The Juvenile Justice Assessment Instrument

Abstract This article presents the development of a new assessment instrument for use with juvenile delinquents: The Juvenile Justice Assessment Instrument (JJAI). The term “juvenile delinquency” covers a multitude of antisocial behaviors engaged in by adolescents. Research indicates that certain intrinsic vulnerabilities may combine with environmental stressors to engender maladaptive behaviors. Unfortunately, these potentially treatable vulnerabilities often remain unrecognized in the delinquent population. Because of the sheer numbers of children entering the juvenile justice system each year, it is impossible to ensure that each child will receive a full evaluation from a trained clinician. The JJAI offers those who work with juvenile delinquents an economical, yet sophisticated, assessment tool for evaluating youngsters and recommending appropriate treatment and disposition. This paper also presents the results of two field trials with the JJAI. In a juvenile justice setting, data elicited by the JJAI was compared to data gathered by the court. In a residential treatment setting, data elicited by the JJAI was compared with information gathered by staff at the treatment facility. A discussion of the obstacles faced by those who interview delinquents, and strategies within the JJAI to overcome them, are discussed.     

Reflections on Budget Systems

Several prominent budget systems of past years, such as the Planning Programming Budget System and Zero-Base Budgeting, are no longer popular as comprehensive systems, each system has had a continuing effect on current practices. This article comments on the usefulness of several features of budget systems particularly from a management perspective. It also offers several criteria for design of budget systems which, it is hoped, would help prevent some of the problems that have been encountered in the past.     

Conditioned Microplitis croceipes Cresson (Hymenoptera: Braconidae) detect and respond to 2,4-DNT: development of a biological sensor

We examined the ability of M. croceipes to learn, detect, and respond to 2,4-DNT, which is a volatile discriminator of trinitrotoluene (TNT). The percentage of conditioned wasps to detect and respond to the various concentrations of 2,4-DNT for > or = 15 sec was measured. Significantly more of the conditioned wasps responded to the concentration of 2,4-DNT used for conditioning than other concentrations examined. Accordingly, percent conditioned wasps to respond > or = 15 sec could be used as a suitable measure to screen air samples and distinguish between samples with or without the target odorant. The data recorded in this study indicate the measured behavior could be used to estimate the concentration of target odorants. Data in this study indicate M. croceipes can detect and respond to this compound, which provide further support for its development as a biological sensor.     

Assessing Violence Risk in Stalking Cases: A Regression Tree Approach

Advances in the field of risk assessment have highlighted the importance of developing and validating models for problematic or unique subgroups of individuals. Stalking offenders represent one such subgroup, where fears of and potential for violence are well-known and have important implications for safety management. The present study applies a Classification and Regression Tree (CART) approach to a sample of stalking offenders in order to help further the process of identifying and understanding risk assessment strategies. Data from 204 stalking offenders referred for psychiatric evaluation to a publicly-funded clinic were used to develop and assess putative risk factors. A series of nested models were used to generate tree algorithms predicting violence in this sample of offenders. Both simplified and more extensive models generated high levels of predictive accuracy that were roughly comparable to logistic regression models but much more straightforward to apply in clinical practice. Jack-knifed cross-validation analyses demonstrated considerable shrinkage in the CART, although the models were still comparable to many other actuarial risk assessment instruments. Logistic regression models were much more resilient to cross-validation, with relatively modest loss in predictive power.     

A Test of Two Methods of Recall for Violent Events

This project took advantage of an opportunity to test the comparability of two different methods for collecting self-reports of violent incidents. Using a life events calendar (LEC) approach, we collected data from individuals about violent incidents that occurred within a 1–3-year prior time period. These individuals had been research participants in a previous study that collected information about violent incidents using prospective, weekly interviews. Results using the LEC method were compared with the weekly self-reports of violence for an overlapping recall period. This allowed us to see how well the recall of violent incidents at a later date mapped onto reports obtained within seven days of any incidents. Overall results show a significant amount of under-reporting using the life-event calendar methodology compared to the weekly interview approach, but some higher concordance of reporting was found for serious rather than minor violence.     

Estimating Regression Models in Which the Dependent Variable Is Based on Estimates

e-mail: jblewis{at}ucla.edu (corresponding author) e-mail: dlinzer{at}ucla.edu Researchers often use as dependent variables quantities estimatedfrom auxiliary data sets. Estimated dependent variable (EDV)models arise, for example, in studies where counties or statesare the units of analysis and the dependent variable is an estimatedmean, proportion, or regression coefficient. Scholars fittingEDV models have generally recognized that variation in the samplingvariance of the observations on the dependent variable willinduce heteroscedasticity. We show that the most common approachto this problem, weighted least squares, will usually lead toinefficient estimates and underestimated standard errors. Inmany cases, OLS with White's or Efron heteroscedastic consistentstandard errors yields better results. We also suggest two simplealternative FGLS approaches that are more efficient and yieldconsistent standard error estimates. Finally, we apply the variousalternative estimators to a replication of Cohen's (2004) cross-nationalstudy of presidential approval.