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
Cites
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Mostly Harmless Econometrics: An Empiricist's Companion
Angrist, J. D., & Pischke, J.-S. (2009) · doi:10.1515/9781400829828 · Cited by 9,467
Mostly Harmless Econometrics: An Empiricist's Companion
Angrist, J. D., & Pischke, J.-S. (2008) · doi:10.2307/j.ctvcm4j72 · Cited by 5,051
The Economics of Discrimination.
Collard, D. A., & Becker, G. S. (1972) · The Economic Journal · doi:10.2307/2230052 · Cited by 3,642
The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte CarloPreprint
Homan, M. D., & Gelman, A. (2014) · arXiv (Cornell University) · Cited by 3,078
POSTERIOR PREDICTIVE ASSESSMENT OF MODEL FITNESS VIA REALIZED DISCREPANCIES
Gelman, A., Meng, X., & Stern, H. S. (1996) · Cited by 1,982
Gardner, W. P., Mulvey, E. P., & Shaw, E. C. (1995) · Psychological Bulletin · doi:10.1037/0033-2909.118.3.392 · Cited by 1,840
The Economics of Discrimination
Becker, G. S. (1971) · doi:10.7208/chicago/9780226041049.001.0001 · Cited by 1,794
Nobel Lecture: The Economic Way of Looking at Behavior
Becker, G. S. (1993) · Journal of Political Economy · doi:10.1086/261880 · Cited by 1,619
Research works printed but not linked: 4
- 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).
- 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).
- Arrow, K. in Discrimination in Labor Markets (eds Ashenfelter, O. & Rees, A.) 3–33 (Princeton Univ. Press, 1973).
- Phelps, E. The statistical theory of racism and sexism. Am. Econ. Rev. 62, 659–661 (1972).
Cited by
Sorted by citations
Items 201–300 of 548
Omitted and Included Variable Bias in Tests for Disparate ImpactPreprint
Jung, J., Corbett‐Davies, S., Shroff, R., & Goel, S. (2018) · arXiv (Cornell University) · Cited by 7
Self-citationBarajas, J. M. (2021) · doi:10.31235/osf.io/wszgv · Cited by 6
Enujioke, S. C., Aalsma, M. C., Meagher, C. G., Hunt, A. L., Hensley, M. M., & Ott, M. A. (2023) · International Journal of Offender Therapy and Comparative Criminology · doi:10.1177/0306624x231159878 · Cited by 5
“When adolescents and young adults are stopped involuntarily, minorities tend to face harsher treatment and are perceived to be guilty, implying that race influences decision-making (Bandes et al., 2019; Del Toro et al., 2019; Hester & Gray, 2018; Manski & Nagin, 2017; Pierson et al., 2020).”
Prosecutor‐driven reform and racial disparities
Amaral, F. A., Ouss, A., & Ozier, D. (2025) · Criminology & Public Policy · doi:10.1111/1745-9133.12699 · Cited by 6
Hartley, R. D., Tillyer, M. S., Tregle, B., & Smith, M. R. (2025) · Journal of Criminal Justice · doi:10.1016/j.jcrimjus.2025.102411 · Cited by 5
The impact of changing ambient population composition on crime during COVID-19 lockdowns
Gu, X., Liu, L., Han, S. Y., et al. (2025) · Applied Geography · doi:10.1016/j.apgeog.2025.103649 · Cited by 5
Can speed cameras make streets safer? Quasi-experimental evidence from New York City
Stagoff-Belfort, A., Ben-Menachem, J., & Beck, B. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2520328122 · Cited by 5
Craig, M. O., & Blount‐Hill, K. (2022) · Crime & Delinquency · doi:10.1177/00111287221100953 · Cited by 5
“For example, Pierson et al. (2020) state that “if black drivers, hypothetically, spend more time on the road than white drivers, that could explain the higher stop rates we see for the former” (p. 737).”
BackgroundRacial Disparities in the Criminal Legal System: Shadows of Doubt and Beyond
Agan, A. (2024) · Journal of Economic Literature · doi:10.1257/jel.20221569 · Cited by 6
Pipe dreams: Cannabis legalization and the persistence of racial disparities in jail incarceration
Wu, G., Durante, K. A., & Melton, H. C. (2024) · Journal of Criminal Justice · doi:10.1016/j.jcrimjus.2024.102230 · Cited by 5
Driving While Broke: The Role of Class Signals in Police Discretion
Knode, J. L., Carter, T. M., & Wolfe, S. E. (2024) · Justice Quarterly · doi:10.1080/07418825.2024.2398543 · Cited by 5
“Consistent with prior research demonstrating that groups overrepresented in searches lead to less efficient recovery of contraband (Carroll & Gonzalez, 2014; Engel & Johnson, 2006; Pierson et al., 2020), we hypothesize that searches of lower value vehicles will have lower contraband recovery rates.”
Beyond Traditional Conceptions of Policing and Crime Control
Rosenbaum, D. P. (2025) · Cambridge University Press eBooks · doi:10.1017/9781009612784 · Cited by 6
Fairness as adequacy: a sociotechnical view on model evaluation in machine learning
Grote, T. (2023) · AI and Ethics · doi:10.1007/s43681-023-00280-x · Cited by 6
“For members of marginalized groups, this may lead to an increase in stop-and-frisk [62, 63].”
Brownlow, B. N., Harmon, K., Pek, J. C. X., Cheavens, J. S., Moore, J. L., & Coccaro, E. F. (2024) · Clinical Psychological Science · doi:10.1177/21677026231217312 · Cited by 5
“This is evidenced by Black individuals being twice as likely to be stopped by police (Baumgartner et al., 2018) and 2.5 times more likely to be searched in a traffic stop despite greater rates of contraband found in searches of White drivers (Pierson et al., 2020).”
InfluentialSchleimer, J. P., Haviland, M. J., Gallagher, A., Mustafa, A., Ross, R., Wintemute, G. J., Bowen, D. M., & Rowhani‐Rahbar, A. (2024) · AJPM Focus · doi:10.1016/j.focus.2024.100206 · Cited by 7
“− 25, 53 In turn, prior criminal history may set the stage for more severe One important collateral consequence of criminal convictions is criminal history − based fi rearm prohibi-tions.”
BackgroundThe Biased Enforcement of Rarely Followed Rules
Wylie, J., Milless, K. L., Sciarappo, J., & Gantman, A. P. (2024) · Personality and Social Psychology Bulletin · doi:10.1177/01461672241252853 · Cited by 5
“Notably, the rate of stopping Black drivers decreases at night when visible racial information about drivers is more obscured (Pierson et al., 2020).”
A Sociobehavioral Model of Racism against the Black Community and Avenues for Anti-Racism Research
Belisle, J., Payne, A. N., & Paliliunas, D. (2022) · Behavior Analysis in Practice · doi:10.1007/s40617-022-00702-y · Cited by 5
Vehicle Stops and Group Position: How Missouri Agencies Use Place and Race to Explain Disparities
Craig, M. O., Reid, J. C., & Kramer, K. L. (2022) · Journal of Contemporary Criminal Justice · doi:10.1177/10439862221110996 · Cited by 5
“…composition of a particular place impacts police decisions on whether to stop and search motorists from groups that are considered “out-of-place” (e.g., Carroll & Gonzalez, 2014; Close & Mason, 2007; Hannon et al., 2021; Levchak, 2017; Meehan & Ponder, 2002; Pierson et al., 2020; Renauer, 2012).”
BackgroundExperiences of police‐related stress among a U.S. national cohort of gay and bisexual men
Bacchus, E. C., D’Angelo, A. B., & Grov, C. (2023) · American Journal of Community Psychology · doi:10.1002/ajcp.12683 · Cited by 5
Stereotypes, Crime, and Policing
O’Flaherty, B., & Sethi, R. (2023) · Annual Review of Criminology · doi:10.1146/annurev-criminol-022422-120610 · Cited by 8
Edwards, K. T. (2020) · Curriculum Inquiry · doi:10.1080/03626784.2020.1860641 · Cited by 7
“The legacy of this nation’s founding is evidenced in the persistence of structural inequalities along a variety of dimensions such as health, wealth, policing, and education (Horsford, 2011; Pierson et al., 2020; Robles et al., 2006).”
BackgroundEffects of officer perception of race and racial tensions on support for body-worn-cameras
Powell-Williams, M., Powell-Williams, T., & Hunt, H. D. (2020) · Journal of Ethnicity in Criminal Justice · doi:10.1080/15377938.2020.1842281 · Cited by 5
“It is well documented that racial disparities are evident in every stage of the American criminal justice process, including officer-initiated stops (Epp, Maynard-Moody, and Haider-Markel, 2014; Fagan, 2010; Gelman, Fagan, & Kiss, 2007; Goel & Phillips, 2017; Pierson et al., 2019; Spitzer, 1999), use of force (Mesic e…”
BackgroundDo Police Maximize Arrests or Minimize Crime? Evidence from Racial Profiling in U.S. CitiesPreprint
Stashko, A. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3132046 · Cited by 5
Fiscal Pressures and Discriminatory Policing: Evidence from Traffic Stops in MissouriPreprint
Harris, A. P., Ash, E., & Fagan, J. A. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3192562 · Cited by 5
“Are you supposed to be here?”: Formerly incarcerated men of color navigating positions of authority
Crain, E. E., Davis, L. S., Louis, G. S., Jensen, H., Robertson, I., Meade, G., Carrasco, S., Overbey, D., & Alves, L. (2024) · Journal of Social Issues · doi:10.1111/josi.12613 · Cited by 4
An experimental look at reasonable suspicion and police discretion
McLean, K. D., Nix, J., Stoughton, S. W., Adams, I. T., & Alpert, G. P. (2023) · Policing An International Journal · doi:10.1108/pijpsm-01-2023-0002 · Cited by 5
Belisle, J., Payne, A. N., Sellers, B., Sickman, E., & Hutchison, L. (2023) · Behavior and Social Issues · doi:10.1007/s42822-023-00134-5 · Cited by 4
“Bias in policing extends beyond shootings; Black people are faced with an increased likelihood of being stopped by the police (Pierson et al., 2020) as well as a disproportionate arrest and imprisonment rate as compared to White people (Schlei-den et al., 2020).”
Delegated Vigilantism and Less-than-Lethal Lynching in Twenty-First-Century America
Tonry, M. (2023) · Crime and Justice · doi:10.1086/726880 · Cited by 4
“Black people are much more likely than Whites to be stopped by the police (Pierson et al. 2020).”
BackgroundForgotten but not gone: A multi-state analysis of modern-day debt imprisonment
Gaebler, J. D., Barghouty, P., Vicol, S., Phillips, C., & Goel, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0290397 · Cited by 3
Self-citationWhat Does it Mean to Say “The Criminal Justice System is Racist”?
Wirts, A. M. (2023) · American Philosophical Quarterly · doi:10.5406/21521123.60.4.03 · Cited by 4
“…to white people in every significant stage of engagement with the criminal justice system, including traffic stops (Shoub 2020; Baumgartner 2018; Pierson 2020), arrests (Patten 2019; Mitchell and Coudy 2017), pre-trial detention and bail (Arnold et al. 2018); plea bargaining (Kutateladze 2016;…”
BackgroundInfluentialNivette, A. E., de Weegh, A. O., & Nägel, C. (2023) · Methodological Innovations · doi:10.1177/20597991231202854 · Cited by 4
“In a nationally representative sample of people aged 16 years and over in the United States, 24% reported having had personal contact with the police in the past 12 months (Harrell and Davis, 2020).”
BackgroundInfluentialContact with and Perceptions of Campus Police Among College Students at a Small-Town University
Finkeldey, J. G., Dennison, C. R., Reyes, N. T., DiRusso, A., & Brown, M. (2024) · Criminal Justice Review · doi:10.1177/07340168241240450 · Cited by 4
“…by law enforcement compared with White individuals (Avdija, 2014; Barnes et al., 2015; Davis et al., 2018; Federal Bureau of Investigation, 2019; Gelman et al., 2007; Kochel et al., 2011; Kovera, 2019; Mitchell & Caudy, 2015; Pierson et al., 2020; Snyder et al., 2020; Stewart et al., 2020).”
Carter, T. M., Wolfe, S. E., Knode, J. L., & Henry, G. H. (2024) · Criminology & Public Policy · doi:10.1111/1745-9133.12664 · Cited by 4
Data Collection and Analysis for Small-Town Policing: Challenges and Recommendations
Kelling, C., Haensch, A., Mendible, A., Brooks, S., Wiedemann, A., Aminian, M., Hasty, W., & Higdon, J. (2024) · Statistics and Public Policy · doi:10.1080/2330443x.2024.2379270 · Cited by 4
“These include initiatives such as the Police Data Initiative (National Policing Institute 2022), Mapping Police Violence (Campaign Zero 2023), Fatal Encoun-ters (Brian Burghart 2023), Stanford Open Policing Project (Pierson 2020), FiveThirtyEight’s Police Misconduct Settlement database (Thomson-DeVeaux, Bronner, and S…”
Mei, S., Deng, Y., Zheng, G., & Han, S. (2025) · Science Advances · doi:10.1126/sciadv.adt6207 · Cited by 4
Costs and Consequences of Traffic Fines and Fees: A Case Study of Open Warrants in Las Vegas, Nevada
Kamanga, F., Smercina, V. R., Brents, B. G., et al. (2021) · Social Sciences · doi:10.3390/socsci10110440 · Cited by 4
Are state minimum jail laws associated with less frequent drunk-driving?
Zamba, P. T., & Rossheim, M. E. (2022) · Traffic Injury Prevention · doi:10.1080/15389588.2022.2117984 · Cited by 4
“Although minimum jail laws could cause problems related to racial disparities in traffic stops (Pierson et al. 2020) and sentencing practices (Neils 2021), our findings suggest that minimum jail sentences are negatively associated with the frequency of self-reported drunk-driving.”
BackgroundA Multi-Site Study of Firearms Displays by Police at Use of Force Incidents
Cubitt, T. I. C., & Nix, J. (2022) · Police Quarterly · doi:10.1177/10986111221136230 · Cited by 4
“In other words, although we observed that Black citizens were no more or less likely than White citizens to have guns drawn on them during UOF incidents, we cannot say with certainty that Black people are equally likely overall to have an officer draw a gun on them, especially given that studies routinely show police…”
BackgroundA two-step process to increase successful geocoding in publicly available police stop data
Wallace, D. M., Helderop, E., Grubesic, T. H., et al. (2023) · Police Practice and Research · doi:10.1080/15614263.2023.2181169 · Cited by 4
“Currently, their data repository has data on over 100 million police stops available to researchers (see https://openpolicing.stanford.edu/data/; Pierson et al., 2020).”
BackgroundCochran, A. L., Wang, J., & Iacobucci, E. (2024) · Travel Behaviour and Society · doi:10.1016/j.tbs.2024.100871 · Cited by 4
Doesn’t everybody jaywalk? On codified rules that are seldom followed and selectively punishedPreprint
Wylie, J., & Gantman, A. P. (2020) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/yfsed · Cited by 4
Introduction to the Special Issue on Communication in Black Families
Hutchins, D., & Nelson, L. R. (2023) · Journal of Family Communication · doi:10.1080/15267431.2023.2243911 · Cited by 4
“This work supports extant research that explores how police officers use their positions of power to silence the Black community (Carbado & Richardson, 2018; Peeples, 2020; Pierson et al., 2020).”
ResultDetecting Bias in Traffic Searches: Examining False Searches of Innocent Drivers
Meyer, M., & Gonzalez, R. (2024) · Journal of Quantitative Criminology · doi:10.1007/s10940-024-09585-4 · Cited by 3
“Another special case of the benchmark test is the “veil of darkness test” (Grogger and Ridgeway 2006; Pierson et al. 2020), which assumes that if police officers are not relying on race for their search decisions, then the proportion of drivers stopped that are Black should not change between light…”
Anticipatory Violence and Health Among Black Adults in the United States
Semenza, D. C., VanHook, C. R., Baker, N. S., & Savage, B. (2025) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-024-02257-w · Cited by 4
“Black individuals are more likely to be stopped and arrested while driving [28], experience nonfatal police aggression [18], and are more likely to have militarized police units employed to their neighborhoods [29].”
Matsuzawa, K. (2025) · The Journal of Law and Economics · doi:10.1086/732666 · Cited by 3
Holtfreter, K., Pusch, N., & Wolfe, S. E. (2025) · Regulation & Governance · doi:10.1111/rego.70081 · Cited by 4
Police Pursuit Fatalities in the US, 2009 to 2023
Hendrix, A. N., Martin, T., Gazzetta, J., & Nunez, J. M. (2026) · JAMA Network Open · doi:10.1001/jamanetworkopen.2026.4340 · Cited by 3
Speech Recognition For Analysis of Police Radio Communication
Srivastava, T., Chou, J.-C., Shroff, P., Livescu, K., & Graziul, C. (2024) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt61566.2024.10832157 · Cited by 5
“To ensure even sampling of BPC across dispatch zones and day/night hours, we created 22 strata (11 zones × 2 levels), since zone captures spatial variation in reported crimes and policing personnel, while the timing of police stops (before/after sunset) impacts police behavior [19].”
MethodCarroll, S. L., Dio, A. M. D., Clark, S. L., Klump, K. L., Hyde, L. W., & Burt, S. A. (2025) · Development and Psychopathology · doi:10.1017/s0954579425100382 · Cited by 5
Characterizing patterns in police stops by race in Minneapolis from 2016 to 2021
Onookome-Okome, T., Gorondensky, J., Rose, E., et al. (2022) · Journal of Ethnicity in Criminal Justice · doi:10.1080/15377938.2022.2086192 · Cited by 3
“…related to racialized policing including support for the “veil of darkness” theory, excess stops of Black and Hispanic drivers compared to white drivers, and policy changes like the legalization of recreational marijuana failing to address racial disparities in police stops (Pierson et al., 2020).”
BackgroundExploring the Feasibility of Assessing Cultural Competence in Police Officers
Reichin, S. L., Jackson, A., Frame, M. C., & Hein, M. B. (2022) · Personnel Assessment and Decisions · doi:10.25035/pad.2022.02.003 · Cited by 3
Systematic Discovery of Bias in Data
Wamburu, J., Tadesse, G. A., Cintas, C., et al. (2022) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata55660.2022.10020781 · Cited by 3
“First, the detected subset is indeed made up of Hispanics, which aligns with the observations made in previous studies [6].”
BackgroundMethodResultInfluentialBoehme, H. M. (2023) · Policing A Journal of Policy and Practice · doi:10.1093/police/paad002 · Cited by 3
Rennert, L. (2022) · Cities · doi:10.1016/j.cities.2023.104308 · Cited by 5
The effects of immigration enforcement on traffic stops: Changing driver or police behavior?
van Tiem, B. (2023) · Criminology & Public Policy · doi:10.1111/1745-9133.12625 · Cited by 3
Data Science and Social Justice in the Mathematics Community
Jones, Q., Vindas-Meléndez, A. R., Mendible, A., Aminian, M., Brooks, H. Z., Alexander, N., Eaton, C. D., & Chodrow, P. S. (2023) · Notices of the American Mathematical Society · doi:10.1090/noti2773 · Cited by 3
Nivette, A. E., de Weegh, A. O., & Jaspers, E. (2023) · Journal of Developmental and Life-Course Criminology · doi:10.1007/s40865-023-00245-y · Cited by 3
“For example, Nihart and colleagues (Nihart et al., 2005) examined adolescents’ attitudes toward the police in the USA and found that those who held more positive feelings towards their parents and teachers also reported more positive feelings towards the police.”
InfluentialPark, K., Munson, M. R., Courtney, M. E., & Blair, K. (2023) · Journal of Public Child Welfare · doi:10.1080/15548732.2023.2279226 · Cited by 3
“…2014) and supports calls for continued reform of policing, courts, and corrections systems to address the ongoing consequences of institutional racism in the United States (Crutchfield, Skinner, Haggerty, McGlynn, & Catalano, 2012; Epp, Maynard-Moody, & Haider-Markel, 2017; Pierson et al., 2020).”
LeRoy, W. (2024) · Journal of Public Economics · doi:10.1016/j.jpubeco.2024.105117 · Cited by 3
How Long is Long Enough: Using Abbreviated Criminal Histories for Pretrial Assessment Instruments?
DeMichele, M. T., Inkpen, C. S., Silver, I. A., & Walker, J. W. (2024) · Justice Quarterly · doi:10.1080/07418825.2024.2422834 · Cited by 3
“Black people are more likely to be stopped, searched, arrested, and prosecuted than White people, and therefore will have higher scores on pretrial instruments (Kochel et al., 2011; Pierson et al., 2020; Stolzenberg et al., 2013).”
Donahue, S. T., & Torrats‐Espinosa, G. (2024) · American Journal of Sociology · doi:10.1086/734296 · Cited by 3
Benedictis-Kessner, J. D., Harvey, M., Jones, D. B., & Warshaw, C. (2025) · Science Advances · doi:10.1126/sciadv.adq8052 · Cited by 4
All Aboard: Light Rail, Mobility Justice, and the Future of Public Transit in Austin, TX
Karner, A. A., & Shuster, J. J. (2025) · Urban Affairs Review · doi:10.1177/10780874251315436 · Cited by 3
“…of urban regimes have visited substantial harm upon speci fi c population groups through overpolicing, forced displacement, exposure to environmental and human health harms, and denial of the bene fi ts of urban investments (Dillon and Poston 2021; Pierson et al. 2020; Pulido 2017; Rowangould 2013).”
Racial Discrimination in Asset Prices: Evidence From Horse Betting
Barnes, S., & Stein, L. C. D. (2025) · Financial Review · doi:10.1111/fire.70042 · Cited by 3
Traffic stops do not prevent traffic deaths
Sarode, A. L., Ho, V. P., Chen, L., et al. (2021) · The Journal of Trauma: Injury, Infection, and Critical Care · doi:10.1097/ta.0000000000003163 · Cited by 3
Dyer, T., Feelemyer, J., Scheidell, J. D., Turpin, R., Brewer, R., Mazumdar, M., Fortune, N., Severe, M., Cleland, C., Remch, M., et al. (2021) · Journal of Interpersonal Violence · doi:10.1177/08862605211021970 · Cited by 5
A fully Bayesian tracking algorithm for mitigating disparate prediction misclassification
Short, M. B., & Mohler, G. (2022) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2022.05.008 · Cited by 4
“The details of how we obtain these parameters are given below in Equations 22 and 25.”
BackgroundMethodSchuelke‐Leech, B., & Janczarski, M. (2019) · IEEE International Symposium on Technology and Society (ISTAS) · doi:10.1109/istas48451.2019.8937964 · Cited by 3
Black Men’s Experience of Police Harassment: A Descriptive Phenomenological Study
Townsell, A., Vogel, E. B., & McLean, A. (2021) · Journal of Phenomenological Psychology · doi:10.1163/15691624-12341385 · Cited by 3
Crozier, W., Garrett, B. L., & Modjadidi, K. (2020) · Social Science Research Network · doi:10.1080/24751979.2021.1976596 · Cited by 2
“Similarly, the criminal justice system disparately impacts people of color for many types of offenses, such as with traffic stops (Pierson et al., 2020; Warren, Tomaskovic-Devey, Smith, Zingraff, & Mason, 2006) and misdemeanors more generally (Stevenson & Mayson, 2018).”
BackgroundStelter, M., Essien, I., Sander, C., & Degner, J. (2021) · doi:10.31234/osf.io/djp8g · Cited by 3
Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-MakingPreprint
Schoeffer, J., De‐Arteaga, M., & Kuehl, N. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2209.11812 · Cited by 3
“…is neither a necessary nor sufficient requirement for fair decision-making [7, 27, 36, 63, 88, 94], and that there exist several real-world examples where the inclusion of sensitive features can make historically disadvantaged groups like Black people or women better off [27, 84, 97, 117].”
BackgroundOwusu-Bempah, A., Wallace, D., Gaston, S., Eason, J., & Sevell, E. (2024) · Sociology of Race and Ethnicity · doi:10.1177/23326492241232322 · Cited by 2
Machine Learning Classification Algorithms for Traffic Stops—A Comparative Study
Hoti, M. H., Misini, E., Lajçi, U., & Ahmedi, L. (2024) · International Journal of Online and Biomedical Engineering (iJOE) · doi:10.3991/ijoe.v20i07.47763 · Cited by 2
Assessing the Deterrent Effects of Ignition Interlock Devices
Zeithammer, R., Macinko, J. A., & Silver, D. (2024) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2024.09.009 · Cited by 2
Forest Fires and Climate Change Impacts on Water Resources
Verma, M., & Sati, M. (2025) · Springer eBooks · doi:10.1007/978-3-031-89967-6_9 · Cited by 3
The Ethics of Defunding the Police
Jones, B., & Lim, D. (2025) · Perspectives on Politics · doi:10.1017/s1537592725101850 · Cited by 2
Predictors of Sociopolitical Involvement Among White Young Adults During the Covid-19 Pandemic
Woolverton, G. A., Satterthwaite‐Freiman, M., Rastogi, R., Keum, B. T., Hahm, H. C., & Liu, C. H. (2025) · Race and Social Problems · doi:10.1007/s12552-025-09462-0 · Cited by 2
“White individuals who engage in equity-focused behaviors may risk decreased access to unearned resources associated with white privilege, such as greater employment opportunities or more favorable treatment by law enforcement (Bertrand & Mullainathan, 2004; Pierson et al., 2020).”
Abascal, M., Armenta, A., & Halm, W. M. (2025) · Socius Sociological Research for a Dynamic World · doi:10.1177/23780231251389022 · Cited by 2
“…focus on external classification because how others see and classify us affects how they treat us in consequential encounters, from reaching out to a loan officer (Hanson et al. 2016), to applying for a job (Pager, Bonikowski and Western 2009), to being stopped by the police (Pierson et al. 2020).”
Public opinion on police misconduct: Discrimination and information resistance
Eck, K., & Steinert, C. (2026) · Science Advances · doi:10.1126/sciadv.aeb9501 · Cited by 2
“We chose the empirical case of Germany for the following reasons: The literature on police misconduct has so far focused almost exclusively on the case of the United States [e.g., ( 15 , 16 , 18 , 64 – 66 )], but we know comparatively little about perceptions of police mis-conduct in Europe.”
Chan, E. W. (2026) · Journal of Statistics and Data Science Education · doi:10.1080/26939169.2026.2708903 · Cited by 2
Riser, Q. H., Rouse, H. L., & Dorius, C. J. (2023) · Children and Youth Services Review · doi:10.1016/j.childyouth.2023.106807 · Cited by 2
Racial Slurs by Police and Posttraumatic Stress Symptoms: Intrusive Policing and Perceived Injustice
McFarland, M. J., McFarland, C. A. S., Moniz, K., & Manley, L. (2023) · Journal of Urban Health · doi:10.1007/s11524-023-00747-6 · Cited by 2
“Police, however, are less likely to find contraband among Blacks than whites suggesting the bar for searches are lower among Blacks than whites [36].”
BackgroundPark, S., & Lum, C. M. (2023) · Policing An International Journal · doi:10.1108/pijpsm-05-2023-0062 · Cited by 2
Singichetti, B., Golightly, Y. M., Wang, Y. C., et al. (2024) · Accident Analysis & Prevention · doi:10.1016/j.aap.2023.107449 · Cited by 2
Skinner, J. (2024) · Criminal Justice Policy Review · doi:10.1177/08874034241264787 · Cited by 2
“During traffic stops, African Americans are also more likely to be searched and receive more severe outcomes in the form of citations and arrests (Baumgartner et al., 2018; Durose et al., 2007; Pierson et al., 2020; Roh & Robinson, 2009).”
Jauk, D., Peralta, R. L., & Michael, C. (2024) · Social Sciences · doi:10.3390/socsci13100505 · Cited by 2
“Discriminatory policing (i.e., unnecessary aggression, over-policing) and the greater likelihood of being stopped, searched, and shot are examples of discriminatory policing (Pierson et al. 2020; Hoekstra and Sloan 2022).”
Statistical Power and Search Intensity Bias in Hit Rates Tests of Discrimination
Lundberg, A. L. (2021) · Journal of Quantitative Criminology · doi:10.1007/s10940-021-09520-x · Cited by 1
Racial Disparities in Misdemeanor Speeding Convictions
Anwar, S., Bayer, P. J., Hjalmarsson, R., & Mizel, M. L. (2021) · RAND Corporation eBooks · doi:10.7249/rra1317-1 · Cited by 2
“The research examining racial disparities in motor vehicle stops and searches is extensive and typically finds that motorists in racial or ethnic minority groups are more likely than White motorists to have their vehicles stopped and searched for traffic violations (see Cordner, Williams, and Velasco, 2002; Farrell et…”
BackgroundLos Angeles Police Department (LAPD) Stops: Race and the Perception of Bias
Vernon, P. B., & Lynn, T. J. (2021) · Journal of Law and Criminal Justice · doi:10.15640/jlcj.v9n1a11 · Cited by 2
Trucks Don’t Mean Trump: Diagnosing Human Error in Image Analysis
Zamfirescu-Pereira, J. D., Chen, J., Wen, E., Koenecke, A., Garg, N., & Pierson, E. (2022) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3531146.3533145 · Cited by 3
“For example, in criminal justice [30, 36, 40, 44, 55, 57], algorithms have been used to diagnose human error in bail decisions [40, 44] and stop-and-frisk [30, 36],”
BackgroundMethodSelf-citationRanganath, A. (2022) · Journal of Map & Geography Libraries · doi:10.1080/15420353.2022.2107598 · Cited by 2
The Past as Prologue: Police Stops and Legacies of Complaints About Neighborhood Police Misconduct
McCarthy, B., Hagan, J. L., Herda, D., & Skogan, W. G. (2023) · Race and Justice · doi:10.1177/21533687221140553 · Cited by 2
“Stop studies with national (Pierson et al., 2020), state (Baumgartner et al., 2018), and city-level data (ACLU 2015, 2017; D ’ Souza et al., 2019; Fagan et al., 2010; Gelman et al., 2007; Goel et al., 2016; Hannon, 2020; Levchak, 2021; Rojek et al., 2012; Stults et al., 2010) generally fi nd that…”
Duquette, K., Challenger, C. D., & Eng, T. (2023) · Professional School Counseling · doi:10.1177/2156759x231161509 · Cited by 3
“Today ’ s adolescents are also living in a United States where they see racial disparities in policing (Pierson et al., 2020), rising hate crimes (Edwards & Rushin, 2019), and increased polarization across political and ideo-logical lines (Abramowitz & McCoy, 2018).”
BackgroundPolicing, Lethal Force, and the Struggle for Equal Treatment: The Doug Purvis Memorial Lecture
Gillezeau, R. (2023) · Canadian-American public policy · doi:10.3138/cpp.2023-010 · Cited by 2
Lead and delinquency rates; A spatio-temporal perspective
Mayer, D. J. (2023) · Social Science & Medicine · doi:10.1016/j.socscimed.2023.116513 · Cited by 3
(2019) · Psychology Crime and Law · doi:10.1080/1068316x.2019.1669599 · Cited by 2
“Consistent with previous observations (Baumgartner, Epp, et al., 2017; Engel & Calnon, 2004; Pierson et al., 2017), blacks and Hispanics left encounters with more severe outcomes.”
BackgroundResultRetractedRace and the Criminal Justice System
Fernandes, A. D., & Crutchfield, R. D. (2019) · The Handbook of Social Control · doi:10.1002/9781119372394.ch10 · Cited by 1
Secretary Problems with Biased Evaluations using Partial Ordinal InformationPreprint
Salem, J., & Gupta, S. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3444283 · Cited by 2
Learning Fair and Interpretable Representations via Linear OrthogonalizationPreprint
He, Y., Burghardt, K., & Lerman, K. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.12854 · Cited by 4
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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