Challenging From Within : Youth Associations and Female Leadership in Swedish Mosques

This chapter focuses on women members of the Sunnī-dominated national organization Sweden's Young Muslims (Sveriges Unga Muslimer, SUM) and some of its local youth associations in different Swedish towns, to argue that involvement with these associations is increasing Muslim women's engagement with mosques and other venues for acquisition of Islamic knowledge. Illuminating the continuous challenges to the women's presence in mosques and their wider public activism the chapter examines how these women defend their right to exercise religious authority while supporting the traditional sources of Muslim authority in the public sphere. It analyzes how the women reinterpret the Islamic texts to change their daily lives as well as their position within both the Muslim community and Swedish society as a whole. The chapter emphasizes that in more informal situations, backstage among peers, the women put gender on the agenda, initiate reflexive deliberations, and test alternative norms and practices.

The 'voice' approach of trade associations:support for SMEs accessing a research institute

Access to external sources of technical knowledge is one of the keys to staying innovative for small and medium-sized enterprises (SMEs). The literature suggests that SMEs with a weak internal R&D capacity do not make much use of institutional sources like research institutes and universities. In this paper I investigate how trade associations can induce member SMEs to use a research institute. The case of a public research institute and SMEs in the textile industry in Kyoto, Japan is examined. Evidence from the case suggests that trade associations facilitate the use of the institute by expressing a collective `voice' to the management of the institute. The effect is evident among active members in the use of services involving a large information gap as to their benefits. I also consider a shortcoming of the collective approach and suggest some measures to be taken on the part of research institutes.

Spatially clustered associations in health GIS

Overlaying maps using a desktop GIS is often the first step of a multivariate spatial analysis. The potential of this operation has increased considerably as data sources and Web services to manipulate them are becoming widely available via the Internet. Standards from the OGC enable such geospatial mashups to be seamless and user driven, involving discovery of thematic data. The user is naturally inclined to look for spatial clusters and correlation of outcomes. Using classical cluster detection scan methods to identify multivariate associations can be problematic in this context, because of a lack of control on or knowledge about background populations. For public health and epidemiological mapping, this limiting factor can be critical but often the focus is on spatial identification of risk factors associated with health or clinical status. Spatial entropy index HSu for the ScankOO analysis of the hypothetical dataset using a vicinity which is fixed by the number of points without distinction between their labels. (The size of the labels is proportional to the inverse of the index) In this article we point out that this association itself can ensure some control on underlying populations, and develop an exploratory scan statistic framework for multivariate associations. Inference using statistical map methodologies can be used to test the clustered associations. The approach is illustrated with a hypothetical data example and an epidemiological study on community MRSA. Scenarios of potential use for online mashups are introduced but full implementation is left for further research.

Spatially clustered associations in health related geospatial data

Overlaying maps using a desktop GIS is often the first step of a multivariate spatial analysis. The potential of this operation has increased considerably as data sources an dWeb services to manipulate them are becoming widely available via the Internet. Standards from the OGC enable such geospatial ‘mashups’ to be seamless and user driven, involving discovery of thematic data. The user is naturally inclined to look for spatial clusters and ‘correlation’ of outcomes. Using classical cluster detection scan methods to identify multivariate associations can be problematic in this context, because of a lack of control on or knowledge about background populations. For public health and epidemiological mapping, this limiting factor can be critical but often the focus is on spatial identification of risk factors associated with health or clinical status. In this article we point out that this association itself can ensure some control on underlying populations, and develop an exploratory scan statistic framework for multivariate associations. Inference using statistical map methodologies can be used to test the clustered associations. The approach is illustrated with a hypothetical data example and an epidemiological study on community MRSA. Scenarios of potential use for online mashups are introduced but full implementation is left for further research.