“It’s a generosity loop”: Religious and spiritual motivations of volunteers who glean produce to reduce food insecurity

Food insecurity is a common social issue and households look to assistance from food pantries, which often have difficulty supplying fresh or nutritious food. A substantial amount of produce is left in the fields, which can be collected through gleaning. In a focus group with volunteer gleaners at a faith-based nonprofit organization that attempts to fill the gaps of food insecurity, the motivations, challenges, and benefits of volunteering were examined. Volunteering in gleaning generated a sense of collective purpose and community; it addressed deeply held religious and spiritual impulses; and it puts volunteers directly in contact with nature.     

Cambodian Refugee Families: Impacts of Immigration-Related Stressors on Intergenerational Relationships

The purpose of this study was to elucidate Cambodian refugees’ perceptions of immigration-related stressors and their impacts on intergenerational relations during the processes of immigration and settlement. We used narrative analysis to evoke older immigrants’ voices as they transitioned to the United States. Thirty-one Cambodian immigrants were interviewed using open-ended interview guides informed by ethnographic tenets of data collection. Participants expressed (a) changes in family structure and elder isolation and (b) intergenerational ambivalence and elder’s dependence on adult children as products of immigration-related stressors. Implications of these results for refugee and immigrant mental health research are discussed.     

Computationally and statistically efficient model fitting techniques

A significant challenge in fitting metamodels of large-scale simulations with sufficient accuracy is in the computational time required for rigorous statistical validation. This paper addresses the statistical computation issues associated with the Bootstrap and modified PRESS statistic, which yield key metrics for error measurements in metamodelling validation. Experimentation is performed on different programming languages, namely, MATLAB, R, and Python, and implemented on different computing architectures including traditional multicore personal computers and high-power clusters with parallel computing capabilities. This study yields insight into the effect that programming languages and computing architecture have on the computational time for simulation metamodel validation. The experimentation is performed across two scenarios with varying complexity.     

Named social workers – better social work for learning disabled people?

In 2016, the Department of Health in England announced that it would pilot the role of Named Social Worker. We chose to be part of the pilot because we regularly witness too many people’s lives being defined by restrictions imposed by professionals. Erroneous associations between the concepts of risk and danger have become the norm in how learning disabled people’s decision-making is perceived and managed. However, we believe social workers educated in the social model of disability and grounded more generally in disability studies offer an alternative perspective. The pilot is an opportunity to test our hypothesis that social work practice rooted in social model thinking can successfully challenge oppressive practice and disabling barriers, thus providing the opportunity for social workers to genuinely be ‘servants not masters’ in the lives of disabled people.     

The perils of father-reported fertility data for household labour supply models

Many panel data-sets contain father-reported fertility data. Yet, since men tend to underreport past fertility--especially daughters or children from previous marriages--using such data can lead to significantly biased results when estimating household labour supply models. For example, when analysing fertility data from the Panel Study of Income Dynamics, which has a significant retrospective component, fathers' labour supply appears more responsive to the births of sons than to daughters (Lundberg and Rose, Review of Economics and Statistics 84(2): 251-268, 2002). However, no evidence for this differential can be found in a much larger sample of Current Population Survey data from the same population. It is important for researchers to consider the provenance of data on fertility variables and to undertake robustness checks with data reported by women whenever possible.     

Retrospective information on health status and its application for population health measures

Healthy life expectancies are almost always calculated by using health data from cross-sectional surveys. This type of calculation is done partly because data from longitudinal surveys are not always available, and when they are available, they are collected at intervals that are longer than one year. In such cases, collecting health information retrospectively for the years skipped by the survey is useful. The main purpose of this paper is to show how retrospective health information can be used to estimate life expectancies in different health states. Healthy life expectancies are estimated with and without using data on retrospective health information, and the corresponding estimates are compared. The two sets of estimates are similar. We conclude that retrospectively assessed health information based on a one-year recall period can be used to estimate years of life in various health states and that estimates based on such information will closely approximate estimates based on concurrent health information.     

Providing Spatial Data for Secondary Analysis: Issues and Current Practices Relating to Confidentiality

Spatially explicit data pose a series of opportunities and challenges for all the actors involved in providing data for long-term preservation and secondary analysis—the data producer, the data archive, and the data user. We report on opportunities and challenges for each of the three players, and then turn to a summary of current thinking about how best to prepare, archive, disseminate, and make use of social science data that have spatially explicit identification. The core issue that runs through the paper is the risk of the disclosure of the identity of respondents. If we know where they live, where they work, or where they own property, it is possible to find out who they are. Those involved in collecting, archiving, and using data need to be aware of the risks of disclosure and become familiar with best practices to avoid disclosures that will be harmful to respondents.

Person, Perception, and Place: What Matters to Health and Quality of Life

Interest in understanding how characteristics associated with where people live, in addition to the characteristics of the people themselves, affect health outcomes has risen sharply in recent years. While much of the research examining this question focus on teasing apart effects of place and individual on outcomes, less attention has been paid to examining how individuals’ perceptions of where they live may provide some clues to better understanding the influence of place on outcomes. We present findings from analysis undertaken that incorporate the subjective responses of individuals, residing in three socially contrasting neighbourhoods, to their local environment. Our first question addressed whether perceptions related to neighbourhood and city of residence matter to self rated health and quality of life independent of individual characteristics, while the second question examined whether the perceptions and individual characteristics are modified by the neighbourhood socio-economic context. Our results show that perceived neighbourhood characteristics, in addition to individual sociodemographic factors, are significant correlates of self rated health and quality of life. Moreover, we show that the type of perceived neighbourhood characteristics and the magnitude of their influence on self rated health and quality of life vary depending on whether they live in high- versus low-socioeconomic status neighbourhoods.