Who participates? Socioeconomic Factors Associated with Women's Participation in Voluntary Groups

Participation in voluntary groups is potentially an important way to create health promoting social capital. This paper investigates women's participation in voluntary groups, utilising data from a postal survey of 968 female respondents and in‐depth interviews with 30 women. Logistic regression was conducted to examine factors associated with frequency of women's group involvement. Not working full time, living in a married relationship, and having a university education were all significantly associated with regular involvement. The qualitative data further illustrated some of the ways in which these three factors were linked with women's involvement in groups. We conclude that women who were able to regularly participate were those who already enjoyed levels of social and economic privilege. Policies to promote social capital via participation might focus on identifying what types of group involvement benefit women's health, and increasing the accessibility of such groups to include diverse groups of women.     

Creating egalitarian families among the adult children of Turkish- and Polish-origin immigrants in Sweden

This article analyzes the factors shaping egalitarian family relationships among those with two Swedish‐born parents and those with at least one parent born in Poland or Turkey. We ask: (1) What factors affect sharing domestic tasks and do they also shape the division of child care responsibilities? (2) Do these effects differ, depending on the extent of exposure to Swedish life? We analyze data from a longitudinal survey conducted between 1999 and 2003. Holding egalitarian work–family attitudes affects actual sharing of housework, but much more for those growing up in more socially integrated than in less integrated families.     

Utilization of administrative files in health research

Many authors have suggested that administrative health data files could provide the solution to the well-known research problem of obtaining data about volunteer subjects. However, many authors have failed to achieve satisfactory results because the use of these data files leads to special difficulties. Thus, unless the proper methodology is applied, use of health data files does not produce valuable results. In this paper we propose a conceptual framework which can be used to examine the suitability of health data files. More specifically, five aspects are discussed: (1) research team knowledge and skills; (2) identification and documentation of an accessible file; (3) file adequacy to answer the research question; (4) data quality; and (5) data processing. This conceptual framework should help health policy planners and researchers to better identify the problems they will meet and to find adequate solutions to these problems before embarking on the venture of using public data files.     

Investing in children’s education: are Muslim immigrants different?

Using a unique data set on immigrants living in France in 2003, we investigate whether Muslims invest differently in their children’s education compared to non-Muslims. In particular, we want to assess whether educational inequalities between the children of Muslim and non-Muslim immigrants stem from differences between or within families. After controlling for a broad set of individual and household characteristics, we find no difference in education between children of different religions. However, we do find more within-family inequality in children’s educational achievements among Muslims relative to non-Muslims. The within-family variance is 15 % higher among Muslims relative to Catholics and 45 % higher relative to immigrants with other religions, but the intra-family inequality remains difficult to explain. Overall, our results suggest that Muslim parents tend to redistribute their resources more unequally among their children.     

Digital Games as a Context for Children's Cognitive Development: Research Recommendations and Policy Considerations

We document the need to examine digital game play and app use as a context for cognitive development, particularly during middle childhood. We highlight this developmental period as 6- through 12-year olds comprise a large swath of the preadult population that plays and uses these media forms. Surprisingly, this age range remains understudied with regard to the impact of their interactive media use as compared to young children and adolescents. This gap in knowledge about middle childhood may reflect strong and widely held concerns about the effects of digital games and apps before and after this period. These concerns include concurrent and subsequent influences of game use on very young children's and adolescents’ cognitive and socioemotional functioning. We highlight here what is currently known about the impact of media on young children and adolescents and what is not known about this impact in middle childhood. We then offer recommendations for the types of research that developmental scientists can undertake to examine the efficacy of digital games within the rapidly changing media ecology in which children live. We conclude with a discussion of media policies that we believe can help children benefit from their media use. Our hope is that this review will foster greater investigation of the cognitive socialization, as raised over 20 years ago by developmental psychologist and early games researcher Patricia Greenfield, that digital games serve during the middle childhood period, and childhood more generally.     

Optimal SIR algorithm vs. fully adapted auxiliary particle filter: a non asymptotic analysis

Particle filters (PF) and auxiliary particle filters (APF) are widely used sequential Monte Carlo (SMC) techniques. In this paper we comparatively analyse, from a non asymptotic point of view, the Sampling Importance Resampling (SIR) PF with optimal conditional importance distribution (CID) and the fully adapted APF (FA). We compute the (finite samples) conditional second order moments of Monte Carlo (MC) estimators of a moment of interest of the filtering pdf, and analyse under which circumstances the FA-based estimator outperforms (or not) the optimal Sequential Importance Sampling (SIS)-based one. Our analysis is local, in the sense that we compare the estimators produced by one time step of the different SMC algorithms, starting from a common set of weighted points. This analysis enables us to propose a hybrid SIS/FA algorithm which automatically switches at each time step from one loop to the other. We finally validate our results via computer simulations.     

The Access/Impact Problem and the Green and Gold Roads to Open Access

Abstract

The research access/impact problem arises because journal articles are not accessible to all of their would-be users; hence, they are losing potential research impact. The solution is to make all articles Open Access (OA; i.e., accessible online, free for all). OA articles have significantly higher citation impact than non-OA articles. There are two roads to OA: the “golden” road (publish your article in an OA journal) and the “green” road (publish your article in a non-OA journal but also self-archive it in an OA archive). Only 5% of journals are gold, but over 90% are already green (i.e., they have given their authors the green light to self-archive); yet only about 10–20% of articles have been self-archived. To reach 100% OA, self-archiving needs to be mandated by researchers' employers and funders, as the United Kingdom and the United States have recently recommended, and universities need to implement that mandate.