The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index; 4 of the 17 sources its claims cite were checked for support.
A large-scale analysis of racial disparities in police stops across the United States
Open accessAbstract
We assessed racial disparities in policing in the United States by compiling and analysing a dataset detailing nearly 100 million traffic stops conducted across the country. We found that black drivers were less likely to be stopped after sunset, when a 'veil of darkness' masks one's race, suggesting bias in stop decisions. Furthermore, by examining the rate at which stopped drivers were searched and the likelihood that searches turned up contraband, we found evidence that the bar for searching black and Hispanic drivers was lower than that for searching white drivers. Finally, we found that legalization of recreational marijuana reduced the number of searches of white, black and Hispanic drivers-but the bar for searching black and Hispanic drivers was still lower than that for white drivers post-legalization. Our results indicate that police stops and search decisions suffer from persistent racial bias and point to the value of policy interventions to mitigate these disparities.
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Claims the paper makes
38 Own result · 17 Own method · 14 Own interpretation · 8 Sources not found · 3 Partly supported · 3 No basis given · 2 No full text of the sources · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“it suffers from the problem of infra-marginality 8,26,27 .”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
What the sources say
- Supportedcites [8] Anwar, S. & Fang, H. An alternative test of racial prejudice in motor vehicle searches: theory and evidence. Am. Econ. Rev. 96, 127–151 (2006). sourceExperimental — accuracy not yet measured
The Introduction (p. 4) explicitly identifies infra-marginality as a problem for the outcome test: researchers observe average search success rates, not the marginal rates the test requires. It notes that the problem limits empirical applications of the test. (LLM, conf=0.93)
- Not checked — no full text of the sourcecites [26] Ayres, I. Outcome tests of racial disparities in police practices. Justice Res. Policy 4, 131–142 (2002). source
- Partly supportedcites [27] Knowles, J., Persico, N. & Todd, P. Racial bias in motor vehicle searches: theory and evidence. J. Polit. Econ. 109, 203–229 (2001). sourceExperimental — accuracy not yet measured
Section 2.3 (page unavailable) explains the infra-marginality problem: when guilt probabilities are exogenous, observed average guilt rates do not identify the marginal motorists relevant to a test for prejudice. But the paper distinguishes that case from its own outcome test, which relies on motorists responding to search probabilities. The unqualified claim omits that distinction. (LLM, conf=0.87)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the threshold test indicates that the bar for searching black and Hispanic drivers is generally lower than that for searching white drivers across the municipal police departments and states we consider.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Search policies do not differ within the geographic subdivisions considered.
- Rests on an assumption: Officers do not disproportionately suspect more serious criminal activity when searching black and Hispanic drivers than when searching white drivers.
- Rests on an assumption: The Bayesian threshold model's functional form and prior distributions are adequate for identifying search thresholds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In all cases, we found qualitatively similarly results that are suggestive of racial bias against black drivers in stop decisions”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In aggregate across cities, the inferred threshold for white drivers is 10.0% compared to 5.0 and 4.6% for black and Hispanic drivers, respectively.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“We note that these results are consistent with self-reported stop rates by white, black and Hispanic drivers who participated in the national PPCS 1 .”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
What the sources say
- Not matchedcites [1] Davis, E., Whyde, A.& Langton, L. Contacts between Police and the Public, 2015 (Bureau of Justice Statistics, 2018); http://www.bjs.gov/index.cfm?ty=pbdetail&iid=6406
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We find α s = -0.033(95% CI [-0.039, -0.027], P < 0.001) and α c = -0.039(95% CI [-0.045, -0.033], P < 0.001)”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In these jurisdictions, stopped black and Hispanic drivers were searched about twice as often as stopped white drivers.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For each time period, the plot shows a marked drop in the proportion of drivers stopped after dusk who are black, suggestive of discrimination in stop decisions.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We find α s = -0.033(95% CI [-0.039, -0.027], P < 0.001) and α c = -0.039(95% CI [-0.045, -0.033], P < 0.001)”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Among stopped drivers, we found that black and Hispanic individuals were, on average, searched more often than white individuals.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 17
- It may state two separate claims as one. 38
- The quote only partly states this claim. 2
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“the threshold test has been proposed as a more robust means for detecting discrimination 7,22 .”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
What the sources say
- Supportedcites [7] Simoiu, C., Corbett-Davies, S. & Goel, S. The problem of infra-marginality in outcome tests for discrimination. Ann. Appl. Stat. 11, 1193–1216 (2017). source
The Introduction describes the threshold test as a new test for discrimination that mitigates theoretical limitations of outcome analysis. The Conclusion likewise says it addresses shortcomings of the outcome test, supporting the comparison in the claim. (LLM, conf=0.93)
- Not matchedcites [22] Pierson, E., Corbett-Davies, S. & Goel, S. In International Conference on Artificial Intelligence and Statistics (eds Storkey, A. & Fernando Perez-Cruz, F.) 96–105 (PMLR, 2018).
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“thresholds cannot be identified by the observed data alone 7 , and so inferences are dependent on the specific functional form of the underlying Bayesian model, including the prior distributions.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
What the sources say
- Partly supportedcites [7] Simoiu, C., Corbett-Davies, S. & Goel, S. The problem of infra-marginality in outcome tests for discrimination. Ann. Appl. Stat. 11, 1193–1216 (2017). sourceExperimental — accuracy not yet measured
Section 2.3, “Inferring search thresholds” (page unavailable), specifies a Bayesian model with priors, supporting the claim that inference uses modeling assumptions. But a passage reproduced under “Conclusion” says the model would be identified by priors rather than data *without* certain constraints; it does not say thresholds cannot be identified from observed data under the specified model. The paper also says its results are robust to the exact choice of priors, qualifying the claimed dependence on them. (LLM, conf=0.84)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The Bayesian threshold model's functional form and prior distributions are adequate for identifying search thresholds.
- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“in the six municipal police departments we consider, the search rates were 9.5% (95% CI 9.4-9.6%)for black drivers, 7.2% (95% CI 7.0-7.3%)for Hispanic drivers and 3.9% (95% CI 3.8-3.9%)for white drivers.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the gap in hit rates between white and Hispanic drivers was 7.6% (95% CI 6.7-8.6%,P < 0.001), and the gap in hit rates between white and black drivers was 2.6% (95% CI 1.9-3.4%,P < 0.001).”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The estimated gaps in search thresholds between white and non-white drivers are large and statistically significant: the 95% credible interval for the Hispanic-white difference is (-6.4,-4.4%) and the corresponding interval for the black-white difference is (-6.1, -4.0%).”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Aggregating across state patrol stops, contraband was found in 32.0% (95% CI 31.6-32.4%) of searches of white drivers compared to 24.3% (95% CI 23.5-25.2%) of searches of Hispanic drivers and 29.4% (95% CI 28.7-30.0%) of searches of black drivers.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“aggregating across municipal police departments, contraband was found in 18.2% (95% CI 17.8-18.7%) of searches of white drivers compared to 11.0% (95% CI 10.6-11.5%) of searches of Hispanic drivers and 13.9% (95% CI 13.7-14.2%) of searches of black drivers.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The gap in municipal search rates between black and white drivers was 5.6% (95% CI 5.5-5.7%,P <0.001) and the gap in search rates between Hispanic and white drivers was 3.3% (95% CI 3.1-3.5%,P <0.001).”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similarly across states, the inferred threshold for white drivers is 20.9% compared to 16.0% for black drivers and 13.9% for Hispanic drivers.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“among state patrol stops, the annual per-capita stop rate for black drivers was 0.10 compared to 0.07 for white drivers; and among municipal police stops, the annual per-capita stop rate for black drivers was 0.20 compared to 0.14 for white drivers.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the gap in search rates between black and white drivers was 2.4% (95% CI 2.3-2.5%,P < 0.001) and the gap in search rates between Hispanic and white drivers was 2.2% (95% CI 2.1-2.2%,P < 0.001).”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For Hispanic drivers, however, we found that stop rates were lower than for white drivers: 0.05 for stops conducted by state patrol (compared to 0.07 for white drivers) and 0.09 for those conducted by municipal police departments (compared to 0.14 for white drivers).”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the eight state patrol agencies we consider, search rates were 4.3% (95% CI 4.2-4.4%)for black drivers, 4.1% (95% CI 4.0-4.1%)for Hispanic drivers and 1.9% (95% CI 1.9-1.9%)for white drivers.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the gap in hit rates between white and Hispanic drivers was 7.2% (95% CI 6.6-7.8%,P < 0.001) and the gap in hit rates between white and black drivers was 4.3% (95% CI 3.8-4.8%,P < 0.001).”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our primary dataset thus consists of approximately 95 million stops from 21 state patrol agencies and 35 municipal police departments”
- Also stated in: § Data collection and standardization. · plain
“Our primary dataset includes 94,778,505 stops from 21 state patrol agencies and 35 municipal police departments.”
§ A large-scale analysis of racial disparities in police stops across the United States > Compiling a national database of traffic stops.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one. The quote only partly states this claim.
- Also stated in: § Data collection and standardization. · plain
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“the policy change reduced the absolute gap in search rates between race groups; however, the relative gap persisted, with black and Hispanic drivers still more likely to be searched than white drivers post-legalization.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These differences are again large and statistically significant: the 95% credible interval for the Hispanic-white gap is (-8.4,-5.6%); and the analogous interval for the black-white gap is (-6.5%, -3.1%).”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the proportion of stops resulting in a search fell substantially in both Colorado and Washington, while in 12 states where marijuana was not legalized, search rates did not show sharp drops at the end of 2012.”
§ A large-scale analysis of racial disparities in police stops across the United States > Effects of legalization of marijuana.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Despite marijuana legalization decreasing search rates for white, black and Hispanic drivers, Fig. 4 shows that the relative disparity between white and non-white drivers remains.”
§ A large-scale analysis of racial disparities in police stops across the United States > Effects of legalization of marijuana.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Supplementary Fig. 3 shows that white drivers faced consistently higher search thresholds than black and Hispanic drivers, both before and after marijuana legalization.”
§ A large-scale analysis of racial disparities in police stops across the United States > Effects of legalization of marijuana.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: The latent signal distributions for each race and county are homoskedastic discriminant distributions.
- The authors state this as an assumption: The parameters φ and δ can be decomposed into additive race and location terms.
- The authors state this as an assumption: For each stop, a signal is drawn from the race-and-location-specific distribution; a search occurs if the signal exceeds the race-and-location-specific threshold; if searched, contraband is found with probability equal to the signal.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For all three depicted time windows, black drivers comprise a smaller share of stopped drivers after dark, when a veil of darkness masks their race, suggestive of racial profiling.”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The proportion of drivers with typically Hispanic names labelled as Hispanic in the raw data was 70% in Colorado and 79% in Arizona, much higher than in Texas.”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection and standardization.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Despite these lower inferred search thresholds, hit rates for black drivers are comparable to those for white drivers, ostensibly due to the problem of infra-marginality in outcome tests.”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Supplementary Fig. 3 also shows that the threshold faced by all groups decreases after legalization (although not all drops are statistically significant).”
§ A large-scale analysis of racial disparities in police stops across the United States > Effects of legalization of marijuana.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found that α race r I is large and negative for white, black and Hispanic drivers, suggesting that the observed drop in searches in Colorado and Washington was due to marijuana legalization in those states.”
§ A large-scale analysis of racial disparities in police stops across the United States > Effects of legalization of marijuana.
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: For each stop, a signal is drawn from the race-and-location-specific distribution; a search occurs if the signal exceeds the race-and-location-specific threshold; if searched, contraband is found with probability equal to the signal.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The outcome test thus indicates that search decisions may be biased against Hispanic drivers, but the evidence is more ambiguous for black drivers.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: Officers exercise discretion in whom to search.
- The authors state this as an assumption: In the absence of discrimination, searched minority drivers should be found with contraband at the same rate as searched white drivers.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“suggesting discrimination among both state patrols and municipal police departments.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one. The quote only partly states this claim.
- The authors state this as an assumption: Officers who engage in racial profiling are less able to identify a driver's race after dark than during the day.
- Rests on an assumption: Race-specific driving behaviour is not related more to lighting than to time of day.
- Rests on an assumption: Artificial lighting does not substantially weaken the relationship between sunlight and visibility.
- Rests on an assumption: Violation type is not related to lighting in a way that biases the veil-of-darkness test.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The data thus suggest that, although overall search rates dropped in Washington and Colorado, black and Hispanic drivers still faced discrimination in search decisions.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Search policies do not differ within the geographic subdivisions considered.
- Rests on an assumption: Officers do not disproportionately suspect more serious criminal activity when searching black and Hispanic drivers than when searching white drivers.
- Rests on an assumption: The Bayesian threshold model's functional form and prior distributions are adequate for identifying search thresholds.
In the paper
“past work revealed that Texas State Patrol officers incorrectly recorded many Hispanic drivers as white, an error the agency subsequently corrected 36 .”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection and standardization.
What the sources say
- Not matchedcites [36] Friberg, B. et al. Texas Troopers Ticketing Hispanic Drivers as White (KXAN, 2015); https://www.kxan.com/investigations/texas-troopers-ticketing-hispanic-drivers-as-white/
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We used all available data that were sufficiently complete to conduct our analysis.”
§ A large-scale analysis of racial disparities in police stops across the United States > Additional information
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The raw data we received from the states and cities, the processed data we used in this analysis and the code to clean and analyse the data are all available for public inspection and reuse.”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection and standardization.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The threshold test for discrimination was introduced by Simoiu et al. 7 to mitigate the most serious shortcomings of benchmark and outcome analysis.”
§ A large-scale analysis of racial disparities in police stops across the United States > Veil-of-darkness analysis.
What the sources say
- Not matchedcites Simoiu et al. 7
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Under this model of officer behaviour, we interpret lower search thresholds for one group relative to another as evidence of discrimination.”
§ A large-scale analysis of racial disparities in police stops across the United States > Veil-of-darkness analysis.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The left panel (Colorado) represents 1,674,619 stops and the right panel (Washington)represents 3,985,677 stops.”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“we applied a computationally fast variant of the threshold test developed by Pierson et al. 22 , which we fit separately on both state patrol stops and municipal police stops.”
§ A large-scale analysis of racial disparities in police stops across the United States > Veil-of-darkness analysis.
What the sources say
- Not matchedcites Pierson et al. 22
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“we re-categorized as 'Hispanic' all drivers in Texas with Hispanic names who were originally labelled 'white' or who had missing race data; this method adds about 1.9 million stops of Hispanic drivers over the period 2011-2015.”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection and standardization.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If, for example, officers disproportionately patrol black and Hispanic neighbourhoods, the downstream effects can be injurious even if individual stop decisions are not directly affected by the colour of one's skin.”
§ A large-scale analysis of racial disparities in police stops across the United States > Discussion
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“can place heavy burdens on black and Hispanic drivers without improving public safety 17 .”
§ A large-scale analysis of racial disparities in police stops across the United States > Discussion
What the sources say
- Not matchedcites [17] Chohlas-Wood, A., Goel, S., Shoemaker, A. & Shroff, R. An Analysis of the Metropolitan Nashville Police Department’s Traffic Stop Practices https://policylab.stanford.edu/media/nashville-traffic-stops.pdf (Stanford Computational Policy Lab, 2018).
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“since black drivers were more likely to be charged with such offences previous to legalization, these drivers were also disproportionately impacted by the policy change.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We ran numerous automated checks to detect and correct these where possible, although some errors probably remain due to the complex nature of the data.”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection and standardization.
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We did not exclude any data that were deemed sufficient to conduct our analysis.”
§ A large-scale analysis of racial disparities in police stops across the United States > Additional information
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“the KPT model of behaviour requires strong assumptions, including that drivers and officers are rational actors and that every driver has perfect knowledge of the likelihood that he or she will be searched.”
§ A large-scale analysis of racial disparities in police stops across the United States > Assessing bias in traffic stop decisions.
What the sources say
- Not checked — no full text of the sourcecites [28] Engel, R. S. & Tillyer, R. Searching for equilibrium: the tenuous nature of the outcome test. Justice Q. 25, 54–71 (2008). source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Following previous studies 38,39 , we defined a name as 'typically' Hispanic if at least 75% of people with that name identified as Hispanic”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection and standardization.
What the sources say
- Not matchedcites [38] Word, D. & Perkins, C. Building a Spanish Surname List for the 1990s: A New Approach to an Old Problem (Population Division, US Census Bureau, 1996).
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [39] Melendres v Arpaio (2009). 598 F. Supp. 2d 1025 (D. Ariz., 2009).
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“For both the state patrol model and the municipal department model, the prediction errors are minimal and similar across race groups.”
§ A large-scale analysis of racial disparities in police stops across the United States > Veil-of-darkness analysis.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The threshold test, however, aims to capture only taste-based discrimination, as is common in the empirical literature on discrimination.”
§ A large-scale analysis of racial disparities in police stops across the United States > Veil-of-darkness analysis.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We did not re-categorize drivers in any other jurisdiction.”
§ A large-scale analysis of racial disparities in police stops across the United States > Data collection and standardization.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“although our results are qualitatively similar under alternative averaging schemes.”
§ A large-scale analysis of racial disparities in police stops across the United States > Veil-of-darkness analysis.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“we limit our analysis to counties and districts with at least 50 searches per race group.”
§ A large-scale analysis of racial disparities in police stops across the United States > Veil-of-darkness analysis.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Our complete data-cleaning pipeline is extensive and required subjective decisions”
§ A large-scale analysis of racial disparities in police stops across the United States > Compiling a national database of traffic stops.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The results were statistically significant and qualitatively similar in all cases.”
§ A large-scale analysis of racial disparities in police stops across the United States > Veil-of-darkness analysis.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The authors state this as an assumption.
Officers exercise discretion in whom to search.
“Implicit in this test is the assumption that officers exercise discretion in whom to search”
The authors state this as an assumption.
In the absence of discrimination, searched minority drivers should be found with contraband at the same rate as searched white drivers.
“Becker argued that even if minority drivers are more likely to carry contraband, in the absence of discrimination, searched minorities should still be found to have contraband at the same rate as searched whites.”
The authors state this as an assumption.
Officers who engage in racial profiling are less able to identify a driver's race after dark than during the day.
“Their method starts from the idea that officers who engage in racial profiling are less able to identify a driver's race after dark than during the day.”
The paper relies on this without support.
Race-specific driving behaviour is not related more to lighting than to time of day.
“Results could be skewed if race-specific driving behaviour is related more to lighting than time of day, leading the test to suggest discrimination where there is none.”
The paper relies on this without support.
Artificial lighting does not substantially weaken the relationship between sunlight and visibility.
“artificial lighting (for example, from street lamps) can weaken the relationship between sunlight and visibility, and so the method may underestimate the extent to which stops are predicated on perceived race.”
The paper relies on this without support.
Violation type is not related to lighting in a way that biases the veil-of-darkness test.
“if violation type is related to lighting, the test could give an inaccurate measure of discrimination.”
The paper relies on this without support.
Search policies do not differ within the geographic subdivisions considered.
“if search policies differ not only across, but also within, the geographic subdivisions we consider, then the threshold test might mistakenly indicate discrimination where there is none.”
The paper relies on this without support.
Officers do not disproportionately suspect more serious criminal activity when searching black and Hispanic drivers than when searching white drivers.
“if officers disproportionately suspect more serious criminal activity when searching black and Hispanic drivers compared to white drivers (for example, possession of larger quantities of contraband), then lower observed thresholds may stem from non-discriminatory police practices.”
The paper relies on this without support.
The Bayesian threshold model's functional form and prior distributions are adequate for identifying search thresholds.
“thresholds cannot be identified by the observed data alone 7 , and so inferences are dependent on the specific functional form of the underlying Bayesian model, including the prior distributions.”
The paper relies on this without support.
Marijuana legalization in Colorado and Washington was not confounded by other simultaneous changes, and parallel trends hold.
“Using a difference-in-differences strategy, we find that legalization reduced both search rates and misdemeanour rates for drug offences for white, black and Hispanic drivers-though a gap in search thresholds persists.”
The authors state this as an assumption.
The latent signal distributions for each race and county are homoskedastic discriminant distributions.
“these signal distributions are modelled as homoskedastic discriminant distributions, a class of logit-normal mixture distributions supported on the unit interval [0, 1].”
The authors state this as an assumption.
The parameters φ and δ can be decomposed into additive race and location terms.
“We impose additional structure on the signal distributions by assuming that ϕ r,d and δ r,d can be decomposed into additive race and location terms.”
The authors state this as an assumption.
For each stop, a signal is drawn from the race-and-location-specific distribution; a search occurs if the signal exceeds the race-and-location-specific threshold; if searched, contraband is found with probability equal to the signal.
“For each stop i, we draw a signal p i from the associated race-and location-specific discriminant distribution.If the signal p i exceeds the race-and location-specific threshold t ri;di I , then a search is conducted and S i = 1; otherwise there is no search and S i = 0.If a search is conducted, contraband is found with probability p i , in which case H i = 1; otherwise, H i = 0.”
The paper relies on this without support.
Recreational marijuana legalization took effect on 9 December 2012 in Washington and 10 December 2012 in Colorado.
“Measures legalizing recreational marijuana took effect on 9 December 2012 in Washington, and on 10 December 2012 in Colorado.”
The paper relies on this without support.
In Washington, probable cause searches are barred because the state does not have an automobile exception for warrantless searches.
“in Washington, we note that probable cause searches are barred because the state does not have an automobile exception for warrantless searches.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These disparities exist even though they cannot be explained by the belief that Black people supposedly commit more crimes, including violent crimes”
From A call to dismantle systemic racism in criminal legal systems. (2022) · cites this paper as Pierson et al., 2020
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Another study, which examined one hundred million traffic stops across the United States, also found that police were less likely to discover contraband or evidence when searching Black and Hispanic drivers than White drivers.”
From The Rise of the Carceral State: Foundations and Contours of a Rapidly Changing Criminal Legal System (2025) · cites this paper as Pierson et al. 2020
The cited source says what the claim attributes to it.
In the citing paper
“They also found that Black drivers were less likely to be stopped by police after sunset-or, put another way, more likely to be stopped during daytime hours when skin color is more readily apparent (Pierson et al. 2020).”
From The Rise of the Carceral State: Foundations and Contours of a Rapidly Changing Criminal Legal System (2025) · cites this paper as Pierson et al. 2020
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Skin tone (i.e., colorism) has long been identified as among the most salient markers for discrimination (10, 11).”
From Nobel and novice: Author prominence affects peer review (2022) · cites this paper as [10]
Experimental — accuracy not yet measuredIn the citing paper
“SROs do not effectively reduce crime in schools (60)”
From Structural Racism and Suicide Prevention for Ethnoracially Minoritized Youth: A Conceptual Framework and Illustration Across Systems (2022) · cites this paper as [60]
Citations
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- Jung, J., Concannon, C., Shroff, R., Goel, S. & Goldstein, D.G. Simple rules to guide expert classifications. J. R. Stat. Soc. Ser. A (in the press).
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Items 101–200 of 548
Cooper, D., Frisbie, S., Wang, S., Ventimiglia, J. C., Gibbs, V., Love, A. M. A., Mogavero, M. C., Benevides, T. W., Hyatt, J. M., Hooven, K., et al. (2024) · Autism Research · doi:10.1002/aur.3203 · Cited by 13
“…et al., 2022), have excessive force used against them at higher rates (Kramer & Remster, 2018), and have their vehicles more frequently searched (Pierson et al., 2020), intersectional analyses focusing on the police experiences of Black autistic individuals are a future research priority to…”
Better for everyone: Black descriptive representation and police traffic stops
Christiani, L., Shoub, K., Baumgartner, F. R., Epp, D. A., & Roach, K. (2021) · Politics Groups and Identities · doi:10.1080/21565503.2021.1892782 · Cited by 15
Meuris, J. (2022) · Organization Science · doi:10.1287/orsc.2021.1571 · Cited by 12
Yi, Y. (2023) · Demography · doi:10.1215/00703370-10419487 · Cited by 13
Police‐perpetrated racism and health in African American and Black communities
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Police discrimination and police distrust among ethnic minority adolescents in Germany
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The racial composition of road users, traffic citations, and police stops
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Smart Festivals? Security and Freedom for Well-Being in Urban Smart Spaces
Crampton, J. W., Hoover, K. C., Smith, H., et al. (2019) · Annals of the American Association of Geographers · doi:10.1080/24694452.2019.1662765 · Cited by 12
Comparing Systemic and Individual Sources of Racially Disparate Traffic Stop Outcomes
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Verhaeghen, P., & Aikman, S. N. (2022) · Journal of Community Psychology · doi:10.1002/jcop.22840 · Cited by 12
Racial Disparities in the Enforcement of Marijuana Violations in the US
Butcher, B., Robinson, C., Zilka, M., Fogliato, R., Ashurst, C., & Weller, A. (2022) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3514094.3534184 · Cited by 12
Are Police Racially Biased in the Decision to Shoot?
Clark, T. S., Cohen, E., Glynn, A., Owens, M. L., Gunderson, A., & Schiff, K. J. (2023) · The Journal of Politics · doi:10.1086/723973 · Cited by 11
“, New York City’s stop, question, and frisk program) has enabled rigorous social science to deepen evidence of racial disparities in police use of force (e.g., Fryer 2016; Gelman, Fagan, and Kiss 2007; Goel, Rao, and Shroff 2016; Mummolo 2018; Pierson et al. 2017; Voigt et al. 2017).”
BackgroundDiversity Is Diverse: Social Justice Reparations and Science
Jussim, L. J. (2024) · Perspectives on Psychological Science · doi:10.1177/17456916241236171 · Cited by 10
“Police can and have abused their power to issue more tickets to Black motorists (Pierson et al., 2020).”
BackgroundDo Police Maximize Arrests or Minimize Crime? Evidence from Racial Profiling in U.S. Cities
Stashko, A. (2018) · Journal of the European Economic Association · doi:10.1093/jeea/jvac039 · Cited by 12
Assessment of US Federal Funding of Incarceration-Related Research, 1985 to 2022
Boch, S. J., Murnan, A., Pollard, J. F., Nidey, N., Hardy, R. Y., & Iruka, I. U. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.0803 · Cited by 11
Support seeking, system avoidance, and citizenship: Social safety net usage after incarceration
Bryan, B. (2023) · Criminology · doi:10.1111/1745-9125.12351 · Cited by 11
Black Households Are More Burdened by Vehicle Ownership than White Households
Molloy, Q., Garrick, N. W., & Atkinson‐Palombo, C. (2024) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/03611981241231968 · Cited by 12
“Black drivers are stopped and searched more frequently, often for less reason than their White counter-parts ( 7–9 ).”
Measuring racial and ethnic disparities in traffic enforcement with large-scale telematics data
Cai, W., Gaebler, J., Kaashoek, J., Pinals, L., Madden, S. R., & Goel, S. (2022) · PNAS Nexus · doi:10.1093/pnasnexus/pgac144 · Cited by 11
“These cities were selected because of the availability of both telemat-ics data, and high-resolution geocoded data on police stops for speeding, obtained from the Open Policing Project (21).”
BackgroundMethodInfluentialSelf-citationLee, D. J. L., & Parameswaran, A. (2018) · IEEE Data(base) Engineering Bulletin · Cited by 11
Roadway safety, design & equity: A paradigm shift
Michael, J. P., Wells, N. M., Shahum, L., et al. (2021) · Journal of Transport & Health · doi:10.1016/j.jth.2021.101260 · Cited by 11
Racial fairness in violence risk instruments: a review of the literature
Ashford, L., Spivak, B., & Shepherd, S. M. (2021) · Psychology Crime and Law · doi:10.1080/1068316x.2021.1972108 · Cited by 12
“…stops and arrests among racial minorities) potentially resulting in the relationship between predominant risk instrument factors (e.g. previous criminal history) and future arrest being different for racial minorities compared to Whites (Hannah-Moffat, 2013; Harcourt, 2007; Pierson et al., 2020).”
BackgroundMacken, L., & Connell, M. O. (2022) · Cogent Psychology · doi:10.1080/23311908.2022.2156842 · Cited by 10
A transparency statement improves trust in community-police interactions
Dobson, K. S. H., Dittmann, A. G., & Yeager, D. S. (2025) · Nature Communications · doi:10.1038/s41467-024-55709-6 · Cited by 28
The George Floyd Effect: How Protests and Public Scrutiny Changed Police Behavior
Roman, M., Fredriksson, K., Cassella, C., Epp, D. A., & Walker, H. L. (2025) · Perspectives on Politics · doi:10.1017/s1537592725000052 · Cited by 11
“The protests in Los Angeles were similarly intense, leading Governor Gavin Newsom to declare a state of emergency, deploying the National Guard (Reyes-Valarde et al. 2020; Petrie 2020).”
Online Resource Allocation with Matching Constraints
Dickerson, J. P., Sankararaman, K. A., Sarpatwar, K., et al. (2019) · Adaptive Agents and Multi-Agents Systems · doi:10.65109/zglv4908 · Cited by 10
“The policing dataset [44] contains records from the Texas state since 2010.”
BackgroundMethodAyers, J. W., Althouse, B. M., Poliak, A., Leas, E. C., Nobles, A. L., Dredze, M. H., & Smith, D. M. (2020) · Journal of Medical Internet Research · doi:10.2196/22574 · Cited by 10
“This is not to say there is little scientific work on police reform (there is a tremendous literature [32-34]), but little of it has been conducted from a public health perspective or with the benefit of considering strategies popularized by other public health policy successes.”
BackgroundJohnson, L., Devereux, P. G., & Wagner, K. D. (2022) · Harm Reduction Journal · doi:10.1186/s12954-022-00635-3 · Cited by 10
Do Cellphone Bans Save Lives? Evidence From Handheld Laws on Traffic Fatalities
Wright, N. A., & Dorilas, E. (2022) · Journal of Health Economics · doi:10.1016/j.jhealeco.2022.102659 · Cited by 10
Interracial encounters with the police: findings from the NCVS police-public contact survey
Flexon, J. L., D’Alessio, S. J., Stolzenberg, L., & Greenleaf, R. G. (2019) · Journal of Ethnicity in Criminal Justice · doi:10.1080/15377938.2019.1646688 · Cited by 9
Combating Social Injustice and Misinformation to Engage Minority Youth in Computing Sciences
Cummings, D., Anthony, M., Watson, C., Watson, A., & Boone, S. L. (2021) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3408877.3432452 · Cited by 10
“The students learned how to aggregate the data records by race, gender, age (or any of the other 11 fields regularized by the Stanford Team) and find patterns of outcomes that mirrored the findings of the Stanford team and others who have repeated an analysis on the data the team provided [40,41,42].”
ResultRalph, K. M., Barajas, J. M., Johnson-Rodriguez, A., et al. (2022) · Journal of Planning Education and Research · doi:10.1177/0739456x221138073 · Cited by 10
“7 We hypothesized that BIPOC individuals may be more concerned about revenue generation because they are disproportionately ticketed (Grogger and Ridgeway 2006; Pierson et al. 2020).”
Miles, J., Acevedo, A., Panas, L., et al. (2019) · The Journal of Behavioral Health Services & Research · doi:10.1007/s11414-019-09672-6 · Cited by 10
Hu, X., Zhang, X., & Lovrich, N. P. (2020) · Journal of Computational Social Science · doi:10.1007/s42001-020-00079-4 · Cited by 13
“black and Hispanic drivers are more likely to be searched, ticketed, and arrested than are white drivers during traffic stops made for the same initial offenses [57].”
BackgroundInfluentialBeing 'Seen' vs. 'Mis-Seen': Tensions between Privacy and Fairness in Computer VisionPreprint
Xiang, A. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4068921 · Cited by 10
Systemic Discrimination: Theory and MeasurementPreprint
Bohren, J. A., Hull, P., & Imas, A. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4051254 · Cited by 10
“(18)For example, Pincus (1996) defines structural discrimination as referring to “the policies of dominant race/ethnic/gender institutions and the behavior of individuals who implement these policies and control these institutions, which are race/ethnic/gender neutral in intent but which have a differential and/or har…”
BackgroundInfluentialPerspectives on incorporating expert feedback into model updates
Chen, V., Bhatt, U., Heidari, H., Weller, A., & Talwalkar, A. (2023) · Patterns · doi:10.1016/j.patter.2023.100780 · Cited by 15
Hawkins, D. (2023) · Journal of Family Communication · doi:10.1080/15267431.2023.2240801 · Cited by 11
Balancing Act: Evaluating People’s Perceptions of Fair Ranking Metrics
Alkhathlan, M., Cachel, K., Shrestha, H., Harrison, L., & Rundensteiner, E. A. (2024) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3630106.3659018 · Cited by 9
Wen, A. Y., Gubner, N. R., Garrison, M. M., & Walker, S. C. (2023) · Health & Justice · doi:10.1186/s40352-022-00203-8 · Cited by 10
“Moreover, our methods do not take into consideration other cumulative effects of race including increased policing, surveillance, and arrest rates for communities of color which directly impact number of priors—a significant predictor of pretrial detention (Davis et al., 2018; Pierson et al., 2020).”
MethodTransportation Justice and Health
Hansmann, K. J., & Razon, N. (2023) · Milbank Quarterly · doi:10.1111/1468-0009.12676 · Cited by 9
“…ones and seeks to address the up-stream structural determinants that lead to the inequitable distribution of transporta-tion’s benefits (e.g., access to jobs and services 20 ) and its harms (e.g., air pollution, 21 displacement, 22 and increased negative interactions with law enforcement 23 ).”
Marineau, L., Uzzi, M., Buggs, S. A. L., Ihenacho, N., & Campbell, J. (2023) · Trauma, Violence, & Abuse · doi:10.1177/15248380231217042 · Cited by 10
“The profound discrimination experienced by Black men throughout the criminal legal system is well documented (Committee on Revision of the Penal Code, 2021; Klein et al., 2023; Palamar et al., 2015; Pierson et al., 2020).”
BackgroundKnode, J. L., Wolfe, S. E., & Carter, T. M. (2024) · Criminology · doi:10.1111/1745-9125.12366 · Cited by 9
Возможности и ограничения цифровых следов и методов машинного обучения в социологии
Богданов, М. Б., & Smirnov, I. (2021) · Monitoring obŝestvennogo mneniâ: èkonomičeskie i socialʹnye peremeny · doi:10.14515/monitoring.2021.1.1760 · Cited by 9
May I Talk to You for a Minute? An Assessment of Street Stops and Officer Decision-Making
Tillyer, R., Smith, M. R., & Lloyd, C. D. (2021) · Crime & Delinquency · doi:10.1177/00111287211047541 · Cited by 9
“The preponderance of evidence suggests that Black and Hispanic drivers experience higher likelihoods of search (Engel & Johnson, 2006; Pickerill et al., 2009; Pierson et al., 2020; Rosenfeld et al., 2012; Schafer et al., 2006; Tillyer et al., 2019), arrest (Kochel et al.”
BackgroundResultInterest groups, local politics, and police unions
DiSalvo, D. (2022) · Interest Groups & Advocacy · doi:10.1057/s41309-021-00146-9 · Cited by 9
Goals and outcomes of police officer communication: Evidence from in-depth interviews
Oxholm, P. D., & Glaser, J. (2023) · Group Processes & Intergroup Relations · doi:10.1177/13684302221121585 · Cited by 9
“Findings of racially disparate communications by police are complemented by a large body of rigorous research showing racial disparities favoring Whites in police stops, searches, and use of force (Charbonneau & Glaser, 2020; Fagan & Geller, 2020; Geller et al., 2021; Glaser, 2015; Knox et al., 2020; Pierson et al., 2…”
BackgroundWhite Coats for Black Lives: The Time Has Come for Action
Stone, V. E. (2020) · Annals of Internal Medicine · doi:10.7326/m20-4280 · Cited by 10
Racial Disparities in Motor Vehicle Searches Cannot Be Justified by Efficiency
Feigenberg, B., & Miller, C. (2020) · National Bureau of Economic Research · doi:10.3386/w27761 · Cited by 10
TESTING ECONOMIC MODELS OF DISCRIMINATION IN CRIMINAL JUSTICEPreprint
Gelbach, J. B. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3784953 · Cited by 9
Amemiya, J. L., Mortenson, E., Heyman, G. D., et al. (2021) · doi:10.31234/osf.io/47wr6 · Cited by 9
Kajeepeta, S., Bates, L. M., Keyes, K. M., Bailey, Z., Roberts, D. E., Bruzelius, E., Askari, M. S., & Prins, S. J. (2024) · Aggression and Violent Behavior · doi:10.1016/j.avb.2024.101947 · Cited by 14
Boehme, H. M., Jung, S., Geary, I. A., Brown, R. A., & Leasure, P. (2024) · Journal of Experimental Criminology · doi:10.1007/s11292-024-09625-w · Cited by 8
“Some research has found racial disparities in police traffic stops, both in the disparity of who is stopped (Miller, 2008) and the outcome of traffic stops (Baumgartner et al., 2017; Pierson et al., 2020).”
The Trouble with Using Risk Assessment Instruments to Quantify the Chance of Future Offending
Goddard, T. (2021) · Sustainability · doi:10.3390/su132111624 · Cited by 10
“[50] found that police are typically more willing to stop Black and Hispanic drivers based on less suspicious behavior than White drivers.”
BackgroundCan a racial justice frame help overcome opposition to automated traffic enforcement?
Ralph, K. M., Barajas, J. M., Johnson-Rodriguez, A., et al. (2022) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2022.100594 · Cited by 8
Mapping police power and the limits of reform
Lally, N. (2022) · Geoforum · doi:10.1016/j.geoforum.2022.09.006 · Cited by 9
“Studies have shown that the threshold for searching Black people is much lower than white people during traffic stops (Pierson et al. 2020)—disparities in drug citations are one reflection of this kind of disparate scrutiny by police officers.”
Morris, K. G., & Scott, J. C. (2022) · Homicide Studies · doi:10.1177/10887679221139500 · Cited by 10
“Systemic racism within law enforcement and the criminal justice system is responsible for Black individuals being disproportionately stopped and/or arrested by the police, shot by the police and incarcerated (Lett et al., 2021; Nellis, 2021; Pierson et al., 2020).”
Worldwide Views on Police Discretion
Feys, Y. (2023) · SpringerBriefs in criminology · doi:10.1007/978-3-031-22281-8 · Cited by 8
Racial Bias in Criminal Records
Grunwald, B. (2022) · Journal of Quantitative Criminology · doi:10.1007/s10940-023-09575-y · Cited by 11
“Indeed, there is evidence that police stop Black and Hispanic pedestrians at a lower threshold of proof (Pierson et al. 2020; Goel et al. 2016; Eckhouse et al. 2019).”
Verona, E., & Fox, B. (2025) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-081423-024754 · Cited by 13
The downside of downsizing: Persistence of racial disparities following state prison reform
Lerman, A. E., & Mooney, A. C. (2021) · Punishment & Society · doi:10.1177/14624745211006039 · Cited by 8
“…racial bias in criminal justice—as clearly seen, for example, in the evidence of continued racial disparities in police stops (Gelman et al., 2007; Pierson et al., 2020), police involved shootings (Ross, 2015; Spencer et al., 2016), and sentencing outcomes (Mitchell, 2005; Steffensmeier and…”
Background“Crime” in Context: Racialized Physical Space Shifts Person-Perception
James, D., Bonam, C. M., & Taylor, V. J. (2022) · Race and Social Problems · doi:10.1007/s12552-022-09361-8 · Cited by 8
Ethical problems with kindness in healthcare
Jesudason, E. P. (2022) · Journal of Medical Ethics · doi:10.1136/jme-2022-108357 · Cited by 8
Racial bias as a multi‐stage , multi‐actor problem: An analysis of pretrial detention
Grossman, J., Nyarko, J., & Goel, S. (2023) · Journal of Empirical Legal Studies · doi:10.1111/jels.12343 · Cited by 13
Self-citationCamp, N. P. (2023) · Social and Personality Psychology Compass · doi:10.1111/spc3.12930 · Cited by 12
Police Stops and Searches of Indigenous People in Minneapolis: The Roles of Race, Place, and Gender
Gorsuch, M., & Rho, D. (2019) · International Indigenous Policy Journal · doi:10.18584/iipj.2019.10.3.8322 · Cited by 8
“African American and Latino individuals are more often stopped by police in traffic stops and more likely to be searched when stopped (for example, Anwar & Fang, 2006; Gelman, Fagan, & Kiss, 2007; Gross & Barnes, 2002; Knowles, Persico, & Todd, 2001; Pierson et al., 2017; Ritter, 2017).”
BackgroundNot So Black and White: Uncovering Racial Bias from Systematically Misreported Trooper ReportsPreprint
Luh, E. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3357063 · Cited by 8
Sunde, H. M., Weenink, D., & Lindegaard, M. (2023) · Policing and Society: An International Journal of Research and Policy · doi:10.1080/10439463.2023.2216839 · Cited by 8
“…on profiling in policing have shown that police target minorities more often, in stop and searches (e.g. Vito et al. 2021, Carvalho et al. 2022), traffic stops (e.g. Pierson et al. 2020), identity checks (e.g. Jobard and Lévy 2011, Jobard et al. 2012), and ‘geo-policing’ (e.g. Çankaya 2020).”
Burch, T. R. (2023) · Cambridge University Press eBooks · doi:10.1017/9781108982870 · Cited by 6
A realist review on the police use of stop and search powers
Agnew-Pauley, W., Hughes, C. E., & Stevens, A. (2025) · European Journal of Criminology · doi:10.1177/14773708241290593 · Cited by 4
“Themajority of studies of stop and search come from the USA, in relation to the practice of ‘ stop and frisk ’ or traf fi c stops (MacDonald et al., 2016; Pierson et al., 2020).”
Neural Tracking of Race-Related Information During Face Perception
Pang, C., Zhou, N., Deng, Y., Pu, Y., & Han, S. (2025) · Neuroscience Bulletin · doi:10.1007/s12264-025-01419-y · Cited by 10
“These are consistent with previous findings of racial ingroup favoritism in altruistic decision-making reported in laboratory studies [60–62] and in real-life situations [45, 46].”
Homicides involving Black victims are less likely to be cleared in the United States
Campedelli, G. M. (2024) · Criminology · doi:10.1111/1745-9125.12362 · Cited by 8
“…vast and heterogeneous: Prominent research lines focused, for example, on disparities in police stops (Kramer & Remster, 2018; Legewie, 2016; Pierson et al., 2020), disproportionate use of force against civilians (Chalfin et al., 2020; Edwards et al., 2019; Streeter, 2019), and concerns…”
Hetey, R. C., Hamedani, M. G., Markus, H. R., & Eberhardt, J. L. (2024) · Daedalus · doi:10.1162/daed_a_02052 · Cited by 8
High-frequency location data show that race affects citations and fines for speeding
Aggarwal, P., Brandon, A., Goldszmidt, A., Holz, J. E., List, J. A., Muir, I., Sun, G., & Yu, T. (2025) · Science · doi:10.1126/science.adp5357 · Cited by 9
Examining the Validity of Traffic Stop Data: A Mixed-Methods Analysis of Police Officer Compliance
Chanin, J., & Welsh, M. (2020) · Police Quarterly · doi:10.1177/1098611120933644 · Cited by 12
“Following the logic of deterrence theory, it is relatively common practice for agencies to shape behavior through policies that aim to increase the certainty of detection or the severity of punishment associated with non-compliance (Herath & Rao, 2009; Pogarsky & Piquero, 2004).”
MethodDriving While Black and Brown in Vermont: Can Race Data Analysis Contribute to Reform?
Seguino, S., & Brooks, N. (2020) · The Review of Black Political Economy · doi:10.1177/0034644620969903 · Cited by 7
“Extensive data on race and traffic policing are now available at the state and local level.1 In the first U.S. study of its kind, Pierson et al. (2020) undertook the task of analyzing multistate data, based on 95 million traffic stops by 21 state patrol and 35 municipal agencies.”
BackgroundNazaretian, Z., Heraux, C. G., & Merolla, D. M. (2021) · Policing An International Journal · doi:10.1108/pijpsm-01-2021-0004 · Cited by 7
McGuier, E. A., Kolko, D. J., & Dubowitz, H. (2021) · Aggression and Violent Behavior · doi:10.1016/j.avb.2021.101635 · Cited by 7
Does Police Stop and Search Make Everyone Feel Safe? Evidence From the United States
Mulaphong, D., & Cheurprakobkit, S. (2021) · Race and Justice · doi:10.1177/21533687211023576 · Cited by 4
“Future research may broaden the scope of research to police traffic stops and vehicle searches and citizens’ resulting perceptions of injustice or safety (e.g., Lundman, 2012; Pierson et al., 2020; Warren et al., 2006).”
BackgroundEscalera, C., Strassle, P. D., Quintero, S. M., et al. (2022) · BMC Public Health · doi:10.1186/s12889-022-14022-x · Cited by 7
“One study employing complex standardization and analyses of over 100 million traffic stops found that police require less suspicion during traffic stops to search Black and Hispanic drivers than White drivers, suggesting persistent racial bias [14].”
BackgroundAllgood, K. L., Fleischer, N., Morenoff, J. D., Assari, S., & Needham, B. L. (2023) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-023-01523-7 · Cited by 7
“…communities by the police, even commonplace and routine PEs may impose more stress on persons from racially minoritized groups than White people, suggesting that cardiovascular disease risk or risk factors may emerge across racial groups due to PEs [8, 9, 14–16, 58, 60, 62, 65–67, 111, 112].”
Community Relations and Policing: A Communication Accommodation Theory Perspective
Hill, S. L., Giles, H., & Maguire, E. R. (2023) · Springer eBooks · doi:10.1007/978-3-031-41096-3_13 · Cited by 9
Robinson, S. L., McCort, C. D., Smirniotis, C., Wintemute, G. J., & Laqueur, H. S. (2024) · Injury Epidemiology · doi:10.1186/s40621-024-00491-8 · Cited by 8
“Further, racial disparities in police stops, searches, and arrests are well documented (Kovera 2019; Kirk 2008; Schleiden et al. 2020; Austin and Allen 2000; Ousey and Lee 2008; Pierson et al. 2020).”
BackgroundHochstatter, K. R., Akhtar, W. Z., El‐Bassel, N., Westergaard, R. P., & Burns, M. E. (2021) · Journal of Substance Abuse Treatment · doi:10.1016/j.jsat.2021.108484 · Cited by 7
Improving Justice, Equity, Diversity, and Inclusion in Research on Sexual Abuse Perpetration
Fanniff, A. M., & Alexander, A. A. (2022) · Sexual Abuse · doi:10.1177/10790632221091193 · Cited by 8
“…the criminal legal system has been well-established in the broader criminological literature, including policing practices (e.g., Gase et al., 2016; Pierson et al., 2020), pre-trial detention (e.g., Omori & Peterson, 2020), charging (e.g., Starr & Rehavi, 2013), and sentencing (e.g., Brennan &…”
BackgroundPlaying politics with traffic fines: Sheriff elections and political cycles in traffic fines revenue
Su, M., & Buerger, C. (2024) · American Journal of Political Science · doi:10.1111/ajps.12866 · Cited by 6
Legal descriptions of police officers affect how citizens judge them
Spruill, M., & Lewis, N. A. (2022) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2022.104306 · Cited by 6
Sommers, R., & Bohns, V. K. (2023) · Journal of Empirical Legal Studies · doi:10.1111/jels.12375 · Cited by 6
Headley, A. M., Baker, D. B., & Kang, I. (2025) · PAR. Public Administration Review · doi:10.1111/puar.13927 · Cited by 4
Stabile, B. B., Simon, K. M., Thornton, T. E., & Grant, A. (2021) · Public Integrity · doi:10.1080/10999922.2020.1862540 · Cited by 6
“An analysis of nearly 100 million traffic stops across the United States over the course of a decade found that police stop and search decisions exhibit persistent racial bias, with Black drivers more likely to be stopped and searched than White drivers (Pierson et al., 2020).”
BackgroundHazards of anti‐Blackness in the United States
Rowell‐Cunsolo, T. L., Bellerose, M., & Haile, R. (2022) · International Journal of Social Welfare · doi:10.1111/ijsw.12547 · Cited by 6
Omnibus or Ominous immigration laws? Immigration policy and mental health of the Hispanic population
Luo, T., & Kostandini, G. (2022) · Health Economics · doi:10.1002/hec.4611 · Cited by 6
Possibilities and Problems in Trauma-Based and Social Emotional Learning Programs
Pyscher, T., & Crampton, A. E. (2020) · Occasional Paper Series · doi:10.58295/2375-3668.1386 · Cited by 7
On the role of experience versus motivation in predicting the own‐race effect
Tracy, R. E., Zomberg, D., & Young, S. G. (2023) · British Journal of Psychology · doi:10.1111/bjop.12628 · Cited by 10
Yim, A., & Passalacqua, N. V. (2023) · Humans · doi:10.3390/humans3030017 · Cited by 6
Racial Disparities in Police Stops in US Cities
Rivera, R., & Rosenbaum, J. E. (2020) · Significance · doi:10.1111/1740-9713.01412 · Cited by 6
Anti-Oppressive Restorative Justice: Behavior Analysis in Alternatives to Policing
Leland, W., & Stockwell, A. (2021) · Behavior Analysis in Practice · doi:10.1007/s40617-021-00633-0 · Cited by 6
Police equilibrium: a glocal assessment of the demand and supply of police
Dau, P. M., Dewinter, M., Beken, T. V., Witlox, F., & Vandeviver, C. (2022) · Policing & Society · doi:10.1080/10439463.2022.2149750 · Cited by 6
“…and operationally inefficient as other places might require the available resources more, while on the other hand elevated levels of police supply can induce high social cost such as perceived or concrete racial profiling (see, Ridgeway, 2006; Goel et al., 2016; Cohen, 2017; Pierson et al., 2020).”
BackgroundHow Endogenous System Bias Can Distort Decision-Making in Criminal Justice Systems
Pierce, G. L., Rodriguez‐Whitney, E., Drakulich, K., Shatz, S. F., & Radelet, M. L. (2023) · Social Justice Research · doi:10.1007/s11211-023-00408-8 · Cited by 9
SARS-CoV-2 transmission: a sociological review
Siff, E. J., Aghagoli, G., Marin, B. G., Tobin‐Tyler, E., & Poitevien, P. (2020) · Epidemiology and Infection · doi:10.1017/s095026882000240x · Cited by 7
Political ideology and social categorization
Stern, C. (2022) · Advances in experimental social psychology · doi:10.1016/bs.aesp.2021.11.003 · Cited by 7
Metadata
- Authors
- Pierson, E., Simoiu, C., Overgoor, J., Corbett-Davies, S., Jenson, D., Shoemaker, A., Ramachandran, V., Barghouty, P., Phillips, C., Shroff, R., & Goel, S.
- Affiliations
- Stanford University (US)
- New York University (US)
- Corresponding author
- Goel, Sharad
- Venue
- Nature Human Behaviour
- Published
- 2020-05-04
- Volume
- 4
- Issue
- 7
- Pages
- 736-745
- ISSN
- 2397-3374 (ISSN-L)
- OpenAlex
- W2705765409
- Cited by
- 552
- References
- 42
- Citations by year
- 2026: 59 · 2025: 74 · 2024: 97 · 2023: 109 · 2022: 79 · 2021: 71 · 2020: 34
- FWCI
- 254.50
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature Human Behaviour (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- arXiv (Cornell University)
- Funders
- John S. and James L. Knight Foundation
- Hellman Foundation
- Topics
- Social Sciences › Political Science and International Relations › Policing Practices and Perceptions
- Social Sciences › Sociology and Political Science › Criminal Justice and Corrections Analysis
- Social Sciences › Education › Education Discipline and Inequality
- Keywords
- racial disparities in policing, traffic stops, police searches, racial bias, Black drivers, recreational cannabis legalization, contraband, racial profiling, United States
- MeSH terms
- Automobile Driving, Black or African American, Female, Hispanic or Latino, Humans, Male, Time Factors, United States, Police, White People, Racism
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-09-29, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-09-29 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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