Racial Bias in Police Traffic Stops: White Residents' County-Level Prejudice and Stereotypes Are Related to Disproportionate Stopping of Black Drivers

On the Unequal Burden of Obesity: Obesity's Adverse Consequences Are Contingent on Regional Obesity Prevalence

Obesity has adverse consequences for those affected. We tested whether the association between obesity and its adverse consequences is reduced in regions in which obesity is prevalent and whether lower weight bias in high-obese regions can account for this reduction. Studies 1 and 2 used data from the United States (N = 2,846,132 adults across 2,546 counties) and United Kingdom (N = 180,615 adults across 380 districts) that assessed obesity's adverse consequences in diverse domains: close relationships, economic outcomes, and health. Both studies revealed that the association between obesity and its adverse consequences is reduced (or absent) in high-obese regions. Study 3 used another large-scale data set (N = 409,837 across 2,928 U.S. counties) and revealed that lower weight bias in high-obese regions seems to account for (i.e., mediate) the reduction in obesity's adverse consequences. Overall, our findings suggest that obesity's adverse consequences are partly social and, thus, not inevitable.

What do we know about autism and policing globally? Preliminary findings from an international effort to examine autism and the criminal justice system

Research has demonstrated that autistic individuals have higher rates of police contact, however, research has seldom explored the fundamental reasons for these interactions and how this might vary across international contexts. To remedy this, the Global Autism and Criminal Justice Consortium created and disseminated the Global Criminal Justice Survey. Descriptive statistics of survey respondents with and without police contact were compared to glean differential characteristics. Frequency and type of recent police interactions (within the last 5 years) among autistic individuals were also examined to better contextualize the reasons that autistic individuals encounter police. Study findings indicated that across a global sample (i.e., North America, Scandinavia, Europe, and Oceania) nearly half of all autistic individuals had an interaction with police and that those with a history of police contact were usually older, had higher educational qualifications, and were more likely to have a co-occurring mental health or developmental disorder. Among types of interactions, noncriminal encounters, such as welfare checks, traffic incidents, wandering, and behaviors associated with autism, were most common, followed by autistic individuals alleging a crime was committed against them. These findings offer important directions for future research and for targeted policy responses that can address the unique needs of autistic individuals within the justice system.

The racial composition of road users, traffic citations, and police stops

This paper exploits the potential of Global Positioning System datasets sourced from mobile phones to estimate the racial composition of road users, leveraging data from their respective Census block group. The racial composition data encompasses approximately 46 million trips in the Chicago metropolitan region. The research focuses on the relationship between camera tickets and racial composition of drivers vs. police stops for traffic citations and the racial composition in these locations. Black drivers exhibit a higher likelihood of being ticketed by automated speed cameras and of being stopped for moving violations on roads, irrespective of the proportion of White drivers present. The research observes that this correlation attenuates as the proportion of White drivers on the road increases. The citation rate measured by cameras better matches the racial composition of road users on the links with cameras than do stops by police officers. This study therefore presents an important contribution to understanding racial disparities in moving violation stops, with implications for policy interventions and social justice reforms.

Sexual harassment and implicit gender-career biases negatively impact women's life expectancy in the US: a state-level analysis, 2011-2019

BACKGROUND

Despite some gains, women continue to have less access to work and poorer experiences in the workplace, relative to men. The purpose of this study was to examine the relationships among women's life expectancy and two work-related factors, sexual harassment and gender-career biases.

METHOD

We examined the associations at the state level of analysis (and District of Columbia) in the US from 2011 to 2019 (n = 459) using archival data from various sources. Measures of the ratio of population to primary health providers, year, the percent of adults who are uninsured, the percent of residents aged 65 or older, and percent of residents who are Non-Hispanic White all served as controls.

RESULTS

Results of linear regression models showed that, after accounting for the controls, sexual harassment and gender-career biases among people in the state held significant, negative associations with women's life expectancy.

CONCLUSION

The study contributes to the small but growing literature showing that negative workplace experiences and bias against women in the workplace negatively impact women's health.

Local Legislation is Associated With Regional Transgender Attitudes

Using a newly developed measure of implicit transgender attitudes, we investigate the association between state-level antitransgender policies and individual-level attitudes about transgender people among residents. In a large sample of U.S. participants (N = 211,133), we find that individuals living in states with more discriminatory policies against transgender people (e.g., not allowing changes to one's gender identity on official identity papers) exhibited more negative implicit and explicit transgender attitudes. This pattern held after controlling for participant race and gender, as well as when looking only at cisgender participants. These findings extend prior work concerning how intergroup biases relate to regional characteristics such as legislation and do so in a novel and consequential context. This research also informs ongoing work concerning the role of policy-making and social norms on the development and expression of intergroup prejudice.

Filling in the white space: Spatial interpolation with Gaussian processes and social media data

Full national coverage below the state level is difficult to attain through survey-based data collection. Even the largest survey-based data collections, such as the CDC's Behavioral Risk Factor Surveillance System or the Gallup-Healthways Well-being Index (both with more than 300,000 responses p.a.) only allow for the estimation of annual averages for about 260 out of roughly U.S. 3,000 counties when a threshold of 300 responses per county is used. Using a relatively high threshold of 300 responses gives substantially higher convergent validity-higher correlations with health variables-than lower thresholds but covers a reduced and biased sample of the population. We present principled methods to interpolate spatial estimates and show that including large-scale geotagged social media data can increase interpolation accuracy. In this work, we focus on Gallup-reported life satisfaction, a widely-used measure of subjective well-being. We use Gaussian Processes (GP), a formal Bayesian model, to interpolate life satisfaction, which we optimally combine with estimates from low-count data. We interpolate over several spaces (geographic and socioeconomic) and extend these evaluations to the space created by variables encoding language frequencies of approximately 6 million geotagged Twitter users. We find that Twitter language use can serve as a rough aggregate measure of socioeconomic and cultural similarity, and improves upon estimates derived from a wide variety of socioeconomic, demographic, and geographic similarity measures. We show that applying Gaussian Processes to the limited Gallup data allows us to generate estimates for a much larger number of counties while maintaining the same level of convergent validity with external criteria (i.e., N = 1,133 vs. 2,954 counties). This work suggests that spatial coverage of psychological variables can be reliably extended through Bayesian techniques while maintaining out-of-sample prediction accuracy and that Twitter language adds important information about cultural similarity over and above traditional socio-demographic and geographic similarity measures. Finally, to facilitate the adoption of these methods, we have also open-sourced an online tool that researchers can freely use to interpolate their data across geographies.

Police decisions to found sexual assault cases: The influence of community-level factors and space

Previous research has examined the influence of individual- and case-level factors on police decisions in sexual assault cases, with little attention paid to community-level factors. This study examined the association between community-level factors and police decisions to found sexual assault cases. Founding is the first decision officers make and determines whether a case is investigated. An archival data set of N = 8015 sexual assaults reported to a Midwestern city police department was used. Ordinary least squares (OLS) regression was first used to examine the relationship between six community-level factors and founding rates within the city's 77 communities. Geographically weighted regression (GWR) was then used to examine whether these relationships varied by space. OLS results revealed communities with a greater proportion of Black residents, Latinx residents, Asian residents, and higher income had significantly higher founding rates. GWR results replicated these findings indicating these relationships varied significantly by space throughout the city. In contrast to the OLS, GWR results indicated communities farther from a rape crisis center had higher founding rates. Findings underscore the importance of analyzing localized effects and examining individual-, case-, and community-level factors on sexual assault case outcomes in the criminal legal system.

On the role of experience versus motivation in predicting the own-race effect

The other-race effect (ORE) is a longstanding phenomenon in experimental psychology, where recognition for same-race faces is superior than for other-race faces. The present research pits two competing theories of perceptual expertise and social motivation against each other to see which is the more robust predictor of the ORE. In Study 1, we measured Black and White participants' prior contact with individuals from the other-race (i.e. expertise) as well as their expected level of future interaction with other-race individuals (i.e. motivation). Of the two theories, anticipated interaction (i.e. motivation) emerged as a significant predictor of the ORE. Study 2 followed the same design, measuring motivation with a self-report assessment of how much participants are willing to have cross-race friendships. Here, neither experience nor motivation predicted the ORE, though an ORE was established. Differences in measures that assess motivation and the experience versus motivation debate are discussed.

Beyond stereotypes: Prejudice as an important missing force explaining group disparities

We comment on Cesario's assertion that social psychological intergroup research focuses solely on stereotypes, neglecting actual differences between groups to explain group disparities. This reasoning, however, misses yet another explaining force: In addition to stereotypes, ample laboratory and field research documents relationships between group disparities, discrimination, and prejudice, which cannot be explained by people's accurate judgments of real-world group differences.