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.     

Disaggregate-level estimates of indebtedness in the state of Uttar Pradesh in India: an application of small-area estimation technique

The National Sample Survey Organisation (NSSO) surveys are the main source of official statistics in India, and generate a range of invaluable data at the macro level (e.g. state and national levels). However, the NSSO data cannot be used directly to produce reliable estimates at the micro level (e.g. district or further disaggregate level) due to small sample sizes. There is a rapidly growing demand of such micro-level statistics in India, as the country is moving from centralized to more decentralized planning system. In this article, we employ small-area estimation (SAE) techniques to derive model-based estimates of the proportion of indebted households at district or at other small-area levels in the state of Uttar Pradesh in India by linking data from the Debt–Investment Survey 2002–2003 of NSSO and the Population Census 2001 and the Agriculture Census 2003. Our results show that the model-based estimates are precise and representative. For many small areas, it is even not possible to produce estimates using sample data alone. The model-based estimates generated using SAE are still reliable for such areas. The estimates are expected to provide invaluable information to policy analysts and decision-makers.     

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.     

Modelling Job-Search Duration from the Italian Labour Force Data

ABSTRACT: Micro (and possibly panel) data from the Labour Force Surveys are a valuable source for analysing the labour supply behaviour. Among the information collected by the quarterly Italian Labour Force Survey conducted by ISTAT (the Italian national statistical agency), there are data on the duration of job-search. From a single survey, one can only know the duration of search up to the time of the interview. Nonetheless, by appropriately exploiting the longitudinal structure of the survey (the sample scheme is a rotated one, with a 50|X% overlapping of the sample units in two subsequent quarters) it is possible to measure, although imperfectly, some completed spells of job-search. In this paper, we try to model the duration of job-search for a sample of young unemployed. Considerable attention is devoted to the measure of duration of search, and to the evaluation of its accuracy. A one state proportional hazard model is specified and estimated, accounting also for unobserved heterogeneity. The model is estimated on a sample of young (15 to 29 years old) unemployed in January 1986 reinterviewed in April, in an Italian region (Lombardy). The major finding is a fairly clear evidence, both for males and females, of negative duration dependence, even after accounting for the unobserved heterogeneity that turns out to affect the female population.     

Does Mixed Methods Research Matter to Understanding Childhood Well-Being?

There has been a rich debate in development studies on combining research methods in recent years. We explore the particular challenges and opportunities surrounding mixed methods approaches to childhood well-being. We argue that there are additional layers of complexity due to the distinctiveness of children’s experiences of deprivation or ill-being. This paper is structured as follows. Sections 2 and 3 discuss the nature of mixed methods approaches and tensions. Sections 4 and 5 apply these debates to researching childhood well-being in particular, in both Northern and Southern contexts. Section 6 concludes and discusses future work.

Brave new brains: sociology,family and the politics of knowledge

This article critically explores sociological arguments for greater biosocial synthesis, centring contemporary developments in public policy to demonstrate how such a reframing of humanity tends to reinforce existing political orders and socially patterned normativities. The case for further amalgamation of the social and life sciences is examined to suggest that production of somatic markers of truth from relational encounters largely relies upon an anaemic and politically contained version of the social as acquired in early childhood. More specifically, the gendered, classed and culturally specific practice of parenting children has come to occupy a new significance in accounts of social brains and environmentally reactive genomes. This is highlighted through a discussion of ‘early intervention’ as a heavily biologized policy rationale framing opportunities for biosocial collaboration. It is argued that late capitalist objectives of personal investment and optimization are driving this assimilation of the social and life sciences, pursuing an agenda that traces and re‐scores long‐standing social divisions in the name of progress.