Nigger : A Critical Race Realist Analysis of the N-word within Hate Crimes Law

On a 2005 summer morning, Nicholas “Fat Nick” Minucci (White) beat Glenn Moore (Black) with a baseball bat and robbed him. During the assault, Minucci repeatedly screamed the N-word. At trial, Minucci’s attorney argued that he had not committed a hate crime. The essence of the defense’s argument was that Minucci’s use of the N-word while assaulting and robbing Moore was not indicative of any bias or prejudice. The defense went on to indicate that Minucci had Black friends, was immersed in Black culture, and employed the N-word as part of his everyday vocabulary. Two Black men—Gary Jenkins (hip hop music producer) and Randall Kennedy (Harvard Law Professor)—testified that the N-word is not necessarily a racial epithet. In this article, we systematically analyze this assessment of the N-word within hate crimes law. We employ a Critical Race Realist methodology toward this end. In doing so, we 1) systematically analyze Black and White usage of the N-word within popular culture (i.e., comedy, rap music, and spoken word) and 2) reconcile these findings with research on implicit (unconscious) race bias. In sum, we argue that whereas many Blacks may use the N-word, the usage of Whites immersed in Black culture is nil. Furthermore, we find that many Whites harbor implicit anti-Black biases and such biases predict racial hostility and the use of racial epithets. Consequently, within the realm of hate crimes law, courts should presume racial animus where a White person uses the N-word while committing a crime against a Black person. Furthermore, despite high rates of Black usage of the N-word and high rates of implicit anti-Black biases among Blacks, a law of intra-racial hate crimes among Blacks predicated upon their usage of the N-word would be fruitless. This is so given that the N-word means something differently when used intra-racially among Blacks than when directed at a Blacks from Whites

Personality, antisocial behavior, and aggression: A meta-analytic review

Purpose Although the relationship between personality and antisocial behaviors has been widely examined and empirically supported in the psychological literature, relatively few efforts to study this relationship have appeared in mainstream criminology.Materials and methods The current study focuses on the domains and facets from the Five-Factor Model of personality, and how they are related to antisocial and aggressive behaviors.Results The meta-analytic findings indicate that the higher-order traits of Agreeableness, Conscientiousness, and Neuroticism demonstrate the most consistent relationships with these outcomes. At the lower-order trait level, straightforwardness, compliance, and altruism from Agreeableness, deliberation from Conscientiousness, angry hostility from Neuroticism, and warmth from Extraversion were among the strongest correlates.Conclusion The findings are consistent with previous meta-analytic studies, thus providing compelling support for their utility in understanding antisocial and aggressive behavior. As such, they should be afforded greater theoretical and empirical attention within criminology.

The Impact Of Missing Risk Factor Data On Semiparametric Group-Based Trajectory Models

Purpose: To investigate how missing data (Missing Completely at Random [MCAR] vs. Missing Not at Random [MNAR]) on risk factors can impact trajectory solutions (i.e., latent class probabilities) and coefficient estimates capturing the relationship between covariates and trajectory group solutions using a semiparametric group-based trajectory modeling (GBTM) approach. Methods: To address this issue, we conducted a systematic investigation using Monte Carlo simulation. Data were generated from a population with known growth parameters and risk factors. Observations for risk factors were then systematically deleted in a way that reflects key missing data assumptions (MCAR and MNAR). Models were then estimated to test the sensitivity of the estimates to each missing data scenario. Results: Two key findings emerged: (1) trajectory solutions were largely unaffected by missing data on risk factors; and, (2) there was some degree of bias in estimating relationships between risk factors and trajectory group membership when data were missing on those risk factors. Conclusions: GBTM may be useful for testing etiological explanations of long-term patterns of offending. Missing data on risk factors poses a threat to this approach, however