Comparative probability for conditional events: A new look through coherence

We study, from the standpoint of coherence, comparative probabilities on an arbitrary familyE of conditional events. Given a binary relation ·, coherence conditions on · are related to de Finetti's coherent betting system: we consider their connections to the usual properties of comparative probability and to the possibility of numerical representations of ·. In this context, the numerical reference frame is that of de Finetti's coherent subjective conditional probability, which is not introduced (as in Kolmogoroff's approach) through a ratio between probability measures.Another relevant feature of our approach is that the family & need not have any particular algebraic structure, so that the ordering can be initially given for a few conditional events of interest and then possibly extended by a step-by-step procedure, preserving coherence.     

Social forecasting: An integral part of corporate planning?

The increasing need for business to monitor the social dimensions of its environment and, hopefully make some forecasts of future trends has met with some constructive response from academics and consultants although not as yet on a very liberal scale. The published literature does not indicate to what extent companies in general attemp social forecasting and, where they do, the degree of integration which exists within their corporate planning systems. The authors, therefore, decided to survey a sample of British organizations to see if they could shed some light on these issues and thereby add some information to the excellent accounts of individual cases of social forecasting in, they suspect, the more advanced and atypical companies. The survey suggests a general picture of: awareness of the value of social forecasting; fairly widespread ignorance of the techniques which do exist, primitive though these may largely be; successful integration of social forecasting into the corporate planning systems of a substantial number of organizations but not in the majority.     

Assessment of Composite Indicators Using the ANOVA Model Combined with Multivariate Methods

The synthesis of a number of single observed indicators into a unique composite indicator involves various subjective choices related, for instance, to the type of combination (linear, non-linear) and to the aggregation method (simple average, geometric average) used in its construction. Thus, it is clearly important to analyse the variability of a composite indicator according to all possible alternatives before employing it in any decision-making process. Within such a framework, in this paper, we present a new approach based on a combination of explorative and confirmative analyses aiming to investigate the impact of different subjective choices on the variability of composite indicators. This new approach also allows the analysis of the related individual differences among the statistical units and the use of external information on the same units to enhance the interpretation of the final results.     

Caregivers' perspectives on the SafeCare® programme: Implementing an evidence‐based intervention for child neglect

This qualitative study examined caregivers' experiences with SafeCare®, an evidence‐based programme that focuses on child neglect through modules on health, safety, and parenting. Shortly after completing SafeCare, 30 caregivers participated in a semi‐structured interview about their experiences with the programme. Overall, caregivers indicated that the programme helped with improvements in their parenting skills. Among the factors that contributed to a positive experience were the simplicity of language, the skills‐based approach, and the quality of the relationship with the SafeCare provider. Caregivers also noted several factors that made it difficult to fully benefit from the programme, including financial constraints, removal of their child from the home, and general distrust towards the child welfare system. Findings provide relevant information for SafeCare providers in terms of identifying areas that work well for caregivers completing the programme, as well as areas that might serve as impediments. Implications for contemporary child welfare practice are also considered.     

Prevention training of paraprofessionals in the schools: an examination of relevancy and effectiveness

Prevention training programs for paraprofessional school personnel are examined in this article. Prevention training for the reduction of student alcohol and other drug use, incorporating a student well-being model, is described and evaluated. The prevention training, entitled "Enhancing Student Well-Being," took place in two urban school districts with over 200 paraprofessional school personnel participating. The training was evaluated using measures of knowledge gained, self-efficacy, and participant satisfaction. Pre- and post-training differences showed consistent gains in participant efficacy expectations but less consistent gains in outcome expectations and knowledge. Participant satisfaction and self-reports of knowledge enhanced and skill improvement were uniformly high across all training programs. Implications for inservice prevention training of paraprofessionals are discussed.     

Nonconglomerative coherent conditional probabilities in statistical inference

Noteworthy connections among conglomerability, countable additivity and coherence are discussed in detail, reaching the conclusion that nonconglomerable conditional probabilities must not be doomed and play a significant role in statistical inference. Extended and updated version of a contributed paper presented at the International Conference on “Information Processing and Management of Uncertainty in knowledge-based systems”, IPMU 2004, Perugia, Italy.     

An individual treatment programme for sexually abused adult males: description and preliminary findings

Growing recognition of male sexual abuse and its potentially debilitating effects has underscored the need to develop effective treatment interventions for this population. The present study describes an individual treatment programme that was developed for adult males who have experienced childhood sexual abuse. The treatment programme focused on three areas related to sexual abuse, specifically feelings of self‐blame, anger and anxiety. The study also presents preliminary findings on treatment effects, using self‐report measures that five participants completed prior to treatment and at various assessments following treatment termination. Overall findings indicated improvements in behavioural self‐blame, anger, state anxiety and trait anxiety. Treatment did not appear to have an effect on characterological self‐blame over the long term. The study's findings are limited by the reliance on self‐report data and the absence of a comparison group. As such, our findings should be viewed as an initial contribution to the currently limited empirical data on treatment effects for sexually abused adult males. Copyright © 2005 John Wiley & Sons, Ltd.     

Do bootstrap confidence procedures behave well uniformly in P?

An important statistical problem is to construct a confidence set for some functional T(P) of some unknown probability distribution P. Typically, this involves approximating the sampling distribution J_n(P) of some pivot based on a sample of size n from P. A bootstrap procedure is to estimate J_n(P) by J_n(&Pcirc;_n), where P?_n is the empirical measure based on a sample of size n from P. Typically, one has that J_n(P) and J_n(P?_n) are close in an appropriate sense. Two questions are addressed in this note. Are J_n(P) and J_n(P?_n) uniformly close as P varies as well? If so, do confidence statements about T(P) possess a corresponding uniformity property? In the case T(P) = P, the answer to the first questions is yes; the answer to the second is no. However, bootstrap confidence statements about T(P) can be made uniform over a restricted, though large, class of P. Similar results apply to other functional T(P).     

Socio-political forecasting and management information systems

This paper is an attempt to place the forecasting of socio-political variables in the context of actual information needs of industrial companies. Initially discussion is of the effect of socio-political variables upon companies with a review of this significance for decision makers and decision takers. An attempt is then made to categorise existing forecasting techniques in the context of socio-political data whilst regard is paid to the possible effects of socio-political variables on companies. Discussion is then broadened to a consideration of current practice both in the UK and in the USA. Problems implicit in current practice are commented upon and the paper ends with the conclusion that socio-political forecasting is currently significant to many companies and that there is a major potential role for management scientists to play in the development and implementation of appropriate techniques.     

Can the Augmented Solow Model with Migration Explain the Italian Internal Brain Drain?

We extend the Dolado et al. (1994) model to both inflows and outflows of migrants and assume that they have a human capital endowment that contributes to increase/decrease the stock of human capital in the receiving/sending economy. We derive the conditional convergence equation in which the impact of migration flows on the growth rate is disentangled in a pure quantity effect and in a quality or composition effect of immigration and emigration rates that accounts for the relative human capital endowment of migrants with respect to resident population. Next, we test the model with Italian regional data for the 1970–2005 time period. We find that the model provides a good explanation of the Italian experience. The quantity effect is negative for the immigration rate and positive for the emigration rate, whereas the composition effect is positive for immigration and negative for emigration. Finally, we separate the centre‐north from the south and find that the composition effect of emigration is stronger for the latter. We interpret these results as a clear evidence of a brain drain from the Mezzogiorno to the centre‐northern regions.