Assessing reoffense risk with juvenile sexual offenders

This article summarizes a two-year study of juvenile sexual offenders in Washington. Both community-based and institution-based treatment programs were evaluated. A typical profile of the juvenile sexual offender is offered, as well as recidivism data from a mean 20-month follow-up period.     

Characteristics of a central change programme within a governmental bureaucracy: a grounded theory study

Purpose The purpose of the paper is to present a theory of organisational change within the setting of a governmental bureaucracy. Design/methodology/approach Orthodox grounded theory is employed in the setting of a change programme in 12 Audit departments of the Dutch Ministries (public-sector). Findings The examined organisational change has specific characteristics. The Dutch ‘ministerial autonomy’ and the clearly recognizable role types of the key figures involved have a strong impact on the change programme and the realisation of its goals. Research limitations/implications Findings are derived on the basis of a substantive case study of the change programme of the Dutch Departmental Audit function. The research sheds new light on characteristics related to the occupational group of Chartered Accountants and characteristics of a governmental bureaucracy and it helps to understand change programmes within this bureaucracy. Practical implications The grounded theoretical model draws attention to the impact of key figures and circumstances on a change programme within the central government. Originality/value The paper builds on theories of organisational change but applies them in the typical context of the Dutch civil service where ministerial autonomy, on the one hand, and a move in the direction of more centrally organised activities (concern idea), on the other, require a difficult balancing act of all players in the change arena.     

Semiparametric sieve maximum likelihood estimation under cure model with partly interval censored and left truncated data for application to spontaneous abortion

Lifetime Data Analysis - This work was motivated by observational studies in pregnancy with spontaneous abortion (SAB) as outcome. Clearly some women experience the SAB event but the rest do not....     

“Why I Can't Stand Out in Front of My House?”: Street‐Identified Black Youth and Young Adult's Negative Encounters With Police

This street participatory action research (Street PAR) study organized 15 residents to document street‐identified Black youth and adult's negative experiences with police in Wilmington, Delaware. Data were collected on mostly street‐identified Black men and women aged 18–35 in the forms of (1) 520 surveys, (2) 24 individual interviews, (3) four dual interviews, (4) three group interviews, and (5) extensive field observations. Forty‐two percent of survey participants reported being stopped by police in the last year. However, with the exception of being “stopped,” participants overall reported little negative contact with police at least within the past year. Chi‐square and ANOVA analyses suggest an interactional relationship exists between race, gender, and age on experiences with police. Younger Black men (18–21) were found to have the most negative contact with police. Analysis suggests a smaller, more hardened mostly male variant of the larger street community has had repeated contact with police. Qualitative analysis reveals at least two major themes: (1) disrespect and disdain for residents and (2) low motivation for working with police. Street PAR methodology was also found to be instrumental in working with local residents and the Wilmington Police Department to improve conditions between residents and police.     

Money-metric utilitarianism

We discuss a method of ranking allocations in economic environments which applies when we do not know the names or preferences of individual agents. We require that two allocations can be ranked with the knowledge only of agents present, their aggregate bundles, and community indifference sets—a condition we refer to as aggregate independence. We also postulate a basic Pareto and continuity property, and a property stating that when two disjoint economies and allocations are put together, the ranking in the large economy should be consistent with the rankings in the two smaller economies (reinforcement). We show that a ranking method satisfies these axioms if and only if there is a probability measure over the strictly positive prices for which the rule ranks allocations on the basis of the random-price money-metric utilitarian rule. This is a rule which computes the money-metric utility for each agent at each price, sums these, and then takes an expectation according to the probability measure.     

A methodological strategy for a one-number census in the UK

As a result of lessons learnt from the 1991 census, a research programme was set up to seek improvements in census methodology. Underenumeration has been placed top of the agenda in this programme, and every effort is being made to achieve as high a coverage as possible in the 2001 census. In recognition, however, that 100% coverage will never be achieved, the one-number census (ONC) project was established to measure the degree of underenumeration in the 2001 census and, if possible, to adjust fully the outputs from the census for that undercount. A key component of this adjustment process is a census coverage survey (CCS). This paper presents an overview of the ONC project, focusing on the design and analysis methodology for the CCS. It also presents results that allow the reader to evaluate the robustness of this methodology.     

ROBUST ESTIMATION OF SMALL‐AREA MEANS AND QUANTILES

Small‐area estimation techniques have typically relied on plug‐in estimation based on models containing random area effects. More recently, regression M‐quantiles have been suggested for this purpose, thus avoiding conventional Gaussian assumptions, as well as problems associated with the specification of random effects. However, the plug‐in M‐quantile estimator for the small‐area mean can be shown to be the expected value of this mean with respect to a generally biased estimator of the small‐area cumulative distribution function of the characteristic of interest. To correct this problem, we propose a general framework for robust small‐area estimation, based on representing a small‐area estimator as a functional of a predictor of this small‐area cumulative distribution function. Key advantages of this framework are that it naturally leads to integrated estimation of small‐area means and quantiles and is not restricted to M‐quantile models. We also discuss mean squared error estimation for the resulting estimators, and demonstrate the advantages of our approach through model‐based and design‐based simulations, with the latter using economic data collected in an Australian farm survey.     

The impact of involuntary job loss on those disabled by society: a pilot study to encourage effective participation

Over half of the people who become disabled whilst employed are thought to be pressured into leaving their job. This study investigates the experience of involuntary retirement/redundancy due to disability. Three researchers who had all experienced such involuntary job loss were trained to conduct the research. Semi-structured interviews were designed and conducted by disabled researchers. The training of the researchers enabled them to successfully conduct a research project. The results of the project show the impact of involuntary job loss due to disability to be considerable. This study would suggest that government reforms to create new opportunities for disabled people of a working age are well overdue. Although there were some problems experienced with the amount of training required and the lack of objectivity, training disabled researchers to conduct research proved to be a valuable experience for both the researchers and the facilitators.     

ESTIMATING DISTRIBUTION FUNCTIONS FROM SURVEY DATA WITH LIMITED BENCHMARK INFORMATION

The model-based approach to estimation of finite population distribution functions introduced in Chambers & Dunstan (1986) is extended to the case where only summary information is available for the auxiliary size variable. Monte Carlo results indicate that this ‘limited information’ extension is almost as efficient as the ‘full information’ method proposed in the above reference. These results also indicate that the model-based confidence intervals generated by either of these methods have superior coverage properties to more conventional design-based confidence intervals.