Child learning and family mealtime environment,parenting style and family functioning among preschoolers in Hong Kong

A two-wave longitudinal study on 470 parent–child dyads examined the impact of family mealtime environment, parenting style and family functioning on preschoolers’ (three to six years old) learning. Measures included parent report on parenting style, family functioning, family meal frequency, mealtime television, feeding practice, teacher/parent report of academic competence and individual assessment of preschoolers’ preschool concepts. Family mealtime environment variables were associated with pre-schoolers’ learning, in addition to parenting style and family functioning, after controlling for family income and wave 1 preschoolers’ learning. The results highlighted the importance of family mealtime environment on preschoolers’ learning.     

Flood Risk Perceptions and Insurance Choice: Do Decisions in the Floodplain Reflect Overoptimism?

In the presence of rare disasters, risk perceptions may not always align with actual risks. These perceptions can nevertheless influence an individual's willingness to mitigate risks through activities such as purchasing flood insurance. In a survey of Maryland floodplain residents, we find that stated risk perceptions predict voluntary flood insurance take‐up, while perceptions themselves varied widely among surveyed residents, owing in large part to differences in past flood experience. We use a formal test for overoptimism in risk perceptions and find that, on aggregate, floodplain residents are overly optimistic about flood risks.     

Toward Probabilistic Prediction of Flash Flood Human Impacts

This article focuses on conceptual and methodological developments allowing the integration of physical and social dynamics leading to model forecasts of circumstance‐specific human losses during a flash flood. To reach this objective, a random forest classifier is applied to assess the likelihood of fatality occurrence for a given circumstance as a function of representative indicators. Here, vehicle‐related circumstance is chosen as the literature indicates that most fatalities from flash flooding fall in this category. A database of flash flood events, with and without human losses from 2001 to 2011 in the United States, is supplemented with other variables describing the storm event, the spatial distribution of the sensitive characteristics of the exposed population, and built environment at the county level. The catastrophic flash floods of May 2015 in the states of Texas and Oklahoma are used as a case study to map the dynamics of the estimated probabilistic human risk on a daily scale. The results indicate the importance of time‐ and space‐dependent human vulnerability and risk assessment for short‐fuse flood events. The need for more systematic human impact data collection is also highlighted to advance impact‐based predictive models for flash flood casualties using machine‐learning approaches in the future.     

A dimensionality reduction method of continuous dependent variables based supervised Laplacian eigenmaps

Dimensionality reduction is one of the important preprocessing steps in high-dimensional data analysis. In this paper we propose a supervised manifold learning method, it makes use of the information of continuous dependent variables to distinguish intrinsic neighbourhood and extrinsic neighbourhood of data samples, and construct two graphs according to these two kinds of neighbourhoods. Following the idea of Laplacian eigenmaps, we reveal that on the low-dimensional manifold the neighbourhood structure can be preserved or even improved. Our approach has two important characteristics: (i) it uses dependent variables to find an informative low-dimensional projection which is robust to noisy independent variables and (ii) the objective function simultaneously enlarges the distance between dissimilar samples and pushes similar samples close to each other according to the graph constructed with the help of continuous dependent variables. Our experiments demonstrate that the effectiveness of our method is over their traditional rivals.     

Propensity score prediction for electronic healthcare databases using super learner and high-dimensional propensity score methods

ABSTRACT

The optimal learner for prediction modeling varies depending on the underlying data-generating distribution. Super Learner (SL) is a generic ensemble learning algorithm that uses cross-validation to select among a ‘library’ of candidate prediction models. While SL has been widely studied in a number of settings, it has not been thoroughly evaluated in large electronic healthcare databases that are common in pharmacoepidemiology and comparative effectiveness research. In this study, we applied and evaluated the performance of SL in its ability to predict the propensity score (PS), the conditional probability of treatment assignment given baseline covariates, using three electronic healthcare databases. We considered a library of algorithms that consisted of both nonparametric and parametric models. We also proposed a novel strategy for prediction modeling that combines SL with the high-dimensional propensity score (hdPS) variable selection algorithm. Predictive performance was assessed using three metrics: the negative log-likelihood, area under the curve (AUC), and time complexity. Results showed that the best individual algorithm, in terms of predictive performance, varied across datasets. The SL was able to adapt to the given dataset and optimize predictive performance relative to any individual learner. Combining the SL with the hdPS was the most consistent prediction method and may be promising for PS estimation and prediction modeling in electronic healthcare databases.     

Precarious lives and resistant possibilities: the labour of people with learning disabilities in times of austerity

This paper draws on feminist and queer philosophers? discussions of precarity and employment, too often absent from disability studies, to explore the working lives of people with learning disabilities in England in a time of austerity. Recent policy shifts from welfare to work welcome more disabled people into the job market. The reality is that disabled people remain under-represented in labour statistics and are conspicuously absent in cultures of work. We live in neoliberal-able times where we all find ourselves precarious. But, people with learning disabilities experience high levels of uncertainty in every aspect of their lives, including work, relationships and community living. Our research reveals an important analytical finding: that when people with learning disabilities are supported in imaginative and novel ways they are able to work effectively and cohesively participate in their local communities (even in a time of cuts to welfare). We conclude by acknowledging that we are witnessing a global politics of precarity and austerity. Our urgent task is to redress the unequal spread of precaritization across our society that risks leaving people with learning disabilities experiencing disproportionately perilous lives. One of our key recommendations is that it makes no economic sense (never mind moral sense) to pull funding from organisations that support people with intellectual disabilities to work.     

Learning disabled students and access to accommodations: socioeconomic status,capital, and stigma

In the 1990s, Canadian universities began implementing policies to accommodate learning disabled students. While such policies appear to make post-secondary education more accessible, students must manage considerable complexity and absorb social and financial costs to receive accommodations. Through interviews with learning disabled students, this research explores the effects of socio-economic status (SES) on how, or whether, students access accommodations at a Nova Scotian university. Drawing on the work of Bourdieu and Goffman, this study suggests that SES affects students’ abilities to navigate the accommodation process successfully, and that accommodation policies, while important, may not ensure equal access to accommodations.     

Open innovation and quality management: the moderating role of interorganisational IT infrastructure and complementary learning styles

This study seeks to explain the influence of quality management on the relationship between open innovation and performance. We propose that, to contribute to open innovation performance, an organisation’s commitment to quality improvement must rely on the combination of its own resources and capabilities and its open innovation partners’ resources and capabilities. Specifically, we examine the moderating role of an interorganisational IT infrastructure and the complementarity of learning styles among an organisation committed to quality improvement and its supply network. Using data from 270 managers of European firms, our results show that the negative effects of quality management on open innovation performance can be overcome by complementing the organisation’s learning style with that of its open innovation partner, particularly, its supply network, and, most importantly, obtaining information technologies compatible with those of its supply network members.     

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.     

A good fit: the contribution of action learning to supervision practice

This paper discusses the value of action learning for social work supervisors. Recent years have seen renewed focus on supervision as a reflective space and some indications that the tide may be turning in regard to the dominance of managerial priorities within the supervision of direct practice. It is less evident that a similar shift is taking place for supervisors themselves and, anecdotally, many describe their own supervision as having a business focus with limited scope for reflective dialogue. While the traditional functions of supervision need to adapt to fit the responsibilities of those in management positions, it remains true that these staff provide a vital containing role within the organisational hierarchy. For that to be sustained, it is important that supervisors have space and structure within which to process the emotional, intellectual and practical challenges of their work. The integration of action learning sets within post-qualifying courses for supervisors has demonstrated a useful dual function. Firstly, they provide an effective model for group supervision, facilitating in-depth reflection on complex practice issues. Secondly, they offer managers a peer supervision forum; a safe place to explore dilemmas and share the vulnerabilities which belong to management roles as well as practice.