Working systemically following abuse: exploring safe uncertainty

This paper explores systemic practice and ‘safe uncertainty’ in work with parents who do not accept responsibility following child abuse. The prevailing view has been that little positive work can be carried out with families where responsibility is denied. Our work is offered to add to the small yet growing number of publications which challenge the dominant discourse relating to child protection work. A case study is illustrated within which the issue of assessment versus therapy emerges. The Legal Department of the Local Authority Social Services requested an assessment from child and family psychiatry. Concern developed regarding the point at which assessment ended and therapy began. The authors offer a systemic model in exploring the importance of a safe multi‐disciplinary framework within which uncertainty can be tolerated and therapy/change work can be affected. A framework within which parents can be supported in developing skills to meet the needs of children is presented. These issues are central to the professional and legal systems relating to child protection in the UK. Copyright © 1999 John Wiley & Sons, Ltd.     

Multicriteria decision making applied to waste recycling in Brazil

Waste management, like other environmental issues, tends to be a suitable topic for problem solving using multicriteria decision-making techniques when uncertainty is involved. This paper presents two cases where the decision makers had different preferences. In the first case, social agents required an evaluation of different disposal alternatives for plastic waste. In the second case, existing construction and demolition waste recycling facilities required a performance evaluation.     

A mortality model based on a mixture distribution function

A new mortality model based on a mixture distribution function is proposed. We mix a half-normal distribution with a generalization of the skew-normal distribution. As a result, we get a six-parameter distribution function that has a good fit with a wide variety of mortality patterns. This mixture model is fitted to several mortality data schedules and compared with the Siler (five-parameter) and Heligman–Pollard (eight-parameter) models. Our proposal serves as a convenient compromise between the Heligman–Pollard model (which ensures a good fit with data but is often overparameterized) and the Siler model (which is more compact but fails to capture ‘accident humps’).     

How We Fall Apart: Similarities of Human Aging in 10 European Countries

We analyze human aging—understood as health deficit accumulation—for a panel of European individuals, using four waves of the Survey of Health, Aging and Retirement in Europe (SHARE data set) and constructing a health deficit index. Results from log-linear regressions suggest that, on average, elderly European men and women develop approximately 2.5 % more health deficits from one birthday to the next. In nonlinear regressions (akin to the Gompertz-Makeham model), however, we find much greater rates of aging and large differences between men and women as well as between countries. Interestingly, these differences follow a particular regularity (akin to the compensation effect of mortality) and suggest an age at which average health deficits converge for men and women and across countries. This age, which may be associated with human life span, is estimated as 102 ± 2.6 years.     

Ranking and Prioritization of Emergency Departments Based on Multi-indicator Systems

In this work we discuss how Emergency Departments (EDs) can be ranked on the basis of multiple indicators. This problem is of absolute relevance due to the increasing importance of EDs in regional healthcare systems and it is also complex as the number of indicators that have been proposed in the literature to measure ED performance is very high. Current literature faces this problem using synthetic (or numerically aggregated) indicators of a set of performance measures but, although simple, this solution has a number of drawbacks that make this choice inefficient: a compensation effect among the indicators; a high degree of subjectivism in the indicators weighting; opacity in the decision making; all the EDs are considered to be comparable. Indeed, the situations in which EDs are comparable (i.e. when all the performance of one ED are not lower than the performance indicators of the other) are a minority and incomparability is by itself a source of information that should be used to identify situations for which different policy actions should be designed. In this work we propose to use non compensatory composite indicators and partial ordering theory to rank and compare EDs giving value to the reasons of such an incomparability. These methods are applied on a case study of 19 EDs in an administrative region in Italy.     

Big Data and Social Indicators: Actual Trends and New Perspectives

Big Data are a top subject in international research articles and a vast debate is taking place on their actual capability of being used to complement or even substitute official statistics surveys and social indicators in particular. In this paper we analyse the metadata of the Scopus database of academic articles on Big Data and we show that most of the existing and intensively growing literature is focused on software and computational issues whilst articles that are specifically focused on statistical issues and on the procedures to build social indicators from Big Data are a much smaller share of this vast production. Nevertheless the works that focus on these topics show promising results because in developed countries Big Data seem to be a good information base to create reliable proxies of social indicators, whereas in developing countries their use (for instance using satellite images) may be a viable alternative to traditional surveys. However, Big Data based social indicators deeply suffer of a number of open issues that affect their actual use: they do not correspond to any sampling scheme and they are often representative of particular segments of the population; they generally are private process-produced data whose access by national statistical offices is rarely possible although the intrinsic value of the information contained in Big Data has a social importance that should be shared with the whole community; Big Data lack the socio-economic background on which social indicators have been founded and their help to policy makers in their decision process is a fully open point. Therefore Big Data may be a big opportunity for the definition of traditional or new social indicators but their statistical reliability should be further investigated and their availability and use should be internationally coordinated.     

Racial disparities in birth care: Exploring the perceived role of African-American women providing midwifery care and birth support in the United States

Background

Midwifery care has been linked to positive birth outcomes. Despite the broad racial disparities in maternal and infant outcomes in the United States (US), little is known about the role of minority women in either providing or receiving this type of care. A vibrant community of minority women, who self-identify as providing these services, exists online. In this exploratory study we ask how they describe their role; view their practice; and position themselves in the broader discussions of racial health disparities in the US.