‘Surrounded with so much uncertainty’: asylum seekers and manufactured precarity in Australia

In Australia, nearly 30,000 asylum seekers have the legal right to work, but their temporary and conditional migration status exposes them to work-related precarity. This article draws on a small qualitative study that examined asylum seekers’ experiences of seeking work and achieving economic security. Over an 18-month period, 29 semi-structured interviews with asylum seekers who had work rights in Australia were conducted. It provides insights into how restrictive immigration policies manufacture precarity through short-term, conditional visas, resulting in employer risk aversion, segmentation into insecure work, and in-work instability and mistreatment. Asylum seekers manage their experiences and feelings of pervasive insecurity through individual coping and survival strategies.     

Expatriate contact with a local host: an intervention to increase social support

Social capital is a crucial factor for expatriates to employ as they cope with the demands of an international assignment. This longitudinal study used a mixed method approach to examine the social support benefits of expatriate contact with a local host. Western expatriates in the Netherlands were randomly divided into two groups: an experimental group (n = 33), that had contact with a Dutch host during 9 months, and a control group (n = 32) with no host. Qualitative methods such as interviews and diaries were included to shed light on the various types of social support that occurred. Results show that local hosts offered all four types of social support: social companionship, informational support, emotional support, and instrumental support. Furthermore, expatriates with a host increased their social capital; they received significantly more social support from host nationals than did those without a host. This study shows that HRD professionals may develop the social capital of expatriates by bringing them into contact with a local host, which can produce more social support from host nationals. Increased social capital may lead to a higher performance at both the individual and organisational levels.     

Estimates of subgroup treatment effects in overall nonsignificant trials: To what extent should we believe in them?

In drug development, it sometimes occurs that a new drug does not demonstrate effectiveness for the full study population but appears to be beneficial in a relevant subgroup. In case the subgroup of interest was not part of a confirmatory testing strategy, the inflation of the overall type I error is substantial and therefore such a subgroup analysis finding can only be seen as exploratory at best. To support such exploratory findings, an appropriate replication of the subgroup finding should be undertaken in a new trial. We should, however, be reasonably confident in the observed treatment effect size to be able to use this estimate in a replication trial in the subpopulation of interest. We were therefore interested in evaluating the bias of the estimate of the subgroup treatment effect, after selection based on significance for the subgroup in an overall “failed” trial. Different scenarios, involving continuous as well as dichotomous outcomes, were investigated via simulation studies. It is shown that the bias associated with subgroup findings in overall nonsignificant clinical trials is on average large and varies substantially across plausible scenarios. This renders the subgroup treatment estimate from the original trial of limited value to design the replication trial. An empirical Bayesian shrinkage method is suggested to minimize this overestimation. The proposed estimator appears to offer either a good or a conservative correction to the observed subgroup treatment effect hence provides a more reliable subgroup treatment effect estimate for adequate planning of future studies.     

Measuring Child Poverty in South Africa: Sensitivity to the Choice of Equivalence Scale and an Updated Profile

This paper offers evidence on the sensitivity of child poverty in South Africa to changes in the adult equivalence scale (AES) and updates the child poverty profile based on the Income and Expenditure Survey 2005/06. Setting the poverty line at the 40th percentile of households calculated with different AESs the scope and composition of child poverty are found to be relatively insensitive to the scale used. The rankings of children of different ages, girls versus boys, racial groupings and children living in rural versus urban areas are unaffected by choice of AES, although some provincial rankings on the poverty headcount measure are. The proportions of children and households ‘correctly’ identified as poor for the full range of scales is extremely high. These findings support the argument that it may be appropriate for profiling poverty in South Africa to use a poverty line based on a per capita welfare measure. For the construction of the child poverty profile, per capita income is used as the welfare indicator with the poverty line set at the 40th percentile of household. The profile suggests that poverty amongst children is more extensive than amongst the population or adults even after the massive injection of transfers into households with poor children through the child support grant. The child poverty headcount, depth and severity are all highest amongst children age 0–4 and lowest amongst those aged 15–17, who are not yet beneficiaries of the grants. They are also highest amongst African and Coloured children. Large variations across provinces remain. The analysis underlines the importance of prioritising children in the fight against poverty, particularly in their earliest years.     

Differences between paid and unpaid social services for beneficiaries

In many Western welfare states, social work services that have traditionally been provided by paid employees are being replaced by family support, community support, informal networks, and volunteering. For the field of social work, it is relevant to know what it matters to beneficiaries whether services are provided by volunteers or by paid employees. The central question of this article is therefore as follows: What are the differences between unpaid and paid social services for beneficiaries? The article is based on literature review and focus groups. Our results suggest that beneficiaries do experience some differences regarding the advantages of volunteer services for beneficiaries that can be summarized in three propositions: (1) services provided by volunteers are more relational than are services provided by paid employees, and they are therefore perceived as more equal, flexible and sincere. (2) The effects of volunteer services for beneficiaries are not exclusively positive. (3) Although particular tasks may appear to be interchangeable to some extent, the relative advantages of a given task depend upon whether it is performed by a paid worker or by a volunteer. Additional research is needed in order to provide further validation.     

Impact of Race on the Implementation of Empirically Supported Treatments in Substance Abuse Treatment

The effort to address the gap between research and practice in substance abuse treatment has largely neglected the role of local resources and political trends. This study seeks to clarify the role of the local environment in implementing empirically supported treatments (ESTs). The study consisted of secondary data analysis of substance abuse treatment centers (N = 13,079) and U.S. Census data to determine the likelihood of using EST by substance abuse treatment centers in counties with 50% or more Black residents. Bivariate and multivariate models were employed. After controlling for various factors, results indicate that substance use disorder treatment agencies that accept federal funding are less likely to use ESTs if they are located in counties with predominantly (> 50%) Black residents. Implementation of ESTs could be influenced by community racial distribution (% Black), but environmental constraints and events might shift implementation patterns.     

A socio-ecological perspective of urban green networks: the Stockholm case

Landscape fragmentation threatens habitats, biodiversity and other ecosystem services. In tackling this threat, the dynamic processes of social-ecological systems should be recognised and understood. Although network analysis based on graph theory has been recognised as an efficient way of spatially understanding landscape or habitat connectivity, only few studies have offered specific approaches or suggestions for integrating detailed social-ecological values into geographical distributions. As a contribution to bridging this gap, this paper introduces a social-ecological network model for the issue of landscape or habitat fragmentation applied to the case of Stockholm, Sweden. Graph theory was used in combination with sociotope and biotope maps for simple visualisation of network situations in two-dimensional maps. The European crested tit (Lophophanes cristatus), European common toad (Bufo bufo) and human beings were selected as indicator species, based on a landscape ecology analysis in Stockholm Municipality in 2009. Slope, land use and human disturbance maps were assessed in order to decide cost values of travelling from node to node. Lease-cost-path accumulation was used to create ideal reference maps of green networks. Three separate maps were then developed for suggesting efficient routes for three indicators in city scale that mainly connect from the Royal National City Park to the other parts of the city. The model in Hjorthagen neighbourhood to highlight two practical paths that link this fragmented community to its neighbouring park areas. Findings make it possible to address two scales of network improvement strategies, namely first for the city-scale green network that connects geographical habitats (nodes) and the regional green wedges of the city, and the second that of neighbourhood links between habitats in detailed layers of green networks. Strategic improvement potentials are presented based on ideal reference maps of green networks correspondingly.     

Who is leading the campaign charts? Comparing individual popularity on old and new media

Attention in the mass media is seen as crucial for electoral success. However, most ordinary candidates hardly get any attention in the news. With social media outlets becoming ever more popular, the question is whether the overall asymmetry in attention for candidates still holds today. Do candidates who dominate the traditional media during the campaign also dominate the social media? Or can candidates make up for a lack of mass media coverage by attracting attention on these new media platforms? This paper aims to answer these questions by pairing Twitter activity and Twitter popularity with newspaper attention for a large number of individual candidates in the 2014 Belgian election campaign. We expand the normalization versus equalization debate by not only looking at how much a new medium is used, but also at its success in terms of popularity and audience reach. Our findings show that the two platforms are indeed related, mainly because a small political elite dominates both old and new media. Twitter popularity and Twitter activity (albeit to a lesser extent) are higher among powerful politicians. We elaborate on why these findings are so much in line with the normalization hypothesis.     

Functional analysis of high-content high-throughput imaging data

High-content automated imaging platforms allow the multiplexing of several targets simultaneously to generate multi-parametric single-cell data sets over extended periods of time. Typically, standard simple measures such as mean value of all cells at every time point are calculated to summarize the temporal process, resulting in loss of time dynamics of the single cells. Multiple experiments are performed but observation time points are not necessarily identical, leading to difficulties when integrating summary measures from different experiments. We used functional data analysis to analyze continuous curve data, where the temporal process of a response variable for each single cell can be described using a smooth curve. This allows analyses to be performed on continuous functions, rather than on original discrete data points. Functional regression models were applied to determine common temporal characteristics of a set of single cell curves and random effects were employed in the models to explain variation between experiments. The aim of the multiplexing approach is to simultaneously analyze the effect of a large number of compounds in comparison to control to discriminate between their mode of action. Functional principal component analysis based on T-statistic curves for pairwise comparison to control was used to study time-dependent compound effects.