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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
• PNrrERN's score includes criminal history measures that did not require conviction and thereby may overestimate risk because of faulty data; • PNITERN's score may be higher based on evidence of juvenile offending • PATTERN may increase risk when the individual does not engage in various types of p
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
• PNrrERN's score includes criminal history measures that did not require conviction and thereby may overestimate risk because of faulty data; • PNITERN's score may be higher based on evidence of juvenile offending • PATTERN may increase risk when the individual does not engage in various types of p
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
• PNrrERN's score includes criminal history measures that did not require conviction and thereby may overestimate risk because of faulty data; • PNITERN's score may be higher based on evidence of juvenile offending • PATTERN may increase risk when the individual does not engage in various types of p
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