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Chronicling the history and personal experiences of African Americans on the road from the advent of the automobile through the seismic changes of the 1960s and beyond – Driving While Black explores the background of a phrase rooted in realities that have been a part of the African American experience for hundreds of years – told in part through the stories of the people who lived through it.

\"Bubba Wallace, an American automobile racing driver, is the most successful African American driver active in NASCAR (the National Association for Stock Car Auto Racing).\"(World Book Online Behind the Headlines) Read more about American race driver, Bubba Wallace.

We assessed racial disparities in policing in the United States by compiling and analysing a dataset detailing nearly 100 million traffic stops conducted across the country. We found that black drivers were less likely to be stopped after sunset, when a ‘veil of darkness’ masks one’s race, suggesting bias in stop decisions. Furthermore, by examining the rate at which stopped drivers were searched and the likelihood that searches turned up contraband, we found evidence that the bar for searching black and Hispanic drivers was lower than that for searching white drivers. Finally, we found that legalization of recreational marijuana reduced the number of searches of white, black and Hispanic drivers—but the bar for searching black and Hispanic drivers was still lower than that for white drivers post-legalization. Our results indicate that police stops and search decisions suffer from persistent racial bias and point to the value of policy interventions to mitigate these disparities. Pierson et al. compiled and analysed a dataset detailing nearly 100 million traffic stops conducted across the United States, finding evidence of persistent racial bias against black and Hispanic drivers in police stops and search decisions.

Background African ancestry is a significant risk factor for advanced prostate cancer (PCa). Mortality rates in sub-Saharan Africa are 2.5-fold greater than global averages. However, the region has largely been excluded from the benefits of whole genome interrogation studies. Additionally, while structural variation (SV) is highly prevalent, PCa genomic studies are still biased towards small variant interrogation. Methods Using whole genome sequencing and best practice workflows, we performed a comprehensive analysis of SVs for 180 (predominantly Gleason score ≥ 8) prostate tumours derived from 115 African, 61 European and four ancestrally admixed patients. We investigated the landscape and relationship of somatic SVs in driving ethnic disparity (African versus European), with a focus on African men from southern Africa. Results Duplication events showed the greatest ethnic disparity, with a 1.6- (relative frequency) to 2.5-fold (count) increase in African-derived tumours. Furthermore, we found duplication events to be associated with CDK12 inactivation and MYC copy number gain, and deletion events associated with SPOP mutation. Overall, African-derived tumours were 2-fold more likely to present with a hyper-SV subtype. In addition to hyper-duplication and deletion subtypes, we describe a new hyper-translocation subtype. While we confirm a lower TMPRSS2-ERG fusion-positive rate in tumours from African cases (10% versus 33%), novel African-specific PCa ETS family member and TMPRSS2 fusion partners were identified, including LINC01525, FBXO7 , GTF3C2 , NTNG1 and YPEL5 . Notably, we found 74 somatic SV hotspots impacting 18 new candidate driver genes, with CADM2 , LSAMP , PTPRD , PDE4D and PACRG having therapeutic implications for African patients. Conclusions In this first African-inclusive SV study for high-risk PCa, we demonstrate the power of SV interrogation for the identification of novel subtypes, oncogenic drivers and therapeutic targets. Identifying a novel spectrum of SVs in tumours derived from African patients provides a mechanism that may contribute, at least in part, to the observed ethnic disparity in advanced PCa presentation in men of African ancestry.

Are there conditions under which minority bureaucrats are less likely to provide active representation? The authors address this question by testing the link between passive and active representation for race in a police department and in the particular instance of racial profiling. Literature from three areas-racial profiling, representative bureaucracy, and police socialization-is brought together. The findings support the hypothesis that organizational socialization can hinder the link between passive and active representation. Furthermore, the authors find that the presence of black police officers is related to an increase in racial profiling in the division. This finding was unexpected and raises several important questions regarding active representation and race.

This paper provides new evidence on racial profiling using information on the race of both motorists and officers. Extending the model of Knowles, Persico, and Todd (2001), we develop a new test for distinguishing between preference-based and statistical discrimination. Our test is based on the notion that if search decisions are driven purely by statistical discrimination, then they should be independent of officer race. Our results, by contrast, demonstrate that officers are more likely to search if officer race and driver race differ. We then investigate and rule out two alternative explanations for our findings.

Police checking for illegal drugs are much more likely to search the vehicles of African‐American motorists than those of white motorists. This paper develops a model of police and motorist behavior that suggests an empirical test for distinguishing whether this disparity is due to racial prejudice or to the police’s objective to maximize arrests. When applied to vehicle search data from Maryland, our test results are consistent with the hypothesis of no racial prejudice against African‐American motorists. However, if police have utility only for searches yielding large drug finds, then our analysis would suggest bias against white drivers. The model’s prediction regarding nonrace characteristics is also largely supported by the data.

Objectives. We compared reported safety belt use, for both drivers and passengers, among teenagers with learner’s permits, provisional licenses, and unrestricted licenses in states with primary or secondary enforcement of safety belt laws. Methods. Our data source was the 2006 National Young Driver Survey, which included a national representative sample of 3126 high-school drivers. We used multivariate, log-linear regression analyses to assess associations between safety belt laws and belt use. Results. Teenaged drivers were 12% less likely to wear a safety belt as drivers and 15% less likely to wear one as passengers in states with a secondary safety belt law than in states with a primary law. The apparent reduction in belt use among teenagers as they progressed from learner to unrestricted license holder occurred in only secondary enforcement states. Groups reporting particularly low use included African American drivers, rural residents, academically challenged students, and those driving pickup trucks. Conclusions. The results provided further evidence for enactment of primary enforcement provisions in safety belt laws because primary laws are associated with higher safety belt use rates and lower crash-related injuries and mortality.

A few years ago, the global consulting firm McKinsey and Company began issuing a series of increasingly urgent reports concerning “automation” and the future of work. Defining automation broadly as artificial intelligence and “other digital technologies,” the company promised in its reports that it could advise companies how they might prepare. Amidst this flurry of publication, McKinsey produced several articles specifically on the theme of “The Future of Work in Black America.” With “a new and proprietary data set”—a data set so proprietary readers were not privileged to see it—McKinsey claimed that “automation” would hurt the job prospects of Black Americans, and in particular Black men, more deeply and more broadly than any other demographic group in the United States. The jobs Black people held, McKinsey seemed to believe, were precisely those best performed by robots. For McKinsey's analysts, this conclusion was all but obvious when one considered, first, the racist exclusion of Black Americans from the resources of society, and second, the levels of education required to obtain the jobs Black people in America disproportionately hold, like “truck drivers, food service workers, and office clerks.”