Community-Based Design Research: Learning Across Generations and Strategic Transformations of Institutional Relations Toward Axiological Innovations

The socio-ecological challenges facing communities in the 21st century are building towards a critical conjuncture of history, culture, power, and profound inequity. Scholars working in the service of social transformation and improving the wellbeing of communities are calling for creative, deliberate, and consequential interventions. Tharp & O’Donnell (this issue) call for increased engagement between Cultural-Community Psychology and Cultural-Historical Activity Theory to lead this kind of call. Drawing from our experiences in community based design research, we argue for cultivating axiological innovations in research and interventions. We explore three examples including: critical historicity, inter-generational learning, and strategic transformations of institutional relations.     

A Comparison of the Effect of Two Computer-Based Counseling Interventions on the Career Decidedness of Adults

This article describes two computer-based career counseling interventions provided for adults who are auto workers in career transition. It was found that these workers can increase their level of career decidedness and make progress in their commitment to occupational choice through the use of a computer-based career counseling program. Supporting previous research, this study indicated that computer-plus-counselor intervention is more effective in this type of career counseling than the computer-only intervention.     

The Evolution of Organizations: Suggestions from Complexity Theory About the Interplay Between Natural Selection and Adaptation

There has been much debate in the managementliterature between neo-Darwinists (who believe in thenatural selection of populations of organizations) andadaptationists (who contend that changes in organization structure and behavior occur in response to theenvironment). The general thesis of neo-Darwinism isthat species are blindly selected for survival by theenvironment. The latest empirical support for the dominant neo-Darwinism perspective adopted bymost biologists is based primarily on the experimentsconducted by Salvador Luria who claims to haveconclusively demonstrated that genes mutate randomly.Recently, however, biologists have re-examined Luria sresearch methods and, after replications of hisexperiments, now question some aspects of the validityof his results. Moreover, there is now new researchwhich provides support for the earlier adaptationistposition, namely, the existence of evolutionary driversand directors existing within self-organizing systems.Of particular importance to the present study is the experimental indication thatself-organizing systems play a conscious role in theirown evolution. We propose that similar mechanisms orprocesses operate in organizational adaptation, thuspointing toward a theoretical modification ofneo-Darwinism that embraces both adaptation and naturalselection in a general, unified theory.     

Informal shelter providers: Low income households sheltering the homeless

Despite the important role they play in preventing homelessness, those who shelter people who can not afford housing of their own have been neglected by researchers. This study examines the characteristics of these low income informal shelter providers. While informal shelter providers were similar to a comparison group of low income households that did not shelter others, there were also significant differences between the two groups. Informal shelter providers were more much more likely to live in single family dwellings, they were more likely to be long-term residents of the community, they were more likely to have experienced homelessness themselves, and they devoted a disproportionate share of their incomes to housing.     

Approximability and exact resolution of the multidimensional binary vector assignment problem

In this paper we consider the multidimensional binary vector assignment problem. An input of this problem is defined by m disjoint multisets \(V^1, V^2, \ldots , V^m\), each composed of n binary vectors of size p. An output is a set of n disjoint m-tuples of vectors, where each m-tuple is obtained by picking one vector from each multiset \(V^i\). To each m-tuple we associate a p dimensional vector by applying the bit-wise AND operation on the m vectors of the tuple. The objective is to minimize the total number of zeros in these n vectors. We denote this problem by Open image in new window , and the restriction of this problem where every vector has at most c zeros by Open image in new window . Open image in new window was only known to be Open image in new window -hard, even for Open image in new window . We show that, assuming the unique games conjecture, it is Open image in new window -hard to Open image in new window -approximate Open image in new window for any fixed Open image in new window and Open image in new window . This result is tight as any solution is a Open image in new window -approximation. We also prove without assuming UGC that Open image in new window is Open image in new window -hard even for Open image in new window . Finally, we show that Open image in new window is polynomial-time solvable for fixed Open image in new window (which cannot be extended to Open image in new window ).     

Who Can Tell? Network Diversity,Within‐Industry Networks,and Opportunities to Share Job Information

This article examines opportunities to share job information. It adds to the growing body of research on information holders and complements existing research that explains what kinds of networks and network positions provide the greatest benefit to job seekers. Data from an exploratory study of entry‐level, white‐collar workers are used to relate opportunities to share information—defined to consist of both knowledge of a job opening and awareness of a potential applicant among one's network members—with information holders’ network composition. The data show that information holders with strong within‐industry networks have more opportunities to share information and do share more information. Information holders with diverse networks more often identify potential applicants for jobs and thus have more opportunities to share information. However, despite having more opportunities to do so, they do not share information more often than those with less diverse networks. These findings, combined with the growing literature on information holders, suggest that different aspects of network composition affect the flow of job information at different stages and thus by different mechanisms.     

Adaptive importance sampling in general mixture classes

In this paper, we propose an adaptive algorithm that iteratively updates both the weights and component parameters of a mixture importance sampling density so as to optimise the performance of importance sampling, as measured by an entropy criterion. The method, called M-PMC, is shown to be applicable to a wide class of importance sampling densities, which includes in particular mixtures of multivariate Student t distributions. The performance of the proposed scheme is studied on both artificial and real examples, highlighting in particular the benefit of a novel Rao-Blackwellisation device which can be easily incorporated in the updating scheme. This work has been supported by the Agence Nationale de la Recherche (ANR) through the 2006–2008 project ’ . Both last authors are grateful to the participants to the BIRS meeting on “Bioinformatics, Genetics and Stochastic Computation: Bridging the Gap”, Banff, for their comments on an earlier version of this paper. The last author also acknowledges an helpful discussion with Geoff McLachlan. The authors wish to thank both referees for their encouraging comments.     

An empirical Bayes procedure for the selection of Gaussian graphical models

A new methodology for model determination in decomposable graphical Gaussian models (Dawid and Lauritzen in Ann. Stat. 21(3), 1272?C1317, 1993) is developed. The Bayesian paradigm is used and, for each given graph, a hyper-inverse Wishart prior distribution on the covariance matrix is considered. This prior distribution depends on hyper-parameters. It is well-known that the models??s posterior distribution is sensitive to the specification of these hyper-parameters and no completely satisfactory method is registered. In order to avoid this problem, we suggest adopting an empirical Bayes strategy, that is a strategy for which the values of the hyper-parameters are determined using the data. Typically, the hyper-parameters are fixed to their maximum likelihood estimations. In order to calculate these maximum likelihood estimations, we suggest a Markov chain Monte Carlo version of the Stochastic Approximation EM algorithm. Moreover, we introduce a new sampling scheme in the space of graphs that improves the add and delete proposal of Armstrong et al. (Stat. Comput. 19(3), 303?C316, 2009). We illustrate the efficiency of this new scheme on simulated and real datasets.     

Union Membership and the Union Wage Gap in the UK

We consider the choice of union membership in the UK and its effect on the union/non‐union wage differential allowing for the endogeneity of the union choice. We include identifying variables not previously used and find that correcting for selectivity is important and has a large impact on the estimated differential. Moreover, union choice is itself affected by the wage gap.     

Informal Shelter Providers: Low Income Households Sheltering the Homeless

Despite the important role they play in preventing homelessness, those who shelter people who can not afford housing of their own have been neglected by researchers. This study examines the characteristics of these low income informal shelter providers. While informal shelter providers were similar to a comparison group of low income households that did not shelter others, there were also significant differences between the two groups. Informal shelter providers were more much more likely to live in single family dwellings, they were more likely to be long-term residents of the community, they were more likely to have experienced homelessness themselves, and they devoted a disproportionate share of their incomes to housing.