Interkulturelle Kompetenz in der Polizei: Qualifizierungsstrategien

Increasing tension and scandal-laden conflicts with members of ethnic minorities during the 1990s make it clear, that the German police force is still not satisfactorily prepared to deal with a multi-cultural society. An immediate reaction was the engagement of training programmes, giving higher-rank officials something to present as an approach to solving the problem. This can apparently be seen as cosmetic change without effect on the structure and culture of the organisation. This work attempts to map the potential for sustainable development of intercultural competence via training programmes, based on the results of international research on police work. Four classical models of intercultural training are described, and their suitability for further education within the police analysed. Starting from the difficulties of determining the actual competency requirements specific in the field, and the basic problems of mediating and acquiring inter-cultural skills, the article concludes with a discussion of sustainable education strategies, which extend to fundamental questions of organisational development.     

Bridges between deterministic and probabilistic models for binary data

For the analysis of binary data, various deterministic models have been proposed, which are generally simpler to fit and easier to understand than probabilistic models. We claim that corresponding to any deterministic model is an implicit stochastic model in which the deterministic model fits imperfectly, with errors occurring at random. In the context of binary data, we consider a model in which the probability of error depends on the model prediction. We show how to fit this model using a stochastic modification of deterministic optimization schemes.The advantages of fitting the stochastic model explicitly (rather than implicitly, by simply fitting a deterministic model and accepting the occurrence of errors) include quantification of uncertainty in the deterministic model’s parameter estimates, better estimation of the true model error rate, and the ability to check the fit of the model nontrivially. We illustrate this with a simple theoretical example of item response data and with empirical examples from archeology and the psychology of choice.