Geographic Variation in the Black-Violence Stereotype

2018 ◽  
Vol 10 (3) ◽  
pp. 287-294 ◽  
Author(s):  
David J. Johnson ◽  
William J. Chopik
Keyword(s):  
Violent Crime ◽  
Black People ◽  
Violent Behavior ◽  
State Level ◽  
The United States ◽  
Crime Rates ◽  
Racial Groups ◽  
White People ◽  
Implicit Stereotypes ◽  
Implicit And Explicit

The stereotype that Blacks are violent is pervasive in the United States. Yet little research has examined whether this stereotype is linked to violent behavior from members of different racial groups. We examined how state-level violent crime rates among White and Black Americans predicted the strength of the Black-violence stereotype using a sample of 348,111 individuals from the Project Implicit website. State-level implicit and explicit stereotypes were predicted by crime rates. States where Black people committed higher rates of violent crime showed a stronger Black-violence stereotype, whereas states where White people committed higher rates of violent crime showed a weaker Black-violence stereotype. These patterns were stronger for explicit stereotypes than implicit stereotypes. We discuss the implications of these findings for the development and maintenance of stereotypes.

Club convergence of crime rates in the United States of America

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kolawole Ogundari
Keyword(s):  
Violent Crime ◽  
Property Crime ◽  
The United States ◽  
Crime Rates ◽  
Community Level ◽  
Club Convergence ◽  
Content Type ◽  
Level Data ◽  
Convergence Club ◽  
Over Time

Purpose The cyclical behavior of US crime rates reflects the dynamics of crime in the country. This paper aims to investigate the US's club convergence of crime rates to provide insights into whether the crime rates increased or decreased over time. The paper also analyzes the factors influencing the probability of states converging to a particular convergence club of crime. Design/methodology/approach The analysis is based on balanced panel data from all 50 states and the district of Columbia on violent and property crime rates covering 1976–2019. This yields a cross-state panel of 2,244 observations with 55 time periods and 51 groups. In addition, the author used a club clustering procedure to investigate the convergence hypothesis in the study. Findings The empirical results support population convergence of violent crime rates. However, the evidence that supports population convergence of property crime rates in the study is not found. Further analysis using the club clustering procedure shows that property crime rates converge into three clubs. The existence of club convergence in property crime rates means that the variation in the property crime rates tends to narrow among the states within each of the clubs identified in the study. Analysis based on an ordered probit model identifies economic, geographic and human capital factors that significantly drive the state's convergence club membership. Practical implications The central policy insight from these results is that crime rates grow slowly over time, as evident by the convergence of violent crime and club convergence of property crime in the study. Moreover, the existence of club convergence of property crime is an indication that policies to mitigate property crime might need to target states within each club. This includes the efforts to use state rather than national crime-fighting policies. Social implications As crimes are committed at the local level, this study's primary limitation is the lack of community-level data on crime and other factors considered. Analysis based on community-level data might provide a better representation of crime dynamics. However, the author hopes to consider this as less aggregated data are available to use in future research. Originality/value The paper provides new insights into the convergence of crime rates using the club convergence procedure in the USA. This is considered an improvement to the methods used in the previous studies.

Abstract 076: Longitudinal Trajectories And Predictors Of County-level Cardiovascular Mortality In The United States (1980-2014)

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Shreya Rao ◽  
Amy E Hughes ◽  
Colby Ayers ◽  
Sandeep R Das ◽  
Ethan A Halm ◽  
...  
Keyword(s):  
Violent Crime ◽  
High Mortality ◽  
Multinomial Logistic Regression ◽  
The United States ◽  
Crime Rates ◽  
Social Characteristics ◽  
Mortality Data ◽  
County Level ◽  
Obesity And Diabetes ◽  
Health Factors

Introduction: CV mortality has declined over 4 decades in the U.S. However, whether declines have been uniformly experienced across U.S. counties, and predictors of CV mortality trajectory are not known. Methods: County-level mortality data from 1980-2014 was obtained from the National Center for Health Statistics. We used a ClustMix approach to identify 3 distinct county phenogroups based on mortality trajectory. Adjusted multinomial logistic regression models were constructed to evaluate the associations between county-level characteristics (demographic, social, and health status) and CV mortality trajectory-based phenogroups. Results: Among 3,133 counties, there were parallel declines in CV mortality in all groups (Fig.1A). High-mortality counties were located in the South and parts of the Ohio and Mississippi River valleys (Fig. 1B). County phenogroups varied significantly in social characteristics such as non-white proportion (low vs. high mortality: 12% vs. 27%), high-school education (11% vs. 20%), and violent crime rates (.01 vs. 0.3/100 population). Disparities in health factors were also observed with higher rates of smoking, obesity, and diabetes in the high (vs. low) mortality groups. A substantial collinearity was observed between social and health factors. In adjusted analysis, social, environmental, and health characteristics explained 56% variance in the county-level CV mortality trajectory. Education status (OR [95% CI]=12.4 [9.4-16.3]), violent crime rates (OR [95% CI] =1.6 [1.3-1.9]), and smoking (OR [95% CI] = 3.9 [3.1- 4.9]) were the strongest predictors of high mortality trajectory phenogroup membership (ref: low mortality). Conclusions: Despite a decline in CV mortality, disparities at the county-level have persisted over the past 4 decades largely driven by differences in social characteristics and smoking prevalence. This highlights the need for multi-domain interventions focusing on safety, education and public health to improve county-level disparities in CV health.

scholarly journals Introduction: African Americans: Official and Unofficial Violence in America

2020 ◽  
pp. 002193472097008
Author(s):  
Molefi Kete Asante
Keyword(s):  
African Americans ◽  
Black Men ◽  
Police Officers ◽  
Black People ◽  
Black Population ◽  
The United States ◽  
Active Imagination ◽  
White People ◽  
Control Forces

In this essay the author introduces the emergence of the paddy rollers as control forces to contain the black population during the enslavement of Africans in the United States. Soon after the end of the Civil War the police forces took over the activities that had been the purvey of the paddy rollers: keeping black people in place and out of the way of white people. However, the resistance to abuse, torture, and murder was never far from the active imagination and reality of African Americans who maintained their own humanity. Tracing, in a limited fashion, how the biologically unscientific race became the premise for racism and the attacks on black people by police officers who often took their perceptions of blacks, especially black men, as negative and inferior from the systemic and institutional character of the society’s understanding of superior and inferior humans. This, according to the author, is at the base of hatred, discrimination, and lynching of African Americans in current and previous occasions. He illustrates this by discussing the case of Mary Turner who was killed in the early part of the 20th century for objecting to white mob attacks on her husband.

scholarly journals Building the Digitally Gated Community: The Case of Nextdoor

2019 ◽  
Vol 17 (1/2) ◽  
pp. 111-117 ◽  
Author(s):  
Rahim Kurwa
Keyword(s):  
United States ◽  
Black People ◽  
The United States ◽  
Gated Communities ◽  
Gated Community ◽  
White People ◽  
Fair Housing ◽  
History Of ◽  
The Many ◽  
Residential Space

The neighborhood is a historic and contemporary site of the assertion of white racial and economic domination, particularly over Black people. Although there is strong evidence that whites continue to prefer racially segregated neighborhoods, fifty years of fair housing jurisprudence has made it more difficult to openly bar non-white residents. Among the many strategies used to protect white domination of residential space is the coordinated surveillance and policing of non-white people. In this paper, I show how Nextdoor, a neighborhood-based social network, has become an important platform for the surveillance and policing of race in residential space, enabling the creation of what I call digitally gated communities. First, I describe the history of the platform and the forms of segregation and surveillance it has supplemented or replaced. Second, I situate the platform in a broader analysis of carcerality as a mode and logic of regulating race in the United States. Third, using examples drawn from public reports about the site, I illustrate how race is surveilled and policed in the context of gentrification and integration. Finally, I discuss implications, questions, and future issues that might arise on the platform.

scholarly journals Infectious Disease Prevalence, Not Race Exposure, Predicts Both Implicit and Explicit Racial Prejudice Across the United States

2019 ◽  
Vol 11 (3) ◽  
pp. 345-355 ◽  
Author(s):  
Brian A. O’Shea ◽  
Derrick G. Watson ◽  
Gordon D. A. Brown ◽  
Corey L. Fincher
Keyword(s):  
Infectious Disease ◽  
United States ◽  
Black Americans ◽  
State Level ◽  
The United States ◽  
Racial Prejudice ◽  
White Americans ◽  
Disease Rates ◽  
Prejudicial Attitudes ◽  
Implicit And Explicit

What factors increase racial prejudice? Across the United States, increased exposure to Black Americans has been hypothesized to increase White Americans’ prejudicial attitudes toward Black Americans. Here we test an alternative explanation: People living in regions with higher infectious disease rates have a greater tendency to avoid out-groups because such avoidance reduces their perceived likelihood of contracting illnesses. Consistent with this parasite-stress hypothesis, we show that both White and Black individuals ( N > 77,000) living in U.S. states in which disease rates are higher display increased implicit (automatic) and explicit (conscious) racial prejudice. These results survived the inclusion of several individual- and state-level controls previously used to explain variability in prejudice. Furthermore, showing disease-related primes to White individuals with strong germ aversion increased their explicit, but not implicit, anti-Black/pro-White prejudice. Domestic out-groups, not just foreigners, may therefore experience increased overt forms of prejudice when disease rates are high.

scholarly journals Racial and Ethnic Disparities in COVID-19 Outcomes: Social Determination of Health

2020 ◽  
Vol 17 (21) ◽  
pp. 8115 ◽  
Author(s):  
Samuel Raine ◽  
Amy Liu ◽  
Joel Mintz ◽  
Waseem Wahood ◽  
Kyle Huntley ◽  
...  
Keyword(s):  
Black People ◽  
National Level ◽  
Ethnic Disparities ◽  
State Level ◽  
The United States ◽  
Racial And Ethnic Disparities ◽  
Incidence And Mortality ◽  
The Social ◽  
Social Determination Of Health

As of 18 October 2020, over 39.5 million cases of coronavirus disease 2019 (COVID-19) and 1.1 million associated deaths have been reported worldwide. It is crucial to understand the effect of social determination of health on novel COVID-19 outcomes in order to establish health justice. There is an imperative need, for policy makers at all levels, to consider socioeconomic and racial and ethnic disparities in pandemic planning. Cross-sectional analysis from COVID Boston University’s Center for Antiracist Research COVID Racial Data Tracker was performed to evaluate the racial and ethnic distribution of COVID-19 outcomes relative to representation in the United States. Representation quotients (RQs) were calculated to assess for disparity using state-level data from the American Community Survey (ACS). We found that on a national level, Hispanic/Latinx, American Indian/Alaskan Native, Native Hawaiian/Pacific Islanders, and Black people had RQs > 1, indicating that these groups are over-represented in COVID-19 incidence. Dramatic racial and ethnic variances in state-level incidence and mortality RQs were also observed. This study investigates pandemic disparities and examines some factors which inform the social determination of health. These findings are key for developing effective public policy and allocating resources to effectively decrease health disparities. Protective standards, stay-at-home orders, and essential worker guidelines must be tailored to address the social determination of health in order to mitigate health injustices, as identified by COVID-19 incidence and mortality RQs.

It's Still Slavery by Another Name

2020 ◽  
pp. 40-50
Author(s):  
Michael D. Yates
Keyword(s):  
Black Men ◽  
Social Distance ◽  
Black People ◽  
Daily Life ◽  
Black Americans ◽  
Well Being ◽  
The United States ◽  
White People ◽  
Men And Women ◽  
Black And White

As the long history, right to the present day, of police and vigilante violence against black people has shown with great clarity, the racial chasm between black and white people in the United States lives on. A few black men and women have climbed into the 1 percent, and a sizable African-American middle class now exists. But by every measure of social well-being, black Americans fare much worse than their white counterparts. Just as for the economic, political, and social distance between capitalists and workers, so too is there a differential between black and white people, for these same interconnected components of daily life continue because of the way our system is structured.

Counting Guns

2002 ◽  
Vol 26 (4) ◽  
pp. 699-708
Author(s):  
Gordon Wood ◽  
Robert Churchill ◽  
Edward Cook ◽  
James Lindgren ◽  
Wilbur Miller ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Social Science ◽  
Statistical Methods ◽  
Violent Crime ◽  
The United States ◽  
Real Income ◽  
Crime Rates ◽  
Gun Control ◽  
Gun Laws ◽  
The Impact

At the fall 2001 Social Science History Association convention in Chicago, the Crime and Justice network sponsored a forum on the history of gun ownership, gun use, and gun violence in the United States. Our purpose was to consider how social science historians might contribute nowand in the future to the public debate over gun control and gun rights. To date, we have had little impact on that debate. It has been dominated by mainstream social scientists and historians, especially scholars such as Gary Kleck, John Lott, and Michael Bellesiles, whose work, despite profound flaws, is politically congenial to either opponents or proponents of gun control. Kleck and Mark Gertz (1995), for instance, argue on the basis of their widely cited survey that gun owners prevent numerous crimes each year in theUnited States by using firearms to defend themselves and their property. If their survey respondents are to be believed, American gun owners shot 100,000 criminals in 1994 in selfdefense–a preposterous number (Cook and Ludwig 1996: 57–58; Cook and Moore 1999: 280–81). Lott (2000) claims on the basis of his statistical analysis of recent crime rates that laws allowing private individuals to carry concealed firearms deter murders, rapes, and robberies, because criminals are afraid to attack potentially armed victims. However, he biases his results by confining his analysis to the years between 1977 and 1992, when violent crime rates had peaked and varied little from year to year (ibid.: 44–45). He reports only regression models that support his thesis and neglects to mention that each of those models finds a positive relationship between violent crime and real income, and an inverse relationship between violent crime and unemployment (ibid.: 52–53)–implausible relationships that suggest the presence of multicollinearity, measurement error, or misspecification. Lott then misrepresents his results by claiming falsely that statistical methods can distinguish in a quasi-experimental way the impact of gun laws from the impact of other social, economic, and cultural forces (ibid.: 26, 34–35; Guterl 1996). Had Lott extended his study to the 1930s, the correlation between gun laws and declining homicide rates that dominates his statistical analysis would have disappeared. An unbiased study would include some consideration of alternative explanations and an acknowledgment of the explanatory limits of statistical methods.

scholarly journals The Association Between State-Level Racial Attitudes Assessed From Twitter Data and Adverse Birth Outcomes: Observational Study (Preprint)

2019 ◽  
Author(s):  
Thu T Nguyen ◽  
Nikki Adams ◽  
Dina Huang ◽  
M Maria Glymour ◽  
Amani M Allen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Birth Weight ◽  
Ethnic Minorities ◽  
Birth Outcomes ◽  
Black People ◽  
State Level ◽  
Adverse Birth Outcomes ◽  
White People ◽  
Machine Learning Model ◽  
Hispanic White

BACKGROUND In the United States, racial disparities in birth outcomes persist and have been widening. Interpersonal and structural racism are leading explanations for the continuing racial disparities in birth outcomes, but research to confirm the role of racism and evaluate trends in the impact of racism on health outcomes has been hampered by the challenge of measuring racism. Most research on discrimination relies on self-reported experiences of discrimination, and few studies have examined racial attitudes and bias at the US national level. OBJECTIVE This study aimed to investigate the associations between state-level Twitter-derived sentiments related to racial or ethnic minorities and birth outcomes. METHODS We utilized Twitter’s Streaming application programming interface to collect 26,027,740 tweets from June 2015 to December 2017, containing at least one race-related term. Sentiment analysis was performed using support vector machine, a supervised machine learning model. We constructed overall indicators of sentiment toward minorities and sentiment toward race-specific groups. For each year, state-level Twitter-derived sentiment data were merged with birth data for that year. The study participants were women who had singleton births with no congenital abnormalities from 2015 to 2017 and for whom data were available on gestational age (n=9,988,030) or birth weight (n=9,985,402). The main outcomes were low birth weight (birth weight ≤2499 g) and preterm birth (gestational age <37 weeks). We estimated the incidence ratios controlling for individual-level maternal characteristics (sociodemographics, prenatal care, and health behaviors) and state-level demographics, using log binomial regression models. RESULTS The accuracy for identifying negative sentiments on comparing the machine learning model to manually labeled tweets was 91%. Mothers living in states in the highest tertile for negative sentiment tweets referencing racial or ethnic minorities had greater incidences of low birth weight (8% greater, 95% CI 4%-13%) and preterm birth (8% greater, 95% CI 0%-14%) compared with mothers living in states in the lowest tertile. More negative tweets referencing minorities were associated with adverse birth outcomes in the total population, including non-Hispanic white people and racial or ethnic minorities. In stratified subgroup analyses, more negative tweets referencing specific racial or ethnic minority groups (black people, Middle Eastern people, and Muslims) were associated with poor birth outcomes for black people and minorities. CONCLUSIONS A negative social context related to race was associated with poor birth outcomes for racial or ethnic minorities, as well as non-Hispanic white people.

The Impact of State Firearm Laws on Homicide Rates among Black and White Populations in the United States, 1991–2016

2019 ◽  
Vol 44 (4) ◽  
pp. 232-240 ◽  
Author(s):  
Anita Knopov ◽  
Michael Siegel ◽  
Ziming Xuan ◽  
Emily F Rothman ◽  
Shea W Cronin ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Black People ◽  
State Level ◽  
The United States ◽  
Homicide Rates ◽  
Black And White ◽  
Author Identification ◽  
Background Check ◽  
Black Populations ◽  
The Impact

Abstract This study aimed to investigate the potential differential effects of state-level firearm laws on black and white populations. Using a panel design, authors examined the relationship between state firearm laws and homicide victimization rates among white people and black people in 39 states during the period between 1991 and 2016. Authors modeled homicide rates using linear regression with year and state fixed effects and controlled for a range of time-varying, state-level factors. Results showed that universal background check laws and permit requirement laws were associated with lower homicide rates among both white and black populations, and “shall issue” laws were associated with higher homicide rates among both white and black populations. Laws that prohibit firearm possession among people convicted of a violent misdemeanor or require relinquishment of firearms by people with a domestic violence restraining order were associated with lower black homicide rates, but not with white homicide rates. Author identification of heterogeneity in the associations between state firearm laws and homicide rates among different racial groups has implications for reducing racial health disparities.

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