The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk
The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk
The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk
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independence <str<strong>on</strong>g>of</str<strong>on</strong>g> data (i.e., the model parameters were not derived from the same sample<br />
for which predicti<strong>on</strong>s would then be made).<br />
This helps to determine whether the<br />
relati<strong>on</strong>ships found in the initial sample are generalizable to other members <str<strong>on</strong>g>of</str<strong>on</strong>g> the same<br />
populati<strong>on</strong>. Once the model has been specified, it may then be used to derive risk<br />
predicti<strong>on</strong>s for probati<strong>on</strong>ers in current caseloads.<br />
<str<strong>on</strong>g>The</str<strong>on</strong>g> model assigns each probati<strong>on</strong> case (not each <str<strong>on</strong>g>of</str<strong>on</strong>g>fender) a ‘reliability score’ to<br />
indicate its risk level. <str<strong>on</strong>g>The</str<strong>on</strong>g> reliability score is a value between 0 and 1. <str<strong>on</strong>g>The</str<strong>on</strong>g> selected<br />
threshold for low-risk cases was 0.5, so that cases with a reliability score greater than 0.5<br />
were designated as low risk and scores equal to or less than 0.5 were not low risk. A<br />
specific <str<strong>on</strong>g>of</str<strong>on</strong>g>fender’s risk score is based <strong>on</strong> the average reliability score across all his or her<br />
active probati<strong>on</strong> cases. However, even if the average reliability score exceeded 0.5, an<br />
<str<strong>on</strong>g>of</str<strong>on</strong>g>fender could not be designated low risk if any <strong>on</strong>e <str<strong>on</strong>g>of</str<strong>on</strong>g> his or her active cases scored 0.5<br />
or below.<br />
<str<strong>on</strong>g>The</str<strong>on</strong>g> Philadelphia model meets many <str<strong>on</strong>g>of</str<strong>on</strong>g> the recommendati<strong>on</strong>s set out by B<strong>on</strong>ta<br />
(2002) and Gottfreds<strong>on</strong> and Moriarty (2006) for optimal risk predicti<strong>on</strong>. B<strong>on</strong>ta suggests<br />
that risk assessments require predictive validity, direct relevance to criminal behavior and<br />
the correcti<strong>on</strong>al setting, and should adhere to the principle <str<strong>on</strong>g>of</str<strong>on</strong>g> the least restrictive<br />
alternative. <str<strong>on</strong>g>The</str<strong>on</strong>g> Philadelphia model is validated by its development <strong>on</strong> a training sample<br />
<str<strong>on</strong>g>of</str<strong>on</strong>g> cases for which outcomes were already known and its applicati<strong>on</strong> to other members <str<strong>on</strong>g>of</str<strong>on</strong>g><br />
the same populati<strong>on</strong>. <str<strong>on</strong>g>The</str<strong>on</strong>g> present paper attempts to further validate its ability to predict<br />
who will be low risk. <str<strong>on</strong>g>The</str<strong>on</strong>g> model’s focus <strong>on</strong> serious <str<strong>on</strong>g>of</str<strong>on</strong>g>fending is directly relevant to<br />
correcti<strong>on</strong>al priorities. Finally, the express purpose <str<strong>on</strong>g>of</str<strong>on</strong>g> the model is to ensure that the<br />
most intensive supervisi<strong>on</strong> and treatment is <strong>on</strong>ly reserved for those who need it most.<br />
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