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Abstract
Matsuda et al. (2022) show that late bloomers also exist in self-report data. They use a "dynamic" definition of late bloomer offending pattern as they have concerns with definitions based on arbitrary age cutoff points. But the approach does not make the groups less arbitrary than hard definitions. In this commentary, I argue that a hard definition has important advantages and demonstrates an alternative using a hard definition while exploring heterogeneity within the late onset group.

Group‐based methodology (SPGM) has been presented as suitable to test for the existence of subpopulations not directly observable. Several criminological studies have used this methodology, and it is fair to say that typological theorizing has been spurred by its development. In particular, much of the empirical support for Moffitt's taxonomy (1993, 2006) is from studies using SPGM. In a small simulation experiment, I investigate whether SPGM is suitable for such tests, and I examine the extent to which similar trajectories might equally well result from mechanisms suggested by general theories. I conclude that, as it is usually applied, SPGM cannot provide evidence either for or against a taxonomy and that the usual findings can be explained by competing theories. I argue that this result is not only because of the methodology characteristics but also because of the modeling strategy applied.

Does employment promote desistance from crime? Most perspectives assume that individuals who become employed are less likely to offend than those who do not. The critical issue has to do with the timing of employment transitions in the criminal trajectory. The turning point hypothesis expects reductions in offending after job entries, whereas the maturation perspective assumes desistance to have occurred ahead of successful transitions to legitimate work. Focusing on a sample of recidivist males who became employed during 2001–2006 (N = 783), smoothing spline regression techniques were used to model changes in criminal offending around the point of entry to stable employment. Consistent with the maturation perspective, the results showed that most offenders had desisted prior to the employment transition and that becoming employed was not associated with further reductions in criminal behavior. Consistent with the turning point hypothesis, we identified a subset of offenders who became employed during an active phase of the criminal career and experienced substantial reductions in criminal offending thereafter. However, this trajectory describes less than 2 percent of the sample. The patterns observed in this research suggest that transition to employment is best viewed as a consequence rather than as a cause of criminal desistance.

AbstractOslo, the capital of Norway, is situated in a North European cool climate zone. We investigate the effect of weather on the overall level of crime in the city, as well as the impact of different aspects of weather (temperature, wind speed, precipitation) on the spatial distribution of crime, net of both total level of crime, time of day and seasonality. Geocoded locations of criminal offences were combined with data on temperature, wind speed, and precipitation. Generalized Additive Models (GAMs) allowed us to map level of and the spatial distribution of crime, and how it was impacted by weather, in a more robust manner than in previous studies. There was slightly more crime in pleasurable weather (i.e. low precipitation and wind speed and high temperatures). However, neither temperature, precipitation nor wind speed impacted the spatial distribution of crime in the city.

The Static-99R has been recommended for use as a first global screen for sorting out sex-convicted persons who are in need of further risk assessment. This study investigated the Static-99R's predictive validity based on a nonselected Norwegian sample ( n = 858) of persons released from prison after having served a sex crime sentence. After a mean observation period of 2,183 days, 3.4% ( n = 29) had recidivated to a new sex offense. A higher number of recidivists were found among those with higher Static-99R total scores. The predictive contribution from each of the ten Static-99R risk items was investigated using standard logistic regression, proportional hazard regression, and random forest classification algorithm. The overall results indicate that the Static-99R is relevant as a risk screen in a Norwegian context, providing similar results concerning predictive accuracy as previous studies.