Implementing Consumer Choice in Long‐term Care: The Impact of Individual Budgets on Social Care Providers in England

In common with many advanced welfare states, England has increasingly relied on consumerist principles to deliver both greater quality and improved efficiency in the long‐term care system. The Individual Budget (IB) pilots marked the next step in this process, through a new system of funding whereby greater control of resources is given to service users, in lieu of direct in‐kind care provision. IBs have the potential to transform the market for care services as well as the relationships between key stakeholders within it. Purchasing will increasingly be shaped by the demands of IB holders, with providers expected to deliver a wider range of personalized services. What will this mean for providers, and what can they do to prepare for these changes? These questions are relevant not just in England but in many other countries adopting similar mechanisms for devolving control over the design, delivery and funding of care to the end‐user. The article explores the early impact of IBs on providers' services, on their workforces, and on the administrative implications for providers of managing IBs. The study finds that providers were positive about the opportunities for better‐quality services that IBs can bring about. However, participants highlighted a number of obstacles to their effectiveness, and reported a range of potentially adverse administrative and workforce consequences which have the potential to jeopardize the consumerist policy objectives of increased choice and efficiency.     

Gambling Control Self-efficacy as a Mediator of the Effects of Low Emotional Intelligence on Problem Gambling

This study investigated whether lower emotional intelligence would be related to less self-efficacy to control gambling and more problem gambling and whether gambling self-efficacy would mediate the relationship between emotional intelligence and problem gambling. A total of 117 participants, including 49 women and 68 men, with an average age of 39.93 (SD = 13.87), completed an emotional intelligence inventory, a gambling control self-efficacy scale, and a measure of problem gambling. Lower emotional intelligence was related to lower gambling self-efficacy and more problem gambling. Gambling control self-efficacy partially mediated the relationship between emotional intelligence and problem gambling.     

Small area estimation of proportions under a spatial dependent aggregated level random effects model

This paper describes small area estimation (SAE) of proportions under a spatial dependent generalized linear mixed model using aggregated level data. The SAE is also applied to produce reliable district level estimates and mapping of incidence of indebtedness in the State of Uttar Pradesh in India using debt and investment survey data collected by National Sample Survey Office (NSSO) and the secondary data from the Census. The results show a significant improvement in precision of model-based estimates generated by SAE as compared to direct estimates. The estimates generated by incorporating spatial information are more efficient than the one generated by ignoring this information.     

Relabelling in Bayesian mixture models by pivotal units

Label switching is a well-known and fundamental problem in Bayesian estimation of finite mixture models. It arises when exploring complex posterior distributions by Markov Chain Monte Carlo (MCMC) algorithms, because the likelihood of the model is invariant to the relabelling of mixture components. If the MCMC sampler randomly switches labels, then it is unsuitable for exploring the posterior distributions for component-related parameters. In this paper, a new procedure based on the post-MCMC relabelling of the chains is proposed. The main idea of the method is to perform a clustering technique on the similarity matrix, obtained through the MCMC sample, whose elements are the probabilities that any two units in the observed sample are drawn from the same component. Although it cannot be generalized to any situation, it may be handy in many applications because of its simplicity and very low computational burden.     

Servers and providers: the distribution of food within the family*

We examine the nature of decision-making surrounding food provision within families and the patterns of food distribution established. The analysis draws upon detailed interview material and dairy records gather from 200 women currently bringing up young children. The sexual divisions and power relations which characterize families are found to have an impact on the choice of food for family consumption and on women's theories concerning the food needs of family members. The manner in which these theories are given concrete expression in the differential distribution of meat both between the sexes and intergenerationally is revealed. Variations in the extent of such inequalities are assessed with reference to the nature of the work undertaken by the marital partners and their relative control over money.     

Concise or comprehensive? Predictors of impact assessment choices for electric transmission line projects

Environmental impact assessment (EIA) procedures required in the United States and many other countries are often highlighted as a major hindrance to timely and efficient deployment of critical infrastructure projects. Under the U.S. National Environmental Policy Act, a more extensive environmental impact statement (EIS) review can take several more years and cost much more than a succinct environmental assessment (EA). This not only affects the project in question, but also likely informs how—or whether—additional projects are pursued. Thus, understanding key predictors of the EA versus EIS choice sheds light on supply-side considerations affecting infrastructure deficits. Using the case of NEPA reviews conducted for 244 transmission line projects between 2005 and 2018 by two U.S. federal agencies in the western United States, the Bureau of Land Management (BLM) and Department of Energy (DOE), this addresses the following question: What project features most predict whether EA or an EIS is used to assess a transmission line project? Drawing upon NEPA assessment guidance and agency NEPA records, we use a regression classification tree to analyze how protocols and project attributes relate to assessment choice. The result is essentially a null finding: transmission line length is by far the most important predictor of whether a project receives an extensive EIS or a shorter EA, with little predictive value provided by other attributes. While absolute project size undoubtedly influences impacts, the lack of further differentiation in what predicts use of EISs versus EAs suggests assessment does not simply respond to project details but also shapes proposal and design choices beforehand.     

Sex counts: An examination of sexual service advertisements in a UK online directory

Internationally, sex work research, public opinion, policy, laws, and practice are predicated on the assumption that commercial sex is a priori sold by women and bought by men. Scarce attention has been devoted to lesbian, gay, bisexual, transgender, or queer/questioning (LGBTQ) sex working as well as women who pay for sex. This is as much an empirical absence as it is a theoretical one, for the ideological claim that women comprise the “vast majority” of sex workers is rarely, if ever, exposed to empirical scrutiny. Focusing on the UK, we address this major gap in evidence in order to challenge the gendered and heterosexist logics that underpin contemporary debates. We do so by presenting large-scale data gained from the quantitative analysis of 25,511 registered member profiles of an online escort directory. Our findings point to heterogeneity rather than homogeneity in the contemporary sex industry including in terms of gender identity, sexual orientation, and advertised client base. For example, while two-thirds of advertisements self-identify as “Female,” one in four are listed as “Male;” less than half list their sexual orientation as “Straight;” and nearly two-thirds advertise to women clients. Our study thus challenges prevailing heteronormative assumptions about commercial sex, which erase LGBTQ sex workers and other non-normative identities and practices, and which we argue have important political, practical, and theoretical consequences.     

Young British religious ‘nones’: findings from the Youth On Religion study

This article contributes to an understanding of diversity in beliefs and practices among young religious ‘nones’ who report the absence of a specific religious faith. It focuses on those describing themselves as atheist, agnostic or otherwise of ‘no religion’ within (a) a large-scale survey of over ten thousand 13–17-year-olds, and (b) interviews, discussion groups and eJournal entries involving one hundred and fifty-seven 17–18-year-olds, in three British multi-faith locations. Compared to the study population as a whole, the young religious ‘nones’ were particularly likely to be white and born in Britain. There was, nonetheless, considerable diversity among this group in beliefs and practices: almost half the survey members mentioned some level of belief in God and most of the interview participants pointed to some presence of religion in their lives. Being a religious ‘none’ is, furthermore, not necessarily a stable identity and some young people had already shown considerable fluidity over their life cycles. Around half the survey members said they had maintained similar religious views to their mothers, but participants in both quantitative and qualitative studies pointed to the impact of their experiences and interactions, as well as the role of science, as factors affecting their beliefs and practices.     

Finite mixtures of quantile and M-quantile regression models

In this paper we define a finite mixture of quantile and M-quantile regression models for heterogeneous and /or for dependent/clustered data. Components of the finite mixture represent clusters of individuals with homogeneous values of model parameters. For its flexibility and ease of estimation, the proposed approaches can be extended to random coefficients with a higher dimension than the simple random intercept case. Estimation of model parameters is obtained through maximum likelihood, by implementing an EM-type algorithm. The standard error estimates for model parameters are obtained using the inverse of the observed information matrix, derived through the Oakes (J R Stat Soc Ser B 61:479–482, 1999) formula in the M-quantile setting, and through nonparametric bootstrap in the quantile case. We present a large scale simulation study to analyse the practical behaviour of the proposed model and to evaluate the empirical performance of the proposed standard error estimates for model parameters. We considered a variety of empirical settings in both the random intercept and the random coefficient case. The proposed modelling approaches are also applied to two well-known datasets which give further insights on their empirical behaviour.