Evidence map›Paper›PMID 34161363›Full record

ArticlePloS one2021

US law enforcement policy predictors of race-specific police fatalities during 2015-16.

Marilyn D Thomas, Alexis N Reeves, Nicholas P Jewell, Eli K Michaels, Amani M Allen

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Marilyn D ThomasDepartment of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States of America.ORCID 0000-0003-3245-6363
Alexis N ReevesDepartment of Epidemiologic Science, University of Michigan School of Public Health, Ann Arbor, MI, United States of America.ORCID 0000-0002-6831-7173
Nicholas P JewellDivision of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA, United States of America.
Eli K MichaelsDivision of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA, United States of America.
Amani M AllenDivision of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA, United States of America.

Funding

Clinical and Translational Science InstituteUL1TR001872 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI COLLARD, HAROLD R, JACOBY, VANESSA · 2016 to 2025
$112.1M
SF BUILD: Enabling Students to Represnt in ScienceUL1GM118985 · NIGMS · SAN FRANCISCO STATE UNIVERSITY · PI MARQUEZ-MAGANA, LETICIA MARIA, MORRIS, MEGHAN D · 2015 to 2023
$18.2M
Social Interventions to address disparities In young adult tobacco useP60MD006902 · NIMHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BIBBINS-DOMINGO, KIRSTEN · 2012 to 2016
$6.4M
NCATS NIH HHS UL1 TR001872NIGMS NIH HHS UL1 GM118985NIMHD NIH HHS P60 MD006902
6 · The paper itself

Abstract

Mounting evidence suggests that law enforcement organizational factors contribute to higher incidence and racial disparities in police killings. To determine whether agency policies contribute to race-specific civilian fatalities, this exploratory study compared fatality rates among agencies with and without selected policies expected to reduce killings. A cross-section of 1085 fatalities in the 2015-2016 The Counted public-use database were matched to 481 agencies in the 2013 Law Enforcement Management and Administrative Statistics (LEMAS) database. Negative binomial regression estimated incidence rate ratios (IRR) adjusted for agency type, number of officers, percent female personnel, median income, percent with a bachelor's degree, violent crime rate, and population size, with inference using robust standard errors. Agencies with greater proportions of full-time personnel (range 43-100%) had lower rates of all (IRR = 0.85; 95% confidence interval [CI] = 0.77-0.93) and non-White civilian killings (IRR = 0.85; CI = 0.73-0.99). Mission statements predicted lower rates of all (IRR = 0.70; CI = 0.58-0.84) and White killings (IRR = 0.60; CI = 0.40-0.90). Community evaluation and more types of personnel incentives predicted lower rates of White (IRR = 0.82; CI = 0.68-0.99) and non-White killings (IRR = 0.94; CI = 0.89-1.00), respectively. Increasing video use predicted higher rates of White killings (IRR = 1.13; CI = 1.01-1.28). No policies were significantly associated with Black civilian killings. Law enforcement policies that help reduce police killings may vary across racial groups with the least benefit for Black civilians. Impact evaluations and meta-analyses of initiatives aimed to mitigate fatalities should be explored, particularly policies to address anti-Black bias. A national registry tracking all police killings and agency policies is urgently needed to inform law enforcement policies aimed to mitigate civilian fatalities.

Indexed as

Organizational PolicyBlack or African AmericanBlack PeopleFemaleHomicideHumansLaw EnforcementMalePoliceUnited StatesWhite People

Identifiers

PMID34161363
PMCPMC8221500

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.