Record Details

Detecting Anomalies in Data on Government Violence

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Detecting Anomalies in Data on Government Violence
 
Identifier https://doi.org/10.7910/DVN/IDD1GQ
 
Creator Kanisha D. Bond
Courtenay R. Conrad
Dylan Moses
Joel W. Simmons
 
Publisher Harvard Dataverse
 
Description Can data on government coercion and violence be trusted when the data are generated by state itself? In this paper, we investigate the extent to which data from the California Department of Corrections and Rehabilitation (CDCR) regarding the use of force by corrections officers against prison inmates between 2008 and 2017 conform to Benford’s Law. Following a growing data forensics literature, we expect misreporting of the use-of-force in California state prisons to cause the observed data to deviate from Benford’s distribution. Statistical hypothesis tests and further investigation of CDCR data—which show both temporal and cross-sectional variance in conformity with Benford’s Law—are consistent with misreporting of the use-of-force by the CDCR. Our results suggest that data on government coercion generated by the state should be inspected carefully before being used to test hypotheses or make policy.
 
Subject Social Sciences
state violence, coercion
 
Contributor Simmons, Joel