender inequality in STEM fields.

`Membership Has Its Privileges': Status Incentives and Categorical Inequality in Education.

Prizes - formal systems that publicly allocate rewards for exemplary behavior - play an increasingly important role in a wide array of social settings, including education. In this paper, we evaluate a prize system designed to boost achievement at two high schools by assigning students color-coded ID cards based on a previously low stakes test. Average student achievement on this test increased in the ID card schools beyond what one would expect from contemporaneous changes in neighboring schools. However, regression discontinuity analyses indicate that the program created new inequalities between students who received low-status and high-status ID cards. These findings indicate that status-based incentives create categorical inequalities between prize winners and others even as they reorient behavior toward the goals they reward.

Disentangling the Effects of Racial Self-identification and Classification by Others: The Case of Arrest.

Scholars of race have stressed the importance of thinking about race as a multidimensional construct, yet research on racial inequality does not routinely take this multidimensionality into account. We draw on data from the U.S. National Longitudinal Study of Adolescent Health to disentangle the effects of self-identifying as black and being classified by others as black on subsequently being arrested. Results reveal that the odds of arrest are nearly three times higher for people who were classified by others as black, even if they did not identify themselves as black. By contrast, we find no effect of self-identifying as black among people who were not seen by others as black. These results suggest that racial perceptions play an important role in racial disparities in arrest rates and provide a useful analytical approach for disentangling the effects of race on other outcomes.

Curricular policy as a collective effects problem: A distributional approach.

Current educational policies in the United States attempt to boost student achievement and promote equality by intensifying the curriculum and exposing students to more advanced coursework. This paper investigates the relationship between one such effort - California's push to enroll all 8th grade students in Algebra - and the distribution of student achievement. We suggest that this effort is an instance of a "collective effects" problem, where the population-level effects of a policy are different from its effects at the individual level. In such contexts, we argue that it is important to consider broader population effects as well as the difference between "treated" and "untreated" individuals. To do so, we present differences in inverse propensity score weighted distributions investigating how this curricular policy changed the distribution of student achievement. We find that California's attempt to intensify the curriculum did not raise test scores at the bottom of the distribution, but did lower scores at the top of the distribution. These results highlight the efficacy of inverse propensity score weighting approaches for examining distributional differences, and provide a cautionary tale for curricular intensification efforts and other policies with collective effects.

From motherhood penalties to husband premia: the new challenge for gender equality and family policy, lessons from Norway.

Given the key role that processes occurring in the family play in creating gender inequality, the family is a central focus of policies aimed at creating greater gender equality. We examine how family status affects the gender wage gap using longitudinal matched employer-employee data from Norway, 1979-96, a period with extensive expansion of family policies. The motherhood penalty dropped dramatically from 1979 to 1996. Among men the premia for marriage and fatherhood remained constant. In 1979, the gender wage gap was primarily due to the motherhood penalty, but by 1996 husband premia were more important than motherhood penalties.

Can we expect more of teachers? Comment on Robinson-Cimpian, Lubienski, Ganley, and Copur-Gencturk (2014).

Robinson-Cimpian, Lubienski, Ganley, and Copur-Gencturk (2014) use nationally representative longitudinal data on a cohort of kindergarten students to argue that teachers' gender biases play a substantial role in creating gender differences in mathematics achievement. In this comment, I first underscore the importance of unpacking the black box of mathematics and understanding how gender differences in specific mathematics skills are related to subsequent gender differences in other areas of mathematics. Second, I place questions of teacher bias in a larger sociological context, arguing that we should not be surprised that teachers subscribe to widely held stereotypes and suggest that focusing on the shortcomings of teachers can mask the role that we as a society play in creating and maintaining these inequalities.

Algebra for All: California's Eighth-Grade Algebra Initiative as Constrained Curricula.

BACKGROUND/CONTEXT: Across the United States, secondary school curricula are intensifying as a growing proportion of students enroll in high-level academic math courses. In many districts, this intensification process occurs as early as eighth grade, where schools are effectively constraining their mathematics curricula by restricting course offerings and placing more students into Algebra I. This paper provides a quantitative single-case research study of policy-driven curricular intensification in one California school district. RESEARCH QUESTIONS: (1a) What effect did 8th eighth grade curricular intensification have on mathematics course enrollment patterns in Towering Pines Unified schools? (2b) How did the distribution of prior achievement in Towering Pines math classrooms change as the district constrained the curriculum by universalizing 8th eighth grade Algebra? (3c) Did 8th eighth grade curricular intensification improve students' mathematics achievement? SETTING: Towering Pines is an immigrant enclave in the inner-ring suburbs of a major metropolitan area. The district's 10 middle schools together enroll approximately 4,000 eighth graders each year. The districts' students are ethnically diverse and largely economically disadvantaged. The study draws upon administrative data describing 8th eighth graders in the district in the 2004-20-05 through 2007-20-08 school years. INTERVENTION/PROGRAM/PRACTICE: During the study period, Towering Pines dramatically intensified middle school students' math curricula: In the 2004-20-05 school year 32% of the district's 8th eighth graders enrolled in Algebra or a higher- level mathematics course; by the 2007-20-08 school year that proportion had increased to 84%. RESEARCH DESIGN: We use an interrupted time-series design, comparing students' 8th eighth grade math course enrollments, 10th grade math course enrollments, and 10th grade math test scores across the four cohorts, controlling for demographics and prior achievement. FINDINGS/RESULTS: We find that students' odds of taking higher level mathematics courses increased as this district implemented the state's Algebra mandate. However, even as the district implemented a constrained curriculum strategy, mathematics achievement growth between 6th sixth and 10th grade slowed and the achievement advantages associated with 8th eighth grade Algebra declined. CONCLUSIONS/RECOMMENDATIONS: Our analyses suggest that curricular intensification increased the inclusiveness and decreased the selectivity of the mathematics tracking regime in Towering Pines middle schools. However, the findings suggest that this constrained curriculum strategy may have may have unintended negative consequences for student achievement.

Looking the part: social status cues shape race perception.

It is commonly believed that race is perceived through another's facial features, such as skin color. In the present research, we demonstrate that cues to social status that often surround a face systematically change the perception of its race. Participants categorized the race of faces that varied along White-Black morph continua and that were presented with high-status or low-status attire. Low-status attire increased the likelihood of categorization as Black, whereas high-status attire increased the likelihood of categorization as White; and this influence grew stronger as race became more ambiguous (Experiment 1). When faces with high-status attire were categorized as Black or faces with low-status attire were categorized as White, participants' hand movements nevertheless revealed a simultaneous attraction to select the other race-category response (stereotypically tied to the status cue) before arriving at a final categorization. Further, this attraction effect grew as race became more ambiguous (Experiment 2). Computational simulations then demonstrated that these effects may be accounted for by a neurally plausible person categorization system, in which contextual cues come to trigger stereotypes that in turn influence race perception. Together, the findings show how stereotypes interact with physical cues to shape person categorization, and suggest that social and contextual factors guide the perception of race.

Cause of death affects racial classification on death certificates.

Recent research suggests racial classification is responsive to social stereotypes, but how this affects racial classification in national vital statistics is unknown. This study examines whether cause of death influences racial classification on death certificates. We analyze the racial classifications from a nationally representative sample of death certificates and subsequent interviews with the decedents' next of kin and find notable discrepancies between the two racial classifications by cause of death. Cirrhosis decedents are more likely to be recorded as American Indian on their death certificates, and homicide victims are more likely to be recorded as Black; these results remain net of controls for followback survey racial classification, indicating that the relationship we reveal is not simply a restatement of the fact that these causes of death are more prevalent among certain groups. Our findings suggest that seemingly non-racial characteristics, such as cause of death, affect how people are racially perceived by others and thus shape U.S. official statistics.