This article argues that social work in the UK needs to renegotiate its relationship with community welfare agencies. It begins by examining what we mean by local community and how welfare needs reflect complex non-linear dynamics unique to the local circumstances. It is argued that these are not always recognised in centralised policy agendas. The article broadly draws a parallel between policy issues for the European Community and for the national state. The drive for both is towards uniformity, which potentially fails to acknowledge the unique circumstances at both the national level between nations and the local level between communities.
The focus of the analysis is the lack of engagement with the subtleties of the local within the arena of social work education and practice. With the opportunity presented by the introduction of a new social work degree in the UK, the authors describe how a social work programme in Liverpool undertook a piece of research with the aim of creating an appropriate place for community welfare agencies in practice placements, the academic curriculum and, ultimately, with the next generation of social work practitioners. Eight welfare agencies within the proximity of Liverpool University, an area known as Toxteth, agreed to participate in the research to investigate what kind of placement module would enable local welfare agencies to engage meaningfully in the social work degree. Out of this process emerged a model for research based curriculum development involving local community agencies and academic institutions. More specifically for Liverpool, it placed the notion of social work's relationship with local community welfare at the heart of professional development for qualifying social workers, paving the way in this region of England for closer links between welfare agencies associated with civil society and professional social workers. 相似文献
A fully nonparametric model may not perform well or when the researcher wants to use a parametric model but the functional form with respect to a subset of the regressors or the density of the errors is not known. This becomes even more challenging when the data contain gross outliers or unusual observations. However, in practice the true covariates are not known in advance, nor is the smoothness of the functional form. A robust model selection approach through which we can choose the relevant covariates components and estimate the smoothing function may represent an appealing tool to the solution. A weighted signed-rank estimation and variable selection under the adaptive lasso for semi-parametric partial additive models is considered in this paper. B-spline is used to estimate the unknown additive nonparametric function. It is shown that despite using B-spline to estimate the unknown additive nonparametric function, the proposed estimator has an oracle property. The robustness of the weighted signed-rank approach for data with heavy-tail, contaminated errors, and data containing high-leverage points are validated via finite sample simulations. A practical application to an economic study is provided using an updated Canadian household gasoline consumption data. 相似文献
Since Skinner's [40] landmark article depicting the manufacturing function as the “missing link” in corporate strategic processes, a portion of the blame for inferior performance in many firms has been attributed to the subordinate strategic position of manufacturing. It has been argued that part of the solution to misalignments between the capabilities possessed by manufacturing and the requirements dictated by customers is for manufacturing to take a more proactive stance. However, little research has been reported which examines manufacturing proactiveness empirically. In this paper, we address this gap by developing an operational definition of manufacturing proactiveness and testing empirically whether a link exists between proactiveness and performance based on data collected from a sample of manufacturers. Based on the manufacturing strategy literature, we identify two major dimensions of manufacturing proactiveness: (1) the degree of manufacturing's involvement in the strategic processes of the business unit; and (2) the degree of commitment to a long-term program of investments in manufacturing structure and infrastructure aimed at building capabilities in anticipation of their need. We develop reliable scales for measuring each of the dimensions of proactiveness and use the data to provide evidence of a clear link between manufacturing proactiveness and business performance. We show that investments in structural programs coupled with either high levels of manufacturing involvement in strategic processes or planned investments in infrastructural programs correlate with higher than average performance. 相似文献