Family comes first or open all hours?: How low paid women working in food retailing manage webs of obligation at home and work

This paper draws on qualitative findings from a study exploring work-life balance issues amongst female employees within food retailing. Whilst female employment is fundamental to this sector, there is limited evidence on employees' experiences of reconciling relatively low-paid work and the particular demands of food retailing with domestic and caring responsibilities. Managing competing discourses and demands at home and work is a feature of many women's lives. For those in low-paid jobs, with fewer material resources to fall back on, such webs of obligation, often stretching over the lifecourse, may be particularly difficult to navigate or escape. In food retail work, as in caring/domestic emergencies, timeframes may be tight and demands made on workers at short notice and outwith the standard working day. The study showed that sustaining their moral identities both as good mothers/daughters/family members ('family comes first') and as good and reliable workers ('the store must be staffed') was, therefore, an everyday practical accomplishment for these food retail employees. We explore women's accounts against the backdrop of particular familial, workplace and socio-cultural expectations and constraints, identifying overlapping sets of values between home and work as well as points of contradiction and tension.     

Exponential Family Models for sampled and census Network data

Much progress has been made on the development of statistical methods for network analysis in the past ten years, building on the general class of exponential family random graph (ERG) network models first introduced by Holland and Leinhardt (1981) . Recent examples include models for Markov graphs, "p*" models, and actor‐oriented models. For empirical application, these ERG models take a logistic form, and require the equivalent of a network census: data on all dyads within the network. In a largely separate stream of research, conditional log‐linear (CLL) models have been adapted for analyzing locally sampled ("egocentric") network data. While the general relation between log‐linear and logistic models is well known and has been exploited in the case of a priori blockmodels for networks, the relation for the CLL models is different due to the treatment of absent ties. For fully saturated tie independence models, CLL and ERG are equivalent and related via Bayes' rule. For other tie independence models, the two do not yield equivalent predicted values, but we show that in practice the differences are unlikely to be large. The alternate conditioning in the two models sheds light on the relationship between local and complete network data, and the role that models can play in bridging the gap between them.     

Analysis of growth curve data by using cubic smoothing splines

Longitudinal data frequently arises in various fields of applied sciences where individuals are measured according to some ordered variable, e.g. time. A common approach used to model such data is based on the mixed models for repeated measures. This model provides an eminently flexible approach to modeling of a wide range of mean and covariance structures. However, such models are forced into a rigidly defined class of mathematical formulas which may not be well supported by the data within the whole sequence of observations. A possible non-parametric alternative is a cubic smoothing spline, which is highly flexible and has useful smoothing properties. It can be shown that under normality assumption, the solution of the penalized log-likelihood equation is the cubic smoothing spline, and this solution can be further expressed as a solution of the linear mixed model. It is shown here how cubic smoothing splines can be easily used in the analysis of complete and balanced data. Analysis can be greatly simplified by using the unweighted estimator studied in the paper. It is shown that if the covariance structure of random errors belong to certain class of matrices, the unweighted estimator is the solution to the penalized log-likelihood function. This result is new in smoothing spline context and it is not only confined to growth curve settings. The connection to mixed models is used in developing a rough testing of group profiles. Numerical examples are presented to illustrate the techniques proposed.     

To live an ordinary life: resource needs and additional costs for people with a physical impairment

Disabled people face increased risks of living in poverty largely due to lower incomes and extra resource requirements compared to non-disabled people. This study incorporated the social model of disability with an economic approach to costing to estimate the additional costs required by people with a physical impairment to achieve an adequate standard of living in New Zealand. Budgets estimating the additional equipment, modifications, transport, support and time required to achieve an adequate standard of living were developed and validated through focus groups with community members. The findings suggest that reducing barriers involves substantial costs ranging from NZ$645–$2,348 per week.     

Measuring Social Return on Investment

Strategic decision making and evaluation in philanthropic giving and social investment requires good‐quality information about the social impacts of that investment. One way to meet this need is by calculating a social return on investment (SROI) measure, akin to the return on investment (ROI) approach used in business analysis. Despite much buzz in the field, SROI measurements are rarely used, in part because of the complexity of the calculations but also because of a number of thorny and often expensive organizational challenges associated with implementing an SROI process. This article explores these implementation challenges by comparing four social venture organizations in the health care field—two in the Netherlands and two in the United States—that have utilized some sort of SROI measurement. We summarize the SROI process and identify the specific organizational challenges in each case. Lessons learned from this analysis include the value of process versus product and the importance of fitting the type of measurement to the organizational context. We conclude with a summary of best practices for organizations and social investors who might try to make effective use of SROI measures.     

(Im)perishable Pleasure, (In)destructible Desire: Sexual Themes in U.S. and English News Coverage of Male Circumcision and Female Genital Cutting

Under what conditions do sexual pleasure and desire get addressed in news coverage of sexual health issues like female genital cutting (FGC) and male circumcision (MC)? In this study we employed an embodied ethnosexuality approach to analyze sexual themes in 1,902 items published from 1985 to 2009 in 13 U.S. and 8 English newspapers and news magazines. Journalists' discussions of sexual pleasure, desire, control, problems, and practices differed in quantity and quality depending on the practice and nation to which they pertained. News coverage in both nations presented FGC as impeding female sexual pleasure, desire, and activity in ways that reinforce (hetero)sexist understandings of sexuality. The English press depicted MC as diminishing male sexuality, whereas U.S. papers showed it as enhancing male sexuality. These patterns are influenced by, and serve to reinforce, cultural norms of embodiment and ethnosexual boundaries based on gender, race, and nationality. They may, in turn, shape public understandings of FGC and MC as social problems.