Racial Disparities In Stop and Frisk Distributions by the Philadelphia Police Department

2020 ◽  
Author(s):  
Annie Vartanian
2017 ◽  
Vol 10 (1) ◽  
pp. 87-113
Author(s):  
Lance Hannon

The City of Philadelphia has faced significant litigation related to racial and ethnic disparities in stop-and-frisk practices. The Philadelphia Police Department has made much of its stop-and-frisk data publicly available in the name of transparency and to facilitate independent investigation (the data describe over 350,000 pedestrian stops with over 45,000 pedestrian frisks for 2014–2015). The current analysis made use of this public data set to explore whether the individual-level relationship between Black racial classification and being subjected to a frisk can be explained by associated neighborhood-level factors such as the violent crime rate. Additionally, the present analysis examined whether variation in the violent crime rate is similarly related to the likelihood of being frisked in predominantly Black versus non-Black areas and whether area racial composition affects the likelihood that an officer’s decision to frisk will be supported with uncovered contraband. The results were consistent with theories of neighborhood racial stigma. In particular, the violent crime rate was a significantly weaker predictor of being frisked in Black areas, and, net of a variety of factors at the individual and neighborhood levels, Black citizens and Black places experienced a disproportionate amount of frisks where no contraband was found or arrest made.


2016 ◽  
Vol 10 (1) ◽  
pp. 365-394 ◽  
Author(s):  
Sharad Goel ◽  
Justin M. Rao ◽  
Ravi Shroff

2019 ◽  
Vol 11 (6) ◽  
pp. 761-769 ◽  
Author(s):  
Erin Cooley ◽  
Neil Hester ◽  
William Cipolli ◽  
Laura I. Rivera ◽  
Kaitlin Abrams ◽  
...  

Violent encounters between police and Black people have spurred debates about how race affects officer decision-making. We propose that racial disparities in police–civilian interactions are amplified when police interact with Black civilians who are encountered in groups. To test this possibility, we analyzed New York City stop and frisk data for over 2 million police stops. Results revealed that Black (vs. White) people were more likely to be frisked, searched, arrested, and have force used against them. Critically, these racial disparities were more pronounced for people stopped in groups (vs. alone): Being stopped in a group led to a 1.7% increase in racial disparities for frisks, a 1% increase for searches, a 0.3% increase for arrests, and a 1.7% increase for use of force. Moreover, these disparities held even when we controlled for a potential proxy of effective policing: discovery of illegal contraband. We conclude that groups amplify racial disparities in policing.


2018 ◽  
Vol 21 (4) ◽  
pp. 461-485 ◽  
Author(s):  
Ojmarrh Mitchell ◽  
Greg Ridgeway

This research investigates the fairness and effectiveness of making a large number of bicycle stops as a proactive policing strategy designed to reduce unsafe riding and crime in Tampa, Florida. Public concern about the fairness and effectiveness of this tactic was magnified by a 2015 newspaper article that noted racial disparities in bicycle stops by the Tampa Police Department (TPD). Our analyses found that there are large racial disparities in bicycle stops, which cannot be explained by differences in ridership as measured by our benchmark, bicycle crashes with injury. The observed racial disparities in bicycle stops appear to be attributable to TPD’s crime control efforts, though we cannot rule out some racial bias. Given that crime control was a motivating factor for TPD’s use of bicycle stops, we assessed the effect of bicycle stops on crime using a natural experiment. We found that bicycle stops did not have a meaningful effect on crime.


Author(s):  
Jessica Marinaro ◽  
Alexander Zeymo ◽  
Jillian Egan ◽  
Filipe Carvalho ◽  
Ross Krasnow ◽  
...  

2006 ◽  
Vol 175 (4S) ◽  
pp. 112-112
Author(s):  
Jennifer T. Anger ◽  
Mark S. Litwin ◽  
Qin Wang ◽  
Er Chen ◽  
Chris L. Pashos ◽  
...  

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