Epstein Secrets

ll and 58% of men);' that high scores are likely driven by static factors such as age of first conviction and criminal history 26 See Richard Berk, Acturag, and Fairness for Juvenile Jmike Risks Assessments, 16 J. EMPIRICAL LEG. STUD. 175, 184 (2019). 26 See DOJ Report at 29 (referring implicitly to wh

statistical experts, current and formerly incarcerated individuals, public defenders, public prosecutors, judges, and civil rights organizations"); Danielle Kehl et al., Algorithms in the Criminal Justice System 34 (2017), https:/ /dash.harvard.edu/ bitstream/ handle/1 /33746041 /2017- 07_responsivecommunities_2.pd

ll and 58% of men);' that high scores are likely driven by static factors such as age of first conviction and criminal history 26 See Richard Berk, Acturag, and Fairness for Juvenile Jmike Risks Assessments, 16 J. EMPIRICAL LEG. STUD. 175, 184 (2019). 26 See DOJ Report at 29 (referring implicitly to wh

statistical experts, current and formerly incarcerated individuals, public defenders, public prosecutors, judges, and civil rights organizations"); Danielle Kehl et al., Algorithms in the Criminal Justice System 34 (2017), https:/ /dash.harvard.edu/ bitstream/ handle/1 /33746041 /2017- 07_responsivecommunities_2.pd

ll and 58% of men);' that high scores are likely driven by static factors such as age of first conviction and criminal history 26 See Richard Berk, Acturag, and Fairness for Juvenile Jmike Risks Assessments, 16 J. EMPIRICAL LEG. STUD. 175, 184 (2019). 26 See DOJ Report at 29 (referring implicitly to wh

statistical experts, current and formerly incarcerated individuals, public defenders, public prosecutors, judges, and civil rights organizations"); Danielle Kehl et al., Algorithms in the Criminal Justice System 34 (2017), https:/ /dash.harvard.edu/ bitstream/ handle/1 /33746041 /2017- 07_responsivecommunities_2.pd