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

es: An Empirical Examination of the Effects ofCategorical Versus Probabilistic Risk Communication in Sexually Violent Predator Decisions, 36 BEHAV. SCI. & L. 532, 534 (2018); Nicholas Scoria, The Case Against Categorical Risk Estimates, 36 REHAV. So. & L. 554, 558 (2018). 76 Set Wisconsin u. Loomis, 881 N.W.

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

es: An Empirical Examination of the Effects ofCategorical Versus Probabilistic Risk Communication in Sexually Violent Predator Decisions, 36 BEHAV. SCI. & L. 532, 534 (2018); Nicholas Scoria, The Case Against Categorical Risk Estimates, 36 REHAV. So. & L. 554, 558 (2018). 76 Set Wisconsin u. Loomis, 881 N.W.

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

es: An Empirical Examination of the Effects ofCategorical Versus Probabilistic Risk Communication in Sexually Violent Predator Decisions, 36 BEHAV. SCI. & L. 532, 534 (2018); Nicholas Scoria, The Case Against Categorical Risk Estimates, 36 REHAV. So. & L. 554, 558 (2018). 76 Set Wisconsin u. Loomis, 881 N.W.