Longitudinal Analysis of a Very Short Measure of Positive Youth Development

As developmental scientists cease to perceive adolescence as a period of inevitable turmoil and adopt the Positive Youth Development (PYD) perspective, psychometrically sound measurement tools will be needed to assess adolescents’ positive attributes. In this article we examine the longitudinal stability of the very short version of the PYD scale developed as part of the 4-H Study of PYD. Using a sample of 7,071 adolescents (60 % female) followed between Grades 5 and 12, our results suggest general stability of PYD across adolescence, both in terms of mean levels and rank-order stability. We also show that both a global measure of PYD and the individual Five Cs of PYD consistently correlate with important criterion measures (i.e., contribution, depressive symptoms, and problem behaviors) in expected ways. Although our results suggest weak relationships among our three criteria, we especially note that across adolescence PYD becomes more strongly correlated with contribution but less strongly correlated with depressive symptoms, and that confidence becomes more strongly related to depressive symptoms. We discuss implications for use of the present PYD measure in youth development programs.     

Measuring the Geographical Displacement and Diffusion of Benefit Effects of Crime Prevention Activity

The displacement of crime is an important criminological phenomenon. However, while there has been theoretical discussion of this issue in the research literature, there has been little in the way of either standardized empirical work that investigates the incidence of displacement or in the development of techniques that can be used to measure it. In the current paper we discuss a new technique, the weighted displacement quotient (WDQ), that was developed to measure the geographical displacement of crime. A critical feature of the rationale is that displacement can only be attributed to crime prevention activity if crime is reduced in the target area considered. Thus, the WDQ not only measures what occurs in a buffer (displacement) zone but also relates changes in this area to those in the target area. Part of the appeal of the measure is that it can be used either with aggregate or disaggregate crime data and for any geographical boundary selected, provided the appropriate data are available. In addition to detecting displacement, when detailed data are available, the technique can also be used to identify where the effect was most prominent. The WDQ can equally be used to measure the diffusion of benefit of any crime prevention activity. A series of examples are presented for illustration purposes.     

A neglected and intelligent alternative to arbitration is finally coming of age

Although not a substitute for arbitration, grievance mediation can be an effective, readily available and inexpensive means of resolving some disputes. Educator/arbitrator Bowers also sees it as an unjustly neglected preventive measure and seeks here to remedy that neglect by examining mediation's role in labor relations.     

Predictive Crime Mapping: Arbitrary Grids or Street Networks?

Objectives

Decades of empirical research demonstrate that crime is concentrated at a range of spatial scales, including street segments. Further, the degree of clustering at particular geographic units remains noticeably stable and consistent; a finding that Weisburd (Criminology 53:133–157, 2015) has recently termed the ‘law of crime concentration at places’. Such findings suggest that the future locations of crime should—to some extent at least—be predictable. To date, methods of forecasting where crime is most likely to next occur have focused either on area-level or grid-based predictions. No studies of which we are aware have developed and tested the accuracy of methods for predicting the future risk of crime at the street segment level. This is surprising given that it is at this level of place that many crimes are committed and policing resources are deployed.

Methods

Using data for property crimes for a large UK metropolitan police force area, we introduce and calibrate a network-based version of prospective crime mapping [e.g. Bowers et al. (Br J Criminol 44:641–658, 2004)], and compare its performance against grid-based alternatives. We also examine how measures of predictive accuracy can be translated to the network context, and show how differences in performance between the two cases can be quantified and tested.

Results

Findings demonstrate that the calibrated network-based model substantially outperforms a grid-based alternative in terms of predictive accuracy, with, for example, approximately 20 % more crime identified at a coverage level of 5 %. The improvement in accuracy is highly statistically significant at all coverage levels tested (from 1 to 10 %).

Conclusions

This study suggests that, for property crime at least, network-based methods of crime forecasting are likely to outperform grid-based alternatives, and hence should be used in operational policing. More sophisticated variations of the model tested are possible and should be developed and tested in future research.

     

Permeability and Burglary Risk: Are Cul-de-Sacs Safer?

That crime is concentrated in space is now accepted as commonplace. Explanations for why it clusters at particular locations are various reflecting the range of factors which are held to influence crime placement. In this article, we focus on the role of the permeability of the street network on the location of crime. We first review the research conducted hitherto, summarising the different approaches to analysis and the findings that have so far emerged. Then we present original analyses conducted at the street segment level to examine the issues at hand. In contrast to much of the prior research, in this study we examine the patterns for a large study area in which there is considerable variation in street network configuration. Moreover, and in contrast to all of the previous research, the approach to analysis takes into account the multi-level structure of the data analysed. The findings demonstrate that increased permeability is associated with elevated burglary risk, that burglary risk is lower on cul-de-sacs (particularly those that are sinuous in nature), and that the risk of burglary is higher on more major roads and those street segments that are connected to them. In the conclusion of the paper we outline an agenda for future research.