What accounts for the steady decline in misdemeanour arrest rates in the United States following their peak in the mid-1990s? This article links the fluctuation in low-level law enforcement to changes in the budget and staffing resources cities devoted to policing. This materialist explanation contrasts with accounts that emphasize policy changes like the adoption of community policing. Dynamic panel regression analyses of 940 municipalities indicate low-level arrest rates declined most in places that reduced their police expenditure and personnel, net of crime and other controls. The adoption of community policing was unrelated to misdemeanour arrests. Findings suggest lawmakers should consider how increasing police budgets or police force sizes will likely be accompanied by increases in misdemeanour arrests and their attendant harms.

No abstract

Questions remain on whether the UCR constitutes a legitimate source for analyzing hate crime. While a handful of studies have attempted to uncover the law enforcement characteristics associated with reporting hate crime, scholars have yet to triangulate official data with other sources, namely the NCVS. In this study, I replicate past UCR-NCVS convergence analyses on hate crime incidents, determining whether these series converge and if they do so across different forms of bias motivation. Using 18 years of data from 2003 through 2020 at a national level, results indicate mixed support for convergence, drawing implications for research and policy.

What makes police departments change their practices? Do they transform in isolation, or do they mimic their neighbors? Combining insights from organizational theory and urban sociology, the authors argue that organizational change diffuses, in part, through physically proximate institutions. They apply this theory to an underexamined trend: the decline of misdemeanor arrests in the United States between 1990 and 2018. The study first explores the spatial dynamics of low-level law enforcement by graphing and mapping trends across a range of metropolitan types, finding that suburbs made the fewest low-level arrests and central cities reduced their arrests the most during these years. A spatial autoregressive panel data model reveals that police departments decreased their misdemeanor arrests more when nearby departments did so, net of crime rates and other controls, evincing spatial mimicry. Police reform efforts need not target only state and federal governments but can diffuse outward from city-level changes.