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Abstract

This article analyses informal support networks in Portugal. Using data from a national survey on families with children (1999), it explores the dynamics of support, in terms of the characteristics of, and variations in, families' experience of support. The analysis underlines the importance of social factors, such as the position of families in social and educational structures, and family variables, such as position in the life course, in determining the extent of support received by families. The results show that many families have a low level of support and that extended kinship does not play a significant role in providing support. As in other European countries, assistance flows mainly from parents, from the wife's family and from women rather than men; it is also strongly related to families' position in social structure, with low educational levels and less favourable occupational categories determining lower levels of support over the course of married life. Thus welfare provision stemming from informal relationships reinforces existing social inequalities rather than compensating for them, and the idea of a strong pre- and post-modern welfare society must be challenged.

Abstract ContextExamining land cover's influences on roadkills at single predetermined scales is more common than evaluating multiple scales, but examining land cover at the appropriate scale may be necessary for efficient design of mitigation measures, and that appropriate scale may be difficult to discern a priori. In addition, the taxonomic rank at which data is analysed may influence results and subsequent conclusions concerning mitigation. AimsThe objective of the present study was to assess the influence of variation in spatial scales of land cover explanatory variables and taxonomic rank of response variables in models of wildlife–vehicle collisions (WVCs). Research questions include: (1) do the scales of land cover measurement that produce the highest quality models differ among species; (2) do the factors that influence roadkill events differ within species at different scales of measurement and among species overall; and (3) does the taxonomic rank at which data is analysed influence the selection of explanatory variables? MethodsFour frequent WVC species representing diverse taxonomic classes, i.e. two mammals (Cerdocyon thous and Hydrochaeris hydrochaeris), one reptile (Caiman yacare) and one bird (Caracara plancus), were examined. WVCs were buffered, land cover classes from classified satellite imagery at three buffer radii were extracted, and logistic regression model selection was used. Key resultsThe scale of land cover variables selected for the highest quality models (and the selected variables themselves) may vary among wild fauna. The same explanatory variables and formulae are not always included in the candidate models in all compared scales for a given species. Explanatory variables may differ among taxonomically similar species, e.g. mammals, and pooling species at higher taxonomic ranks can result in models that do not correspond with species-level models of all pooled species. ConclusionsThe most accurate analyses of WVCs will likely be found when species are analysed individually and multiple scales of predictor variable collection are evaluated. ImplicationsMitigating the effects of roadways on wildlife population declines for both common and rare species is resource intensive. Resources spent optimising models for spatially targeting management actions may reduce the amount of resources used and increase the effectiveness of these actions.

Iniciamos esta pesquisa a dez meses das eleições executivas de 2018, período no qual investigamos o comportamento coletivo de 90 grupos de WhatsApp interconectados e de apoio aos seis principais presidenciáveis, bem como os mais de 500 mil textos e imagens enviados pelos usuários, através dessa ferramenta, durante os cinco meses de campanha eleitoral. Com este estudo, identificamos que o alcance ampliado do aplicativo se dá através de sua viralização contra-intuitiva, consequência direta da interconexão estrutural desses grupos. Diante disso, confirmamos nossa hipótese sobre a importância das características e das topologias da rede para uma compreensão aprofundada sobre a desinformação em larga escala via WhatsApp. Como resultado, reconhecemos quais métricas da rede são bem sucedidas na previsão e caminhos preferenciais para a circulação da desinformação segmentada e possibilidades de rastreio de fontes originais das notícias.