140 resultados para Socio-educative measure


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Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.

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(Résumé de l'ouvrage) Au travers d'une analyse socio-historique du rabbinat français, d'une enquête sur Sarcelles et d'un examen du mouvement néo-orthodoxe des Loubavitch, l'auteur brosse un tableau vivant du judaïsme contemporain et des modifications qui le traversent. Laurence Podselver apporte du même coup un éclairage sur les recompositions que connaît l'ensemble du champ religieux aujourd'hui: une affirmation de formes identitaires plus marquées venant se greffer sur l'axe de la sécularisation, de ses adaptations libérales et de ses reconstructions culturelles laïques

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Questionnaires are used in the majority of the studies ondoping prevalence in sport. Nevertheless, prevalence is noteasy to evaluate and previous epidemiologic studies demonstrateda wide variance. This variance has mostly beenexplained by sample differences. The way to evaluate dopingprevalence in the survey is questioned in this paper. Aquestionnaire was administered to 1810 amateur athletes(993 males, 817 females). Doping use was ascertained invarious ways, using different definitions of doping and typesof question in the survey. Depending on the definition ofdoping and the type of question used, the prevalence ofdoping obtained can differ enormously, between 1.3 and39.2% of athletes. Marijuana and drugs for asthma were thetwo banned substances most used. The majority of athletesoften ignored the banned list and did not use prohibitedsubstances to dope. Using various ways to question athletes,observing the usage of substances, cross checking the data,taking into account the aim of substances uses and thevarious definitions of doping are necessary to give morereliable prevalence of doping. Moreover, doping at anamateur level seems to be less of a sport problem than asocial problem.

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Overall it seems that age and gender interviewer characteristics are relevant in achieving higher cooperation rates by telephone panel members. This appears to be the case especially for older male interviewers, who perform the best on gaining cooperation across different types of respondents. This holds if important interviewer covariates like experience are controlled for. There is no evidence that special sex age or sex matches yield a higher cooperation. It may be that not only the perceived authority of the institution that sponsors the survey plays a role when it comes to cooperation (Groves et al., 1992) but also of the interviewer who asks for this cooperation. Presumably older men have more authority to convince sample members to participate. A simple recommendation is to use as many older male interviewers as possible for the recruitment phase. It is likely that this strategy would also be successful in other western cultures than Switzerland.