The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

<strong>of</strong> low-intensity supervision based on risk <strong>of</strong> serious <strong>of</strong>fending, because there may be
public and political anxiety about reducing criminal justice intervention to adjudicated
<strong>of</strong>fenders. Thus, for low-intensity probation to maintain credibility, it is arguably more
sensible to demonstrate that few serious <strong>of</strong>fenders slipped through the net than to show
how many non-serious <strong>of</strong>fenders had their supervision requirements reduced. From the
model standpoint, we must ensure a high positive predictive value, which indicates the
proportion <strong>of</strong> predicted low-risk <strong>of</strong>fenders who were actually low risk, and high
specificity (proportion <strong>of</strong> serious <strong>of</strong>fenders who received a non-low risk prediction).
Large values for these two measures indicate a low rate <strong>of</strong> false positives (predicted lowrisk
<strong>of</strong>fenders who commit serious crimes).
Conversely, we expect to see lower
sensitivity and lower negative predictive values, because the sample contains many false
negatives. Most non-low risk probationers do not go on to be serious <strong>of</strong>fenders in the
two-year follow-up. Serious <strong>of</strong>fenses are rare events in our sample, and non-low risk
<strong>of</strong>fenders are not necessarily high risk. 9
Low values on these two measures are more
acceptable because there is no harm when an <strong>of</strong>fense is not committed, regardless <strong>of</strong> the
risk prediction. However, we must also keep the purpose <strong>of</strong> the model in mind: the
diversion <strong>of</strong> a majority <strong>of</strong> <strong>of</strong>fenders in APPD’s caseload to low-intensity supervision. If
sensitivity is too low (too few non-serious <strong>of</strong>fenders received low-risk predictions), that
goal will not be fulfilled.
Table 3.5 shows the results <strong>of</strong> these tests using the model definition <strong>of</strong> severity.
<strong>The</strong> positive predictive values are high at all thresholds, indicating a low rate <strong>of</strong> false
positives in general. This is promising, but will be driven by the very low sample
prevalence <strong>of</strong> serious <strong>of</strong>fending post-risk assessment. <strong>The</strong> present cut-<strong>of</strong>f point <strong>of</strong> 0.5
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