Abstract:The police need public support and cooperation to be effective in controlling crime and holding offenders accountable. In many disadvantaged communities of color, poor relationships between the police and residents undermine effective policing. Weak police–minority community relationships are rooted in a long history of discriminatory practices and contemporary proactive policing strategies that are overly aggressive and associated with racial disparities. There are no simple solutions to address the complex r… Show more
“…To date suggestions by scholars that potentially limit the disparate outcomes among minority citizens in targeted hot spots of crime tend to focus on the type of policing that is undertaken. Examples include focusing on problem oriented policing as opposed to more traditional policing tactics such as stops and arrests (Braga & Apel, 2016;Braga et al, 1999;Owens et al, 2018), or improving perceptions of police legitimacy during police interactions with the public (Braga, Brunson, & Drakulich, 2019;Lum & Nagin, 2017;Owens et al, 2018). But problem oriented policing often devolves into more traditional policing (Braga & Bond, 2008), and one should not entirely dismiss the capability of traditional approaches, such as conducting more police stops in hot spots of crime, to reduce crime (Groff et al, 2015;Rosenfeld, Deckard, & Blackburn, 2014;Weisburd, Telep, & Lawton, 2014).…”
Section: Discussionmentioning
confidence: 99%
“…One, the concept of fairness is intimately tied into legitimacy (Tyler, 2017;Tyler, Fagan, & Geller, 2014). Increasing perceptions of fairness is then expected to have downstream effects of the community cooperating with police, thus making investigations more effective (Braga et al, 2019).…”
Section: Fairness In Allocating Police Resourcesmentioning
confidence: 99%
“…Other recent work focuses on what police do at hot spots to reduce crime, in particular strategies focusing on problem-oriented policing approaches and procedural justice are less likely to result in negative community impressions (Braga et al, 2019;Owens et al, 2018). While encouraging police to be procedurally just in their encounters with the public is no doubt a good thing, there is scant evidence that improving procedural justice has resulted in improved police-citizen relations (Nagin & Telep, 2017;Worden & McLean, 2017).…”
Section: Fairness In Allocating Police Resourcesmentioning
confidence: 99%
“…I attempt to solve this problem by formulating a linear program to spatially allocate police resources to maximize police activity in high crime areas, while limiting the amount of racial disparity one would expect in contacts with the police. Currents solutions only focus on the types of policing that occurs within hot spots, which although may improve police community relations (Braga, Brunson, Drakulich, 2019;Lum & Nagin, 2017;Owens et al, 2018) are unlikely to reduce DMC and the disparate impact that occurs with more criminal justice contact (Brayne, 2014). As opposed to focusing on what the police do in hot spots, this article proposes a proactive policing strategy that is consistent with a hot spots policing approach, but still takes into consideration how the spatial distribution of police resources can either exacerbate or mitigate DMC.…”
Police targeting hot spots of crime tends to disproportionately burden minorities via stops and arrests. This work attempts to reduce disproportionate minority contact by formulating a crime hot spots spatial allocation strategy for police that prioritizes areas of high crime, but constrains the targeted hot spots given different levels of acceptable racial inequality. This racial inequality constraint is measured as the proportion of minorities likely to be stopped in those areas prioritized by police. Using data on stops and crime in New York City, I show that police stops can be more equitably distributed according to race, but there are fundamental trade-offs. One cannot gain a racial distribution of stops proportionately equal to the residential population without large decreases in the efficiency of targeting high crime areas. More modest gains can be had though in reducing the proportion of minorities stopped while still targeting high crime locations.
“…To date suggestions by scholars that potentially limit the disparate outcomes among minority citizens in targeted hot spots of crime tend to focus on the type of policing that is undertaken. Examples include focusing on problem oriented policing as opposed to more traditional policing tactics such as stops and arrests (Braga & Apel, 2016;Braga et al, 1999;Owens et al, 2018), or improving perceptions of police legitimacy during police interactions with the public (Braga, Brunson, & Drakulich, 2019;Lum & Nagin, 2017;Owens et al, 2018). But problem oriented policing often devolves into more traditional policing (Braga & Bond, 2008), and one should not entirely dismiss the capability of traditional approaches, such as conducting more police stops in hot spots of crime, to reduce crime (Groff et al, 2015;Rosenfeld, Deckard, & Blackburn, 2014;Weisburd, Telep, & Lawton, 2014).…”
Section: Discussionmentioning
confidence: 99%
“…One, the concept of fairness is intimately tied into legitimacy (Tyler, 2017;Tyler, Fagan, & Geller, 2014). Increasing perceptions of fairness is then expected to have downstream effects of the community cooperating with police, thus making investigations more effective (Braga et al, 2019).…”
Section: Fairness In Allocating Police Resourcesmentioning
confidence: 99%
“…Other recent work focuses on what police do at hot spots to reduce crime, in particular strategies focusing on problem-oriented policing approaches and procedural justice are less likely to result in negative community impressions (Braga et al, 2019;Owens et al, 2018). While encouraging police to be procedurally just in their encounters with the public is no doubt a good thing, there is scant evidence that improving procedural justice has resulted in improved police-citizen relations (Nagin & Telep, 2017;Worden & McLean, 2017).…”
Section: Fairness In Allocating Police Resourcesmentioning
confidence: 99%
“…I attempt to solve this problem by formulating a linear program to spatially allocate police resources to maximize police activity in high crime areas, while limiting the amount of racial disparity one would expect in contacts with the police. Currents solutions only focus on the types of policing that occurs within hot spots, which although may improve police community relations (Braga, Brunson, Drakulich, 2019;Lum & Nagin, 2017;Owens et al, 2018) are unlikely to reduce DMC and the disparate impact that occurs with more criminal justice contact (Brayne, 2014). As opposed to focusing on what the police do in hot spots, this article proposes a proactive policing strategy that is consistent with a hot spots policing approach, but still takes into consideration how the spatial distribution of police resources can either exacerbate or mitigate DMC.…”
Police targeting hot spots of crime tends to disproportionately burden minorities via stops and arrests. This work attempts to reduce disproportionate minority contact by formulating a crime hot spots spatial allocation strategy for police that prioritizes areas of high crime, but constrains the targeted hot spots given different levels of acceptable racial inequality. This racial inequality constraint is measured as the proportion of minorities likely to be stopped in those areas prioritized by police. Using data on stops and crime in New York City, I show that police stops can be more equitably distributed according to race, but there are fundamental trade-offs. One cannot gain a racial distribution of stops proportionately equal to the residential population without large decreases in the efficiency of targeting high crime areas. More modest gains can be had though in reducing the proportion of minorities stopped while still targeting high crime locations.
“…This is an important finding that not only replicates prior findings for the deterrent effect of arrests following shootings (Wyant et al, 2012), but provides evidence that solving violent crimes results in a lower probability of retaliation (Leovy, 2015). Improving clearance rates for serious violence is not impossible (Braga & Dusseault, 2018) and is also expected to have downstream effects of improving perceptions of police as well (Braga, Brunson, & Drakulich, 2019). These estimates of crime reductions can potentially be used to justify increased detective resources, especially given the costs associated with serious violence (Hunt, Saunders, & Kilmer, 2019).…”
Objectives: Near repeat patterns have been identified for a host of different crimes, but effective strategies to reduce near repeats have had more variable results. This study identifies near repeat crime patterns in Dallas, Texas and examines the effects of an arrest on reducing the probability of future crime. Method: Using open source crime data from the Dallas Police Department from July 2014 through June 2018, we identified near repeat patterns for shootings, interpersonal robberies, residential burglaries, and thefts from motor vehicles. Logistic regression models were used to test the effect of an arrest on reducing near repeat crimes; controls for geographic, demographic, and temporal factors were included in each model. Results: Near repeat calculations suggest violent crime clustered closely in time and space, with property crime dispersed over larger spatial and temporal dimensions. Across all four crime types, findings suggest arrests resulted in 20% to 40% reductions in a near repeat follow up crime.Conclusions: In line with past research on shootings, arrests reduced the likelihood of subsequent crimes. This suggests policing strategies to increase arrests may be a fruitful way to reduce near repeat crime patterns.Code to replicate the analysis can be found at:https://www.dropbox.com/sh/72q0i7wm60ndqve/AABgFB8zwGHG6xjExvaD01EGa?dl=0.
It is well documented that there has been significant enthusiasm across the globe in respect of using AI for all forms of social activity. However, the electoral process – the time, place, and manner of elections within democratic nations – is one of few sectors in which there has been limited penetration of AI. Electoral management bodies in many countries have recently started exploring and deliberating over the use of AI in the electoral process. In this paper, we consider five avenues within the core electoral process which have potential for AI usage, and map the challenges involved in using AI within them. These five avenues are: voter list maintenance, determining polling booth locations, polling booth protection processes, voter authentication, and video monitoring of elections. Within each avenue, we lay down the context, illustrate current or potential usage of AI, and discuss extant or potential ramifications of AI usage, as well as potential directions for mitigating risks when considering AI usage. We believe that the scant current usage of AI within electoral processes provides a very rare opportunity to deliberate on the risks and mitigation possibilities prior to actual and widespread AI deployment. This paper is an attempt to map the horizons of risks and opportunities in using AI within electoral processes and to help shape the debate around the topic.
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