{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:43:43Z","timestamp":1772264623976,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":129,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,7,21]],"date-time":"2021-07-21T00:00:00Z","timestamp":1626825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Partnership on AI"},{"name":"PwC"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,7,21]]},"DOI":"10.1145\/3461702.3462538","type":"proceedings-article","created":{"date-parts":[[2021,7,31]],"date-time":"2021-07-31T01:21:38Z","timestamp":1627694498000},"page":"100-111","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":26,"title":["On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes"],"prefix":"10.1145","author":[{"given":"Riccardo","family":"Fogliato","sequence":"first","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Alice","family":"Xiang","sequence":"additional","affiliation":[{"name":"Sony AI, Seattle, WA, USA"}]},{"given":"Zachary","family":"Lipton","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Daniel","family":"Nagin","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Alexandra","family":"Chouldechova","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]}],"member":"320","published-online":{"date-parts":[[2021,7,30]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"International Conference on Machine Learning. PMLR, 60--69","author":"Agarwal Alekh","year":"2018","unstructured":"Alekh Agarwal , Alina Beygelzimer , Miroslav Dud'ik , John Langford , and Hanna Wallach . 2018 . A reductions approach to fair classification . In International Conference on Machine Learning. PMLR, 60--69 . Alekh Agarwal, Alina Beygelzimer, Miroslav Dud'ik, John Langford, and Hanna Wallach. 2018. A reductions approach to fair classification. In International Conference on Machine Learning. PMLR, 60--69."},{"key":"e_1_3_2_2_2_1","volume-title":"Code of the street: Decency, violence, and the moral life of the inner city","author":"Anderson Elijah","unstructured":"Elijah Anderson . 2000. Code of the street: Decency, violence, and the moral life of the inner city . WW Norton & Company . Elijah Anderson. 2000. Code of the street: Decency, violence, and the moral life of the inner city .WW Norton & Company."},{"key":"e_1_3_2_2_3_1","volume-title":"Machine Bias: There's Software Used Across the Country to Predict Future Criminals. And it's Biased Against Blacks.","author":"Angwin Julia","year":"2016","unstructured":"Julia Angwin , Jeff Larson , Surya Mattu , and Lauren Kirchner . 2016 . Machine Bias: There's Software Used Across the Country to Predict Future Criminals. And it's Biased Against Blacks. (2016). https:\/\/www.propublica.org\/article\/machine-bias-risk-assessments-in-criminal-sentencing. Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016. Machine Bias: There's Software Used Across the Country to Predict Future Criminals. And it's Biased Against Blacks. (2016). https:\/\/www.propublica.org\/article\/machine-bias-risk-assessments-in-criminal-sentencing."},{"key":"e_1_3_2_2_4_1","volume-title":"Multiple imputation by chained equations: what is it and how does it work? International journal of methods in psychiatric research","author":"Azur Melissa J","year":"2011","unstructured":"Melissa J Azur , Elizabeth A Stuart , Constantine Frangakis , and Philip J Leaf . 2011. Multiple imputation by chained equations: what is it and how does it work? International journal of methods in psychiatric research , Vol. 20 , 1 ( 2011 ), 40--49. Melissa J Azur, Elizabeth A Stuart, Constantine Frangakis, and Philip J Leaf. 2011. Multiple imputation by chained equations: what is it and how does it work? International journal of methods in psychiatric research, Vol. 20, 1 (2011), 40--49."},{"key":"e_1_3_2_2_5_1","volume-title":"Conference on Fairness, Accountability and Transparency. PMLR, 62--76","author":"Barabas Chelsea","year":"2018","unstructured":"Chelsea Barabas , Madars Virza , Karthik Dinakar , Joichi Ito , and Jonathan Zittrain . 2018 . Interventions over predictions: Reframing the ethical debate for actuarial risk assessment . In Conference on Fairness, Accountability and Transparency. PMLR, 62--76 . Chelsea Barabas, Madars Virza, Karthik Dinakar, Joichi Ito, and Jonathan Zittrain. 2018. Interventions over predictions: Reframing the ethical debate for actuarial risk assessment. In Conference on Fairness, Accountability and Transparency. PMLR, 62--76."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v067.i01"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.2010.00182.x"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10940-017-9357-6"},{"key":"e_1_3_2_2_9_1","volume-title":"A convex framework for fair regression. arXiv preprint arXiv:1706.02409","author":"Berk Richard","year":"2017","unstructured":"Richard Berk , Hoda Heidari , Shahin Jabbari , Matthew Joseph , Michael Kearns , Jamie Morgenstern , Seth Neel , and Aaron Roth . 2017. A convex framework for fair regression. arXiv preprint arXiv:1706.02409 ( 2017 ). Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael Kearns, Jamie Morgenstern, Seth Neel, and Aaron Roth. 2017. A convex framework for fair regression. arXiv preprint arXiv:1706.02409 (2017)."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1177\/1525107115623943"},{"key":"e_1_3_2_2_11_1","volume-title":"The behavior of law","author":"Black Donald","unstructured":"Donald Black . 1976. The behavior of law . New York : Academic Press . Donald Black. 1976. The behavior of law. New York: Academic Press."},{"key":"e_1_3_2_2_12_1","volume-title":"Toward a theory of minority-group relations","author":"Blalock Hubert M","unstructured":"Hubert M Blalock . 1967. Toward a theory of minority-group relations . Vol. 325 . New York : Wiley . Hubert M Blalock. 1967. Toward a theory of minority-group relations. Vol. 325. New York: Wiley."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10940-010-9121-7"},{"key":"e_1_3_2_2_14_1","volume-title":"Mobilizing law in urban areas: The social structure of homicide clearance rates","author":"Borg Marian J","year":"2001","unstructured":"Marian J Borg and Karen F Parker . 2001. Mobilizing law in urban areas: The social structure of homicide clearance rates . Law and Society Review ( 2001 ), 435--466. Marian J Borg and Karen F Parker. 2001. Mobilizing law in urban areas: The social structure of homicide clearance rates. Law and Society Review (2001), 435--466."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1177\/1541204004265877"},{"key":"e_1_3_2_2_16_1","first-page":"545","article-title":"Models as Approximations II","volume":"34","author":"Buja Andreas","year":"2019","unstructured":"Andreas Buja , Lawrence Brown , Arun Kumar Kuchibhotla , Richard Berk , Edward George , Linda Zhao , 2019 . Models as Approximations II : A Model-Free Theory of Parametric Regression. Statist. Sci. , Vol. 34 , 4 (2019), 545 -- 565 . Andreas Buja, Lawrence Brown, Arun Kumar Kuchibhotla, Richard Berk, Edward George, Linda Zhao, et al. 2019. Models as Approximations II: A Model-Free Theory of Parametric Regression. Statist. Sci., Vol. 34, 4 (2019), 545--565.","journal-title":"A Model-Free Theory of Parametric Regression. Statist. Sci."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.1997.tb00873.x"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.2007.00084.x"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287586"},{"key":"e_1_3_2_2_20_1","volume-title":"Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. Big data","author":"Chouldechova Alexandra","year":"2017","unstructured":"Alexandra Chouldechova . 2017. Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. Big data , Vol. 5 , 2 ( 2017 ), 153--163. Alexandra Chouldechova. 2017. Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. Big data, Vol. 5, 2 (2017), 153--163."},{"key":"e_1_3_2_2_21_1","volume-title":"Sociological Forum","author":"Clampet-Lundquist Susan","unstructured":"Susan Clampet-Lundquist , Patrick J Carr , and Maria J Kefalas . 2015. The sliding scale of snitching: A qualitative examination of snitching in three Philadelphia communities . In Sociological Forum , Vol. 30 . Wiley Online Library , 265--285. Susan Clampet-Lundquist, Patrick J Carr, and Maria J Kefalas. 2015. The sliding scale of snitching: A qualitative examination of snitching in three Philadelphia communities. In Sociological Forum, Vol. 30. Wiley Online Library, 265--285."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098095"},{"key":"e_1_3_2_2_23_1","unstructured":"G\u00c3\u00a1bor Cs\u00c3\u00a1rdi. 2021. cli: Helpers for Developing Command Line Interfaces. https:\/\/CRAN.R-project.org\/package=cli R package version 2.3.0. G\u00c3\u00a1bor Cs\u00c3\u00a1rdi. 2021. cli: Helpers for Developing Command Line Interfaces. https:\/\/CRAN.R-project.org\/package=cli R package version 2.3.0."},{"key":"e_1_3_2_2_24_1","unstructured":"David B. Dahl David Scott Charles Roosen Arni Magnusson and Jonathan Swinton. 2019. xtable: Export Tables to LaTeX or HTML. https:\/\/CRAN.R-project.org\/package=xtable R package version 1.8--4. David B. Dahl David Scott Charles Roosen Arni Magnusson and Jonathan Swinton. 2019. xtable: Export Tables to LaTeX or HTML. https:\/\/CRAN.R-project.org\/package=xtable R package version 1.8--4."},{"key":"e_1_3_2_2_25_1","volume-title":"Race and the probability of arrest. Social forces","author":"D'Alessio Stewart J","year":"2003","unstructured":"Stewart J D'Alessio and Lisa Stolzenberg . 2003. Race and the probability of arrest. Social forces , Vol. 81 , 4 ( 2003 ), 1381--1397. Stewart J D'Alessio and Lisa Stolzenberg. 2003. Race and the probability of arrest. Social forces, Vol. 81, 4 (2003), 1381--1397."},{"key":"e_1_3_2_2_26_1","unstructured":"William Dieterich Christina Mendoza and Tim Brennan. 2016. COMPAS Risk Scales: Demonstrating Accuracy Equity and Predictive Parity. (2016). William Dieterich Christina Mendoza and Tim Brennan. 2016. COMPAS Risk Scales: Demonstrating Accuracy Equity and Predictive Parity. (2016)."},{"key":"e_1_3_2_2_27_1","volume-title":"Empirical risk minimization under fairness constraints. arXiv preprint arXiv:1802.08626","author":"Donini Michele","year":"2018","unstructured":"Michele Donini , Luca Oneto , Shai Ben-David , John Shawe-Taylor , and Massimiliano Pontil . 2018. Empirical risk minimization under fairness constraints. arXiv preprint arXiv:1802.08626 ( 2018 ). Michele Donini, Luca Oneto, Shai Ben-David, John Shawe-Taylor, and Massimiliano Pontil. 2018. Empirical risk minimization under fairness constraints. arXiv preprint arXiv:1802.08626 (2018)."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9133.2003.tb00126.x"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1353\/sof.2003.0007"},{"key":"e_1_3_2_2_30_1","first-page":"261","article-title":"Police, race, and the production of capital homicides","volume":"23","author":"Fagan Jeffrey","year":"2018","unstructured":"Jeffrey Fagan and Amanda Geller . 2018 . Police, race, and the production of capital homicides . Berkeley J. Crim. L. , Vol. 23 (2018), 261 . Jeffrey Fagan and Amanda Geller. 2018. Police, race, and the production of capital homicides. Berkeley J. Crim. L., Vol. 23 (2018), 261.","journal-title":"Berkeley J. Crim. L."},{"key":"e_1_3_2_2_31_1","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2004. Uniform crime reporting handbook. United States Department of Justice Federal Bureau of Investigation. 2004. Uniform crime reporting handbook."},{"key":"e_1_3_2_2_32_1","volume-title":"National Incident-Based Reporting System","author":"United States Department of Justice Federal Bureau of Investigation. 2009a.","year":"2007","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2009a. National Incident-Based Reporting System , 2007 . (2009). https:\/\/doi.org\/10.3886\/ICPSR25113.v1 United States Department of Justice Federal Bureau of Investigation. 2009a. National Incident-Based Reporting System, 2007. (2009). https:\/\/doi.org\/10.3886\/ICPSR25113.v1"},{"key":"e_1_3_2_2_33_1","volume-title":"Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data","author":"United States Department of Justice Federal Bureau of Investigation. 2009b.","year":"2007","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2009b. Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data , 2007 . (2009). https:\/\/doi.org\/10.3886\/ICPSR25104.v1 United States Department of Justice Federal Bureau of Investigation. 2009b. Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data, 2007. (2009). https:\/\/doi.org\/10.3886\/ICPSR25104.v1"},{"key":"e_1_3_2_2_34_1","volume-title":"National Incident-Based Reporting System","author":"United States Department of Justice Federal Bureau of Investigation. 2010a.","year":"2008","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2010a. National Incident-Based Reporting System , 2008 . (2010). https:\/\/doi.org\/10.3886\/ICPSR27647.v1 United States Department of Justice Federal Bureau of Investigation. 2010a. National Incident-Based Reporting System, 2008. (2010). https:\/\/doi.org\/10.3886\/ICPSR27647.v1"},{"key":"e_1_3_2_2_35_1","volume-title":"Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data","author":"United States Department of Justice Federal Bureau of Investigation. 2010b.","year":"2008","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2010b. Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data , 2008 . (2010). https:\/\/doi.org\/10.3886\/ICPSR27646.v1 United States Department of Justice Federal Bureau of Investigation. 2010b. Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data, 2008. (2010). https:\/\/doi.org\/10.3886\/ICPSR27646.v1"},{"key":"e_1_3_2_2_36_1","volume-title":"Uniform Crime Reporting: National Incident-Based Reporting System","author":"United States Department of Justice Federal Bureau of Investigation. 2011a.","year":"2009","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2011a. Uniform Crime Reporting: National Incident-Based Reporting System , 2009 . (2011). https:\/\/doi.org\/10.3886\/ICPSR30770.v1 United States Department of Justice Federal Bureau of Investigation. 2011a. Uniform Crime Reporting: National Incident-Based Reporting System, 2009. (2011). https:\/\/doi.org\/10.3886\/ICPSR30770.v1"},{"key":"e_1_3_2_2_37_1","volume-title":"Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data","author":"United States Department of Justice Federal Bureau of Investigation. 2011b.","year":"2009","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2011b. Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data , 2009 . (2011). https:\/\/doi.org\/10.3886\/ICPSR30765.v1 United States Department of Justice Federal Bureau of Investigation. 2011b. Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data, 2009. (2011). https:\/\/doi.org\/10.3886\/ICPSR30765.v1"},{"key":"e_1_3_2_2_38_1","volume-title":"Uniform Crime Reporting: National Incident-Based Reporting System","author":"United States Department of Justice Federal Bureau of Investigation. 2012a.","year":"2010","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2012a. Uniform Crime Reporting: National Incident-Based Reporting System , 2010 . (2012). https:\/\/doi.org\/10.3886\/ICPSR33530.v1 United States Department of Justice Federal Bureau of Investigation. 2012a. Uniform Crime Reporting: National Incident-Based Reporting System, 2010. (2012). https:\/\/doi.org\/10.3886\/ICPSR33530.v1"},{"key":"e_1_3_2_2_39_1","volume-title":"Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data","author":"United States Department of Justice Federal Bureau of Investigation. 2012b.","year":"2010","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2012b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data , 2010 . (2012). https:\/\/doi.org\/10.3886\/ICPSR33525.v1 United States Department of Justice Federal Bureau of Investigation. 2012b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data, 2010. (2012). https:\/\/doi.org\/10.3886\/ICPSR33525.v1"},{"key":"e_1_3_2_2_40_1","volume-title":"Uniform Crime Reporting Program Data: National Incident-Based Reporting System","author":"United States Department of Justice Federal Bureau of Investigation. 2013a.","year":"2011","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2013a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System , 2011 . (2013). https:\/\/doi.org\/10.3886\/ICPSR34585.v1 United States Department of Justice Federal Bureau of Investigation. 2013a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System, 2011. (2013). https:\/\/doi.org\/10.3886\/ICPSR34585.v1"},{"key":"e_1_3_2_2_41_1","volume-title":"Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data","author":"United States Department of Justice Federal Bureau of Investigation. 2013b.","year":"2011","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2013b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data , 2011 . (2013). https:\/\/doi.org\/10.3886\/ICPSR34584.v1 United States Department of Justice Federal Bureau of Investigation. 2013b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data, 2011. (2013). https:\/\/doi.org\/10.3886\/ICPSR34584.v1"},{"key":"e_1_3_2_2_42_1","volume-title":"Uniform Crime Reporting Program Data: National Incident-Based Reporting System","author":"United States Department of Justice Federal Bureau of Investigation. 2014a.","year":"2012","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2014a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System , 2012 . (2014). https:\/\/doi.org\/10.3886\/ICPSR35035.v1 United States Department of Justice Federal Bureau of Investigation. 2014a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System, 2012. (2014). https:\/\/doi.org\/10.3886\/ICPSR35035.v1"},{"key":"e_1_3_2_2_43_1","volume-title":"Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data","author":"United States Department of Justice Federal Bureau of Investigation. 2014b.","year":"2012","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2014b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data , 2012 . (2014). https:\/\/doi.org\/10.3886\/ICPSR35020.v1 United States Department of Justice Federal Bureau of Investigation. 2014b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data, 2012. (2014). https:\/\/doi.org\/10.3886\/ICPSR35020.v1"},{"key":"e_1_3_2_2_44_1","volume-title":"Uniform Crime Reporting Program Data: National Incident-Based Reporting System","author":"United States Department of Justice Federal Bureau of Investigation. 2015a.","year":"2013","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2015a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System , 2013 . (2015). https:\/\/doi.org\/10.3886\/ICPSR36120.v2 United States Department of Justice Federal Bureau of Investigation. 2015a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System, 2013. (2015). https:\/\/doi.org\/10.3886\/ICPSR36120.v2"},{"key":"e_1_3_2_2_45_1","volume-title":"Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data","author":"United States Department of Justice Federal Bureau of Investigation. 2015b.","year":"2013","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2015b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data , 2013 . (2015). https:\/\/doi.org\/10.3886\/ICPSR36119.v1 United States Department of Justice Federal Bureau of Investigation. 2015b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data, 2013. (2015). https:\/\/doi.org\/10.3886\/ICPSR36119.v1"},{"key":"e_1_3_2_2_46_1","volume-title":"Uniform Crime Reporting Program Data: National Incident-Based Reporting System","author":"United States Department of Justice Federal Bureau of Investigation. 2016a.","year":"2014","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2016a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System , 2014 . (2016). https:\/\/doi.org\/10.3886\/ICPSR36398.v1 United States Department of Justice Federal Bureau of Investigation. 2016a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System, 2014. (2016). https:\/\/doi.org\/10.3886\/ICPSR36398.v1"},{"key":"e_1_3_2_2_47_1","volume-title":"Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data","author":"United States Department of Justice Federal Bureau of Investigation. 2016b.","year":"2014","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2016b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data , 2014 . (2016). https:\/\/doi.org\/10.3886\/ICPSR36395.v1 United States Department of Justice Federal Bureau of Investigation. 2016b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data, 2014. (2016). https:\/\/doi.org\/10.3886\/ICPSR36395.v1"},{"key":"e_1_3_2_2_48_1","volume-title":"Uniform Crime Reporting Program Data: National Incident-Based Reporting System","author":"United States Department of Justice Federal Bureau of Investigation. 2017a.","year":"2015","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2017a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System , 2015 . (2017). https:\/\/doi.org\/10.3886\/ICPSR36795.v1 United States Department of Justice Federal Bureau of Investigation. 2017a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System, 2015. (2017). https:\/\/doi.org\/10.3886\/ICPSR36795.v1"},{"key":"e_1_3_2_2_49_1","volume-title":"Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data","author":"United States Department of Justice Federal Bureau of Investigation. 2017b.","year":"2015","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2017b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data , 2015 . (2017). https:\/\/doi.org\/10.3886\/ICPSR36791.v1 United States Department of Justice Federal Bureau of Investigation. 2017b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data, 2015. (2017). https:\/\/doi.org\/10.3886\/ICPSR36791.v1"},{"key":"e_1_3_2_2_50_1","volume-title":"Uniform Crime Reporting Program Data: National Incident-Based Reporting System, [United States]","author":"United States Department of Justice Federal Bureau of Investigation. 2018a.","year":"2016","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2018a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System, [United States] , 2016 . (2018). https:\/\/doi.org\/10.3886\/ICPSR37065.v2 United States Department of Justice Federal Bureau of Investigation. 2018a. Uniform Crime Reporting Program Data: National Incident-Based Reporting System, [United States], 2016. (2018). https:\/\/doi.org\/10.3886\/ICPSR37065.v2"},{"key":"e_1_3_2_2_51_1","volume-title":"United States, 2016","author":"United States Department of Justice Federal Bureau of Investigation.","year":"2018","unstructured":"United States Department of Justice Federal Bureau of Investigation. 2018 b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data , United States, 2016 . (2018). https:\/\/doi.org\/10.3886\/ICPSR37062.v1 United States Department of Justice Federal Bureau of Investigation. 2018b. Uniform Crime Reporting Program Data: Police Employee (LEOKA) Data, United States, 2016. (2018). https:\/\/doi.org\/10.3886\/ICPSR37062.v1"},{"key":"e_1_3_2_2_52_1","volume-title":"When are victims unlikely to cooperate with the police? Aggressive behavior","author":"Felson Richard B","year":"2016","unstructured":"Richard B Felson and Brendan Lantz . 2016. When are victims unlikely to cooperate with the police? Aggressive behavior , Vol. 42 , 1 ( 2016 ), 97--108. Richard B Felson and Brendan Lantz. 2016. When are victims unlikely to cooperate with the police? Aggressive behavior, Vol. 42, 1 (2016), 97--108."},{"key":"e_1_3_2_2_53_1","volume-title":"Longitudinal data analysis","author":"Fitzmaurice Garrett","unstructured":"Garrett Fitzmaurice , Marie Davidian , Geert Verbeke , and Geert Molenberghs . 2008. Longitudinal data analysis . CRC press . Garrett Fitzmaurice, Marie Davidian, Geert Verbeke, and Geert Molenberghs. 2008. Longitudinal data analysis .CRC press."},{"key":"e_1_3_2_2_54_1","volume-title":"\u201cMachine Bias: There's Software Used Across the Country to Predict Future Criminals. And it's Biased Against Blacks.\u201d. Unpublished manuscript","author":"Flores Anthony W","year":"2016","unstructured":"Anthony W Flores , Kristin Bechtel , and Christopher T Lowenkamp . 2016. False Positives , False Negatives , and False Analyses: A Rejoinder to \u201cMachine Bias: There's Software Used Across the Country to Predict Future Criminals. And it's Biased Against Blacks.\u201d. Unpublished manuscript ( 2016 ). Anthony W Flores, Kristin Bechtel, and Christopher T Lowenkamp. 2016. False Positives, False Negatives, and False Analyses: A Rejoinder to \u201cMachine Bias: There's Software Used Across the Country to Predict Future Criminals. And it's Biased Against Blacks.\u201d. Unpublished manuscript (2016)."},{"key":"e_1_3_2_2_55_1","volume-title":"Fairness Evaluation in Presence of Biased Noisy Labels. arXiv preprint arXiv:2003.13808","author":"Fogliato Riccardo","year":"2020","unstructured":"Riccardo Fogliato , Max G'Sell , and Alexandra Chouldechova . 2020. Fairness Evaluation in Presence of Biased Noisy Labels. arXiv preprint arXiv:2003.13808 ( 2020 ). Riccardo Fogliato, Max G'Sell, and Alexandra Chouldechova. 2020. Fairness Evaluation in Presence of Biased Noisy Labels. arXiv preprint arXiv:2003.13808 (2020)."},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1198\/000313006X152207"},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1214\/15-AOAS897"},{"key":"e_1_3_2_2_58_1","volume-title":"The accuracy, equity, and jurisprudence of criminal risk assessment. Equity, and Jurisprudence of Criminal Risk Assessment (December 26","author":"Goel Sharad","year":"2018","unstructured":"Sharad Goel , Ravi Shroff , Jennifer L Skeem , and Christopher Slobogin . 2018. The accuracy, equity, and jurisprudence of criminal risk assessment. Equity, and Jurisprudence of Criminal Risk Assessment (December 26 , 2018 ) (2018). Sharad Goel, Ravi Shroff, Jennifer L Skeem, and Christopher Slobogin. 2018. The accuracy, equity, and jurisprudence of criminal risk assessment. Equity, and Jurisprudence of Criminal Risk Assessment (December 26, 2018) (2018)."},{"key":"e_1_3_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372869"},{"key":"e_1_3_2_2_60_1","unstructured":"Mark Greenblatt Mark Fahey Bernice Yeung and Emily Harris. 2018. FBI Moves to Fix Critical Flaw in Its Crime Reporting System. (2018). https:\/\/www.propublica.org\/article\/fbi-moves-to-fix-critical-flaw-in-its-crime-reporting-system. Mark Greenblatt Mark Fahey Bernice Yeung and Emily Harris. 2018. FBI Moves to Fix Critical Flaw in Its Crime Reporting System. (2018). https:\/\/www.propublica.org\/article\/fbi-moves-to-fix-critical-flaw-in-its-crime-reporting-system."},{"key":"e_1_3_2_2_61_1","volume-title":"Equality of opportunity in supervised learning. arXiv preprint arXiv:1610.02413","author":"Hardt Moritz","year":"2016","unstructured":"Moritz Hardt , Eric Price , and Nathan Srebro . 2016. Equality of opportunity in supervised learning. arXiv preprint arXiv:1610.02413 ( 2016 ). Moritz Hardt, Eric Price, and Nathan Srebro. 2016. Equality of opportunity in supervised learning. arXiv preprint arXiv:1610.02413 (2016)."},{"key":"e_1_3_2_2_62_1","doi-asserted-by":"crossref","unstructured":"Jim Hester and Hadley Wickham. 2020. vroom: Read and Write Rectangular Text Data Quickly. https:\/\/CRAN.R-project.org\/package=vroom R package version 1.3.2. Jim Hester and Hadley Wickham. 2020. vroom: Read and Write Rectangular Text Data Quickly. https:\/\/CRAN.R-project.org\/package=vroom R package version 1.3.2.","DOI":"10.32614\/CRAN.package.vroom"},{"key":"e_1_3_2_2_63_1","volume-title":"Race and involvement in common law personal crimes. American sociological review","author":"Hindelang Michael J","year":"1978","unstructured":"Michael J Hindelang . 1978. Race and involvement in common law personal crimes. American sociological review ( 1978 ), 93--109. Michael J Hindelang. 1978. Race and involvement in common law personal crimes. American sociological review (1978), 93--109."},{"key":"e_1_3_2_2_64_1","first-page":"255","article-title":"Domestic violence and mandatory arrest laws: To what extent do they influence police arrest decisions","volume":"98","author":"Hirschel David","year":"2007","unstructured":"David Hirschel , Eve Buzawa , April Pattavina , and Don Faggiani . 2007 . Domestic violence and mandatory arrest laws: To what extent do they influence police arrest decisions . J. Crim. L. & Criminology , Vol. 98 (2007), 255 . David Hirschel, Eve Buzawa, April Pattavina, and Don Faggiani. 2007. Domestic violence and mandatory arrest laws: To what extent do they influence police arrest decisions. J. Crim. L. & Criminology, Vol. 98 (2007), 255.","journal-title":"J. Crim. L. & Criminology"},{"key":"e_1_3_2_2_65_1","volume-title":"Affirmative Algorithms: The Legal Grounds for Fairness as Awareness. arXiv preprint arXiv:2012.14285","author":"Ho Daniel E","year":"2020","unstructured":"Daniel E Ho and Alice Xiang . 2020 . Affirmative Algorithms: The Legal Grounds for Fairness as Awareness. arXiv preprint arXiv:2012.14285 (2020). Daniel E Ho and Alice Xiang. 2020. Affirmative Algorithms: The Legal Grounds for Fairness as Awareness. arXiv preprint arXiv:2012.14285 (2020)."},{"key":"e_1_3_2_2_66_1","doi-asserted-by":"crossref","unstructured":"Jared Huling. 2019. fastglm: Fast and Stable Fitting of Generalized Linear Models using 'RcppEigen'. https:\/\/CRAN.R-project.org\/package=fastglm R package version 0.0.1. Jared Huling. 2019. fastglm: Fast and Stable Fitting of Generalized Linear Models using 'RcppEigen'. https:\/\/CRAN.R-project.org\/package=fastglm R package version 0.0.1.","DOI":"10.32614\/CRAN.package.fastglm"},{"key":"e_1_3_2_2_67_1","doi-asserted-by":"publisher","DOI":"10.1214\/18-AOAS1201"},{"key":"e_1_3_2_2_68_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.2002.tb00976.x"},{"key":"e_1_3_2_2_69_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.0011-1348.2005.00014.x"},{"key":"e_1_3_2_2_70_1","unstructured":"Jacob Kaplan. 2020. asciiSetupReader: Reads Fixed-Width ASCII Data Files (.txt or .dat) that Have Accompanying Setup Files (.sps or .sas). https:\/\/CRAN.R-project.org\/package=asciiSetupReader R package version 2.3.2. Jacob Kaplan. 2020. asciiSetupReader: Reads Fixed-Width ASCII Data Files (.txt or .dat) that Have Accompanying Setup Files (.sps or .sas). https:\/\/CRAN.R-project.org\/package=asciiSetupReader R package version 2.3.2."},{"key":"e_1_3_2_2_71_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.0011-1348.2005.00022.x"},{"key":"e_1_3_2_2_72_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.2011.00226.x"},{"key":"e_1_3_2_2_73_1","volume-title":"Human decisions and machine predictions. The quarterly journal of economics","author":"Kleinberg Jon","year":"2018","unstructured":"Jon Kleinberg , Himabindu Lakkaraju , Jure Leskovec , Jens Ludwig , and Sendhil Mullainathan . 2018. Human decisions and machine predictions. The quarterly journal of economics , Vol. 133 , 1 ( 2018 ), 237--293. Jon Kleinberg, Himabindu Lakkaraju, Jure Leskovec, Jens Ludwig, and Sendhil Mullainathan. 2018. Human decisions and machine predictions. The quarterly journal of economics, Vol. 133, 1 (2018), 237--293."},{"key":"e_1_3_2_2_74_1","volume-title":"Inherent trade-offs in the fair determination of risk scores. arXiv preprint arXiv:1609.05807","author":"Kleinberg Jon","year":"2016","unstructured":"Jon Kleinberg , Sendhil Mullainathan , and Manish Raghavan . 2016. Inherent trade-offs in the fair determination of risk scores. arXiv preprint arXiv:1609.05807 ( 2016 ). Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan. 2016. Inherent trade-offs in the fair determination of risk scores. arXiv preprint arXiv:1609.05807 (2016)."},{"key":"e_1_3_2_2_75_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.1997.tb00877.x"},{"key":"e_1_3_2_2_76_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.2011.00230.x"},{"key":"e_1_3_2_2_77_1","volume-title":"Retaliatory homicide: Concentrated disadvantage and neighborhood culture. Social problems","author":"Kubrin Charis E","year":"2003","unstructured":"Charis E Kubrin and Ronald Weitzer . 2003. Retaliatory homicide: Concentrated disadvantage and neighborhood culture. Social problems , Vol. 50 , 2 ( 2003 ), 157--180. Charis E Kubrin and Ronald Weitzer. 2003. Retaliatory homicide: Concentrated disadvantage and neighborhood culture. Social problems, Vol. 50, 2 (2003), 157--180."},{"key":"e_1_3_2_2_78_1","volume-title":"The co-offender as counterfactual: A quasi-experimental within-partnership approach to the examination of the relationship between race and arrest. Journal of experimental criminology","author":"Lantz Brendan","year":"2019","unstructured":"Brendan Lantz and Marin R Wenger . 2019. The co-offender as counterfactual: A quasi-experimental within-partnership approach to the examination of the relationship between race and arrest. Journal of experimental criminology ( 2019 ), 1--24. Brendan Lantz and Marin R Wenger. 2019. The co-offender as counterfactual: A quasi-experimental within-partnership approach to the examination of the relationship between race and arrest. Journal of experimental criminology (2019), 1--24."},{"key":"e_1_3_2_2_79_1","volume-title":"Social structure and crime control among macrosocial units. American journal of sociology","author":"Liska Allen E","year":"1984","unstructured":"Allen E Liska and Mitchell B Chamlin . 1984. Social structure and crime control among macrosocial units. American journal of sociology , Vol. 90 , 2 ( 1984 ), 383--395. Allen E Liska and Mitchell B Chamlin. 1984. Social structure and crime control among macrosocial units. American journal of sociology, Vol. 90, 2 (1984), 383--395."},{"key":"e_1_3_2_2_80_1","doi-asserted-by":"publisher","DOI":"10.2307\/2578975"},{"key":"e_1_3_2_2_81_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10940-018-9381-1"},{"key":"e_1_3_2_2_82_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1740-9713.2016.00960.x"},{"key":"e_1_3_2_2_83_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcrimjus.2014.10.001"},{"key":"e_1_3_2_2_84_1","doi-asserted-by":"publisher","DOI":"10.1177\/0011128717694595"},{"key":"e_1_3_2_2_85_1","doi-asserted-by":"publisher","DOI":"10.1177\/0886260512468250"},{"key":"e_1_3_2_2_86_1","volume-title":"An algorithm that grants freedom, or takes it away. The New York Times","author":"Metz Cade","year":"2020","unstructured":"Cade Metz and Adam Satariano . 2020. An algorithm that grants freedom, or takes it away. The New York Times ( 2020 ). Cade Metz and Adam Satariano. 2020. An algorithm that grants freedom, or takes it away. The New York Times (2020)."},{"key":"e_1_3_2_2_87_1","volume-title":"Criminal victimization","author":"Morgan Rachel E","year":"2019","unstructured":"Rachel E Morgan and Jennifer L Truman . 2019. Criminal victimization , 2019 . Bureau of Justice Statistics , Vol . 845 (2019). Rachel E Morgan and Jennifer L Truman. 2019. Criminal victimization, 2019. Bureau of Justice Statistics, Vol. 845 (2019)."},{"key":"e_1_3_2_2_88_1","volume-title":"Biased algorithms are easier to fix than biased people. The New York Times","author":"Mullainathan Sendhil","year":"2019","unstructured":"Sendhil Mullainathan . 2019. Biased algorithms are easier to fix than biased people. The New York Times ( 2019 ). Sendhil Mullainathan. 2019. Biased algorithms are easier to fix than biased people. The New York Times (2019)."},{"key":"e_1_3_2_2_89_1","unstructured":"Kirill M\u00c3ller. 2020. here: A Simpler Way to Find Your Files. https:\/\/CRAN.R-project.org\/package=here R package version 1.0.1. Kirill M\u00c3ller. 2020. here: A Simpler Way to Find Your Files. https:\/\/CRAN.R-project.org\/package=here R package version 1.0.1."},{"key":"e_1_3_2_2_90_1","volume-title":"Federal Bureau of Investigation (FBI)","author":"United States Department of Justice.","year":"2019","unstructured":"United States Department of Justice. Federal Bureau of Investigation (FBI) . 2019 . 2019 National Incident-Based Reporting System User Manual . https:\/\/ucr.fbi.gov\/nibrs\/nibrs-user-manual United States Department of Justice. Federal Bureau of Investigation (FBI). 2019. 2019 National Incident-Based Reporting System User Manual. https:\/\/ucr.fbi.gov\/nibrs\/nibrs-user-manual"},{"key":"e_1_3_2_2_91_1","doi-asserted-by":"publisher","DOI":"10.1177\/0022427808317575"},{"key":"e_1_3_2_2_92_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.2005.00034.x"},{"key":"e_1_3_2_2_93_1","doi-asserted-by":"publisher","DOI":"10.1177\/0011128717724298"},{"key":"e_1_3_2_2_94_1","doi-asserted-by":"crossref","unstructured":"Emma Pierson Camelia Simoiu Jan Overgoor Sam Corbett-Davies Daniel Jenson Amy Shoemaker Vignesh Ramachandran Phoebe Barghouty Cheryl Phillips Ravi Shroff etal 2020. A large-scale analysis of racial disparities in police stops across the United States. Nature human behaviour (2020) 1--10. Emma Pierson Camelia Simoiu Jan Overgoor Sam Corbett-Davies Daniel Jenson Amy Shoemaker Vignesh Ramachandran Phoebe Barghouty Cheryl Phillips Ravi Shroff et al. 2020. A large-scale analysis of racial disparities in police stops across the United States. Nature human behaviour (2020) 1--10.","DOI":"10.1038\/s41562-020-0858-1"},{"key":"e_1_3_2_2_95_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10940-007-9030-6"},{"key":"e_1_3_2_2_96_1","unstructured":"Carl E Pope and Howard N Snyder. 2003. Race as a factor in juvenile arrests. US Department of Justice Office of Justice Programs Office of Juvenile.... Carl E Pope and Howard N Snyder. 2003. Race as a factor in juvenile arrests. US Department of Justice Office of Justice Programs Office of Juvenile...."},{"key":"e_1_3_2_2_97_1","doi-asserted-by":"publisher","DOI":"10.1177\/0022427803251125"},{"key":"e_1_3_2_2_98_1","volume-title":"Dirty data, bad predictions: How civil rights violations impact police data, predictive policing systems, and justice","author":"Richardson Rashida","year":"2019","unstructured":"Rashida Richardson , Jason Schultz , and Kate Crawford . 2019. Dirty data, bad predictions: How civil rights violations impact police data, predictive policing systems, and justice . New York University Law Review Online , Forthcoming ( 2019 ). Rashida Richardson, Jason Schultz, and Kate Crawford. 2019. Dirty data, bad predictions: How civil rights violations impact police data, predictive policing systems, and justice. New York University Law Review Online, Forthcoming (2019)."},{"key":"e_1_3_2_2_99_1","doi-asserted-by":"publisher","DOI":"10.1177\/0022427809335168"},{"key":"e_1_3_2_2_100_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10940-015-9270-9"},{"key":"e_1_3_2_2_101_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/63.3.581"},{"key":"e_1_3_2_2_102_1","volume-title":"Multiple imputation for nonresponse in surveys","author":"Rubin Donald B","unstructured":"Donald B Rubin . 2004. Multiple imputation for nonresponse in surveys . Vol. 81 . John Wiley & Sons . Donald B Rubin. 2004. Multiple imputation for nonresponse in surveys. Vol. 81. John Wiley & Sons."},{"key":"e_1_3_2_2_103_1","doi-asserted-by":"publisher","DOI":"10.1111\/1745-9125.12123"},{"key":"e_1_3_2_2_104_1","unstructured":"Frederick Solt and Kellen Gracey. 2020. icpsrdata: Reproducible Data Retrieval from the ICPSR Archive. https:\/\/CRAN.R-project.org\/package=icpsrdata R package version 0.5.0. Frederick Solt and Kellen Gracey. 2020. icpsrdata: Reproducible Data Retrieval from the ICPSR Archive. https:\/\/CRAN.R-project.org\/package=icpsrdata R package version 0.5.0."},{"key":"e_1_3_2_2_105_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.1987.tb00824.x"},{"key":"e_1_3_2_2_106_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.2010.00222.x"},{"key":"e_1_3_2_2_107_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9125.2004.tb00533.x"},{"key":"e_1_3_2_2_108_1","doi-asserted-by":"publisher","DOI":"10.1086\/518906"},{"key":"e_1_3_2_2_109_1","volume-title":"The role of procedural justice and legitimacy in shaping public support for policing. Law & society review","author":"Sunshine Jason","year":"2003","unstructured":"Jason Sunshine and Tom R Tyler . 2003. The role of procedural justice and legitimacy in shaping public support for policing. Law & society review , Vol. 37 , 3 ( 2003 ), 513--548. Jason Sunshine and Tom R Tyler. 2003. The role of procedural justice and legitimacy in shaping public support for policing. Law & society review, Vol. 37, 3 (2003), 513--548."},{"key":"e_1_3_2_2_110_1","volume-title":"R: A language and environment for statistical computing.","author":"R Core Team","year":"2013","unstructured":"R Core Team et al. 2013 . R: A language and environment for statistical computing. (2013). R Core Team et al. 2013. R: A language and environment for statistical computing. (2013)."},{"key":"e_1_3_2_2_111_1","doi-asserted-by":"publisher","DOI":"10.1177\/0022427803253800"},{"key":"e_1_3_2_2_112_1","volume-title":"Malign neglect: Race, crime, and punishment in America","author":"Tonry Michael","unstructured":"Michael Tonry . 1995. Malign neglect: Race, crime, and punishment in America . Oxford University Press . Michael Tonry. 1995. Malign neglect: Race, crime, and punishment in America .Oxford University Press."},{"key":"e_1_3_2_2_113_1","first-page":"231","article-title":"Legitimacy and cooperation: Why do people help the police fight crime in their communities","volume":"6","author":"Tyler Tom R","year":"2008","unstructured":"Tom R Tyler and Jeffrey Fagan . 2008 . Legitimacy and cooperation: Why do people help the police fight crime in their communities . Ohio St. J. Crim. L. , Vol. 6 (2008), 231 . Tom R Tyler and Jeffrey Fagan. 2008. Legitimacy and cooperation: Why do people help the police fight crime in their communities. Ohio St. J. Crim. L., Vol. 6 (2008), 231.","journal-title":"Ohio St. J. Crim. L."},{"key":"e_1_3_2_2_114_1","doi-asserted-by":"publisher","DOI":"10.1111\/jels.12055"},{"key":"e_1_3_2_2_115_1","unstructured":"Kevin Ushey. 2021. renv: Project Environments. https:\/\/CRAN.R-project.org\/package=renv R package version 0.12.5. Kevin Ushey. 2021. renv: Project Environments. https:\/\/CRAN.R-project.org\/package=renv R package version 0.12.5."},{"key":"e_1_3_2_2_116_1","first-page":"1","article-title":"mice: Multivariate Imputation by Chained Equations in R","volume":"45","author":"van Buuren Stef","year":"2011","unstructured":"Stef van Buuren and Karin Groothuis-Oudshoorn . 2011 . mice: Multivariate Imputation by Chained Equations in R . Journal of Statistical Software , Vol. 45 , 3 (2011), 1 -- 67 . https:\/\/www.jstatsoft.org\/v45\/i03\/ Stef van Buuren and Karin Groothuis-Oudshoorn. 2011. mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, Vol. 45, 3 (2011), 1--67. https:\/\/www.jstatsoft.org\/v45\/i03\/","journal-title":"Journal of Statistical Software"},{"key":"e_1_3_2_2_117_1","doi-asserted-by":"publisher","DOI":"10.1097\/EDE.0000000000000105"},{"key":"e_1_3_2_2_118_1","unstructured":"Davis Vaughan and Matt Dancho. 2021. furrr: Apply Mapping Functions in Parallel using Futures. https:\/\/CRAN.R-project.org\/package=furrr R package version 0.2.2. Davis Vaughan and Matt Dancho. 2021. furrr: Apply Mapping Functions in Parallel using Futures. https:\/\/CRAN.R-project.org\/package=furrr R package version 0.2.2."},{"key":"e_1_3_2_2_119_1","volume-title":"Race and crime: A biosocial analysis","author":"Walsh Anthony","unstructured":"Anthony Walsh . 2004. Race and crime: A biosocial analysis . Nova Publishers . Anthony Walsh. 2004. Race and crime: A biosocial analysis .Nova Publishers."},{"key":"e_1_3_2_2_120_1","first-page":"129","article-title":"Policing different racial groups in the United States","volume":"6","author":"Weitzer Ronald","year":"2015","unstructured":"Ronald Weitzer and Rod K Brunson . 2015 . Policing different racial groups in the United States . Cahiers Politiestudies , Vol. 6 , 35 (2015), 129 . Ronald Weitzer and Rod K Brunson. 2015. Policing different racial groups in the United States. Cahiers Politiestudies, Vol. 6, 35 (2015), 129.","journal-title":"Cahiers Politiestudies"},{"key":"e_1_3_2_2_121_1","doi-asserted-by":"publisher","DOI":"10.1177\/0011128799045004006"},{"key":"e_1_3_2_2_122_1","volume-title":"Race and perceptions of police misconduct. Social problems","author":"Weitzer Ronald","year":"2004","unstructured":"Ronald Weitzer and Steven A Tuch . 2004. Race and perceptions of police misconduct. Social problems , Vol. 51 , 3 ( 2004 ), 305--325. Ronald Weitzer and Steven A Tuch. 2004. Race and perceptions of police misconduct. Social problems, Vol. 51, 3 (2004), 305--325."},{"key":"e_1_3_2_2_123_1","doi-asserted-by":"publisher","DOI":"10.21105\/joss.01686"},{"key":"e_1_3_2_2_124_1","unstructured":"Hadley Wickham and Evan Miller. 2020. haven: Import and Export 'SPSS' 'Stata' and 'SAS' Files. https:\/\/CRAN.R-project.org\/package=haven R package version 2.3.1. Hadley Wickham and Evan Miller. 2020. haven: Import and Export 'SPSS' 'Stata' and 'SAS' Files. https:\/\/CRAN.R-project.org\/package=haven R package version 2.3.1."},{"key":"e_1_3_2_2_125_1","volume-title":"Varieties of police behavior: The Management of law and Order in eight communities, with a new preface by the author","author":"Wilson James Q","unstructured":"James Q Wilson . 1978. Varieties of police behavior: The Management of law and Order in eight communities, with a new preface by the author . Harvard University Press . James Q Wilson. 1978. Varieties of police behavior: The Management of law and Order in eight communities, with a new preface by the author .Harvard University Press."},{"key":"e_1_3_2_2_126_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10940-011-9140-z"},{"key":"e_1_3_2_2_127_1","volume-title":"Dynamic Documents with R and knitr","author":"Xie Yihui","unstructured":"Yihui Xie . 2015. Dynamic Documents with R and knitr 2 nd ed.). Chapman and Hall\/CRC , Boca Raton , Florida. https:\/\/yihui.org\/knitr\/ ISBN 978--1498716963. Yihui Xie. 2015. Dynamic Documents with R and knitr 2nd ed.). Chapman and Hall\/CRC, Boca Raton, Florida. https:\/\/yihui.org\/knitr\/ ISBN 978--1498716963.","edition":"2"},{"key":"e_1_3_2_2_128_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v095.i01"},{"key":"e_1_3_2_2_129_1","unstructured":"Hao Zhu. 2020. kableExtra: Construct Complex Table with 'kable' and Pipe Syntax. https:\/\/CRAN.R-project.org\/package=kableExtra R package version 1.3.1. Hao Zhu. 2020. kableExtra: Construct Complex Table with 'kable' and Pipe Syntax. https:\/\/CRAN.R-project.org\/package=kableExtra R package version 1.3.1."}],"event":{"name":"AIES '21: AAAI\/ACM Conference on AI, Ethics, and Society","location":"Virtual Event USA","acronym":"AIES '21","sponsor":["SIGAI ACM Special Interest Group on Artificial Intelligence","AAAI"]},"container-title":["Proceedings of the 2021 AAAI\/ACM Conference on AI, Ethics, and Society"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3461702.3462538","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3461702.3462538","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:49:06Z","timestamp":1750193346000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3461702.3462538"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,21]]},"references-count":129,"alternative-id":["10.1145\/3461702.3462538","10.1145\/3461702"],"URL":"https:\/\/doi.org\/10.1145\/3461702.3462538","relation":{},"subject":[],"published":{"date-parts":[[2021,7,21]]},"assertion":[{"value":"2021-07-30","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}