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3. Analysis of the Seriousness of Criminal Activity In this section we shall analyze the seriousness of criminal activity during a follow-up period after release from prison. Specifically, the dependent vari­ able is a measure of the most serious crime 2 for which the individual is con­ victed during the follow-up period. 3 This dependent variable is qualitative and has three possible values (NONE, MIS, FEL). 4. 6, but in this case the logit model is probably easier to interpret and explain. The reason is that, in the ordered probit model, the estimated coefficients would give the effects of the explanatory variables on the underlying unobservable (presumably, "seriousness") and would be hard to interpret, because seriousness has no obvious cardinal measure.

These results can be summarized by noting that an individual is most likely to have no conviction during his follow-up period if he is comparatively old at release, is nonwhite, is not an alcoholic or drug addict, has had few previous convictions, and has had a short follow-up period. Conversely, the type of individual most likely to have been convicted during his follow-up period is a young, white alcoholic (or drug addict) with many previous con­ victions and a long follow-up period. None of these individual charac­ teristics appears to affect the seriousness of the conviction (misdemeanor versus felony) if convicted.

Second, the criminal records are unusually complete. They were obtained by contacting officials in all areas where there was any indication that an individual lived after release or where 28 3. Logit Analysis of Criminal Activity self-report, FBI check, or the records of the North Carolina Department of Correction indicated that an individual had contact with criminal justice authorities. Finally, it should be emphasized that this data set is essentially a random sample of all releasees. Unlike many other data sets, it is not limited to individuals on parole.

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