Networking practitioner research: synthesising the state of the ‘art’

The aim of this paper is to examine what we know about the experience and outcomes of networked initiatives aimed at facilitating practitioner research. We outline the roles and significance of practitioner research within social work; review emerging understanding of practitioner research network initiatives; and draw conclusions from a comparative analysis of three such initiatives in Auckland, New Zealand, Arhus County, Denmark, and across Scotland. We consider the nature and challenges of practitioner research and a number of responses to how such work should be formulated and conducted. Central to our argument is an empirically informed consideration—from our separate and shared experiences—of how well networks enhance the process and consequences, and art and craft, of such research projects.     

Poly-victimization and resilience portfolios: Trends in violence research that can enhance the understanding and prevention of elder abuse

ABSTRACT

This literature review assesses the current state of knowledge about elder abuse and mistreatment, focusing on the lack of incorporation of all forms of elder victimization and the benefits of a poly-victimization framework. This review also includes existing knowledge on risk factors and calls for a greater focus on protective factors and a greater inclusion on family and community factors. Future research, prevention, and intervention would benefit from considering the true burden of elder victimization and a greater implementation of strengths-based approaches to programs.     

Evaluating Probabilistic Forecasts with Bayesian Signal Detection Models

We propose the use of signal detection theory (SDT) to evaluate the performance of both probabilistic forecasting systems and individual forecasters. The main advantage of SDT is that it provides a principled way to distinguish the response from system diagnosticity, which is defined as the ability to distinguish events that occur from those that do not. There are two challenges in applying SDT to probabilistic forecasts. First, the SDT model must handle judged probabilities rather than the conventional binary decisions. Second, the model must be able to operate in the presence of sparse data generated within the context of human forecasting systems. Our approach is to specify a model of how individual forecasts are generated from underlying representations and use Bayesian inference to estimate the underlying latent parameters. Given our estimate of the underlying representations, features of the classic SDT model, such as the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC), follow immediately. We show how our approach allows ROC curves and AUCs to be applied to individuals within a group of forecasters, estimated as a function of time, and extended to measure differences in forecastability across different domains. Among the advantages of this method is that it depends only on the ordinal properties of the probabilistic forecasts. We conclude with a brief discussion of how this approach might facilitate decision making.     

Labour Underutilisation and Gender: Unemployment Versus Hidden-Unemployment

As labour markets have become more complex there has been increasing interest among researchers in understanding the ways that social and labour market processes and contexts impact on various labour market states. One important area has been in understanding the differences between unemployment and hidden unemployment. This paper considers the ways in which these two labour market states differ for a sample of male and female respondents to the Household Income and Labour Dynamics Australia (HILDA) survey. It presents data related to the reasons why respondents in these two labour force states consider they are jobless and analyses the characteristics of male and female respondents in the two labour market states to consider differences in outcomes. The findings suggest that there are differences in the two states of labour market outcomes and that these are further complicated when one considers processes for males and females.     

Comparing several experimental groups with a control in the multivariate case

This paper presents a multivariate extension of Dunnett's test for comparing simultaneously k treatment group means with a single control group mean. A test based on Hotelling T²statistics is presented and approximate critical values are evaluated for the case of equal numbers of observations in each group, for the .05 and .01 levels of significance, for 1 to 5 variates, for 1 to 10 treatment groups, and for varying degrees of freedom. The accuracy of the procedure for generating approximate critical values is assessed via simulation studies conducted for selected cases and an example is presented using real data.     

Revisiting the model of creative destruction: St. Jacobs,Ontario, a decade later

Ten years ago, the model of creative destruction was developed to predict the fate of communities that base their development on the commodification of rural heritage (Mitchell, C.J.A., 1998. Entrepreneurialism, commodification and creative destruction: a model of post-modern community development. Journal of Rural Studies 14, 273–286). Its application to the village of St. Jacobs, Canada, demonstrated that entrepreneurial investment had fostered the creation of a setting for aestheticized consumption. In this paper we demonstrate that creative destruction has continued to unfold in the village over the course of the past decade. The evolutionary path taken is assessed in light of current literature on rural space. It is concluded that to fully understand the transformative process, one must integrate the demands of myriad sub-cultures, whose social relations, ideologies and actions will contribute to the development of a contested landscape of consumption. This finding necessitates that modifications be made to the model and its various stages. The most significant is recognition that the “heritage-scape” is an interim state of landscape change; one that displaces the productivist landscape of the industrial period, and precedes the creation of the “neo-productivist” leisure-scape of post-industrialism. Whether or not such a “final” state is achieved is dictated by the power struggle that inevitably arises amongst sub-cultures engaged in the transformation of rural space.     

Quantifying the Hurricane Catastrophe Risk to Offshore Wind Power

The U.S. Department of Energy has estimated that over 50 GW of offshore wind power will be required for the United States to generate 20% of its electricity from wind. Developers are actively planning offshore wind farms along the U.S. Atlantic and Gulf coasts and several leases have been signed for offshore sites. These planned projects are in areas that are sometimes struck by hurricanes. We present a method to estimate the catastrophe risk to offshore wind power using simulated hurricanes. Using this method, we estimate the fraction of offshore wind power simultaneously offline and the cumulative damage in a region. In Texas, the most vulnerable region we studied, 10% of offshore wind power could be offline simultaneously because of hurricane damage with a 100‐year return period and 6% could be destroyed in any 10‐year period. We also estimate the risks to single wind farms in four representative locations; we find the risks are significant but lower than those estimated in previously published results. Much of the hurricane risk to offshore wind turbines can be mitigated by designing turbines for higher maximum wind speeds, ensuring that turbine nacelles can turn quickly to track the wind direction even when grid power is lost, and building in areas with lower risk.     

On the robustness of the extreme deviate test for a single multivariate outlier against heavy-tailed distributions

In this paper we assess the sensitivity of the multivariate extreme deviate test for a single multivariate outlier to non-normality in the form of heavy tails. We find that the empirical significance levels can be markedly affected by even modest departures from multivariate normality. The effects are particularly severe when the sample size is large relative to the dimension. Finally, by way of example we demonstrate that certain graphical techniques may prove useful in identifying the source of rejection for the multivariate extreme deviate test.