Political ideology moderates White Americans’ reactions to racial demographic change

An emerging body of research finds that exposure to the shifting racial demographics of a nation can engender concerns about racial group status among members of the dominant racial group. The present work revisits this finding, probing a broader set of group status concerns than has been examined in most past research. Three experiments exposed four samples of White Americans to racial demographic information or race-neutral control information, then assessed their perception that the relative status of racial groups in the nation would change and the extent to which they were alarmed by such a status shift—that is, status threat. Consistent with past work, what we now term perceived status change increased in response to salient racial demographics information, relative to race-neutral control information, irrespective of participants’ political ideology. Departing from past work, however, the perceived threat associated with changing racial demographics was moderated by political ideology. Specifically, politically conservative White participants demonstrated high levels of group status threat in the neutral control condition that either increased (Study 1a, Study 2) or stayed equally high (Study 1b, Study 3) after exposure to information about a racial shift. In contrast, in all studies, politically liberal White participants demonstrated a modest level of group status threat in the control condition that was attenuated upon exposure to a racial shift. Taken together, these results suggest a polarization of responses to the increasing racial diversity of the nation, one that was not observed even just a few years ago.

Racial demographics explain the link between racial disparities in traffic stops and county-level racial attitudes

Disparities in the treatment of Black and White Americans in police stops are pernicious and widespread. We examine racial disparities in police traffic stops by leveraging data on traffic stops from hundreds of U.S. counties from the Stanford Open Policing Project and corresponding county-level data on implicit and explicit racial attitudes from the Project Implicit research website. We find that Black-White traffic stop disparities are associated with county-level implicit and explicit racial attitudes and that this association is attributable to racial demographics: counties with a higher proportion of White residents had larger racial disparities in police traffic stops. We also examined racial disparities in several post-stop outcomes (e.g., arrest rates) and found that they were not systematically related to racial attitudes, despite evidence of disparities. These findings indicate that racial disparities in counties’ traffic stops are reliably linked to counties’ racial attitudes and demographic compositions.

Corresponding Makeup of the Art Market of Erie, Pennsylvania with Regional Success

The art market is a sector of the economy that holds great significance in terms of composition and economic impact. Information pertaining to the for profits of the market is often difficult to obtain, leading to a lack of research in the field. A Colorado based report explored the for profit arts of the state using EMSI data to overcome for profits lack of transparency. This report presented the art market of Colorado as having a major economic impact and served as a foundation for further case studies of the art economy within the nation. Additionally, though diversity in markets generally corresponds with economic success, the racial demographics within the art market as a whole show the market to be predominantly white. This paper consists of four sections specialized to answer the question, “To what extent does the makeup of the art economy of Erie, Pennsylvania correspond with regional success?”. First, I review the current literature regarding arts and their relationship with economics. The second section is developing a multi-pronged replicable methodology geared towards city level analysis that corresponds the makeup of a market to its economic impact. The third section analyzes the findings the methodology provides, and the final section explores the implications this study has in regards to the city investigated and others in the field of art economics moving forward.

Black Disparities in Targeted Therapy Clinical Trials – A Call for Future Reset

Studies show marked disparities in the relative risk of cancer death between Black Americans and White Americans even after adjusting for the stage at diagnosis and age. This may be explained by disparities in different aspects of cancer care including providing equal screening opportunities, availability of proper treatment options and inclusivity in clinical trials. To our knowledge, our study is the first descriptive study on Black disparities in targeted therapy clinical trials. We collected data on Black inclusivity from pivotal clinical trials as well as trials of special interest involving targeted therapies in some of the commonly encountered cancers. Our results show that most targeted therapy trials included in our review were multinational including some participating countries with very few or no Blacks and therefore had very poor Black representation with an average of around 1-3%. Also, some trials lacked transparent data on the racial demographics raising concerns on the generalizability of data when extrapolated to treat the Black population. We have reviewed existing literature on differences in cancer biology and host biology depending on the race and end with suggestions to improve Black inclusivity in clinical trials.

Predictive modeling of COVID-19 case growth highlights evolving racial and ethnic risk factors in Tennessee and Georgia

IntroductionThe SARS-CoV-2 (COVID-19) pandemic has exposed the need to understand the risk drivers that contribute to uneven morbidity and mortality in US communities. Addressing the community-specific social determinants of health (SDOH) that correlate with spread of SARS-CoV-2 provides an opportunity for targeted public health intervention to promote greater resilience to viral respiratory infections.MethodsOur work combined publicly available COVID-19 statistics with county-level SDOH information. Machine learning models were trained to predict COVID-19 case growth and understand the social, physical and environmental risk factors associated with higher rates of SARS-CoV-2 infection in Tennessee and Georgia counties. Model accuracy was assessed comparing predicted case counts to actual positive case counts in each county.ResultsThe predictive models achieved a mean R2 of 0.998 in both states with accuracy above 90% for all time points examined. Using these models, we tracked the importance of SDOH data features over time to uncover the specific racial demographic characteristics strongly associated with COVID-19 incidence in Tennessee and Georgia counties. Our results point to dynamic racial trends in both states over time and varying, localized patterns of risk among counties within the same state. For example, we find that African American and Asian racial demographics present comparable, and contrasting, patterns of risk depending on locality.ConclusionThe dichotomy of demographic trends presented here emphasizes the importance of understanding the unique factors that influence COVID-19 incidence. Identifying these specific risk factors tied to COVID-19 case growth can help stakeholders target regional interventions to mitigate the burden of future outbreaks.

Neighborhood racial demographics predict infants’ neural responses to people of different races

Early in life, greater exposure to diverse people can change the tendency to prefer one’s own social group. For instance, infants from racially diverse environments show less preference for their own-race (ingroup) over other-race (outgroup) faces than infants from racially homogeneous environments. Yet how social environment changes ingroup versus outgroup demarcation in infancy is unclear. A commonly held assumption is that early emerging ingroup preference is based on an affective process: feeling more comfortable with familiar ingroup than unfamiliar outgroup members. However, other processes may also underlie ingroup preference: Infants may attend more to ingroup than outgroup members and/or mirror the actions of ingroup over outgroup individuals. By aggregating 7- to 12-month-old infants’ electroencephalography (EEG) activity across three studies, we disambiguate these different processes in the EEG oscillations of preverbal infants according to social environment. White infants from more racially diverse neighborhoods exhibited greater frontal theta oscillation (an index of top-down attention) and more mu rhythm desynchronization (an index of motor system activation and potentially neural mirroring) to racial outgroup individuals than White infants from less racially diverse neighborhoods. Neighborhood racial demographics did not relate to White infants’ frontal alpha asymmetry (a measure of approach-withdrawal motivation) toward racial outgroup individuals. Racial minority infants showed no effects of neighborhood racial demographics in their neural responses to racial outgroup individuals. These results indicate that neural mechanisms that may underlie social bias and prejudices are related to neighborhood racial demographics in the first year of life.

Two Decades of Ecstasy: Shifting Demographic Trends in Decedents using MDMA

Deaths with a toxicology finding of the party drug, 3,4-Methylenedioxymethamphetamine (MDMA), over the 20-year period from 2000-2019 in San Francisco are presented to identify shifting demographic trends. Of the 148 cases, 129 (87.2%) were male with mean and median ages of 30 and 28, respectively. The most common manner of death (MOD) in males was homicide (65 of 129) and accident (49 of 129). The most common MOD in females was accident (15 of 19). Regarding racial demographics, Black homicide deaths accounted for 59 of 67 (88.1%) of total homicides. The most prevalent cause of death for homicides was gunshot wounds (63 of 67, 94.0%). Homicide prevalence was high in the first decade of the study (53 of 88, 60.2%), sharply dropping off after 2011. White accidental deaths made up most of the accidental deaths (45 of 64, 70.3%). Since 2015, accidental deaths with MDMA began to rise (40 of 60, 66.7%), most with other coingestants. MDMA concentrations (median, mean ± SD) between homicide (290, 450 ± 490 ng/mL) and accidental (250, 680 ± 1120 ng/mL) deaths were similar. MDMA concentrations were elevated in central blood compared to peripheral blood from unmatched cases. MDMA was detected in a variety of decedents during the two decades, with primarily young Black male gunshot wound homicide victims in the first decade and primarily young White male accidental polydrug victims in the second decade. This study demonstrates that MDMA is no longer confined to a party setting, but can also be found in different socio-economic strata, including its association with violent homicidal deaths.