When it Works and Where it Fails: Spatial,Temporal, and Budgetary Constraints to Civic Environmentalism*

Objectives. With its focus on civic engagement, market‐based tools, and public‐private partnerships, the model of civic environmentalism has been successful in dealing with small, localized problems. Yet, a serious investigation of its use to deal with large‐scale, complex problems has not been undertaken. This article expands on the original model and applies it to the problem of the dead zone in the Gulf of Mexico. Methods. An exploratory case‐study framework is used to analyze the usefulness of this second‐generation model of environmental policy. Archival data sources, in the form of media reports, congressional hearings, case histories, and organizational websites, were used to develop the case study. Results. The case study demonstrated that polycentric governance, local‐level participation, civic leadership, and voluntary, incentive‐based programs were integral components of the model of civic environmentalism. However, in the case of the Gulf of Mexico's dead zone, the model's success is limited by spatial, budgetary, and temporal factors, as well as a lack of issue salience and minimal negative impacts on fishery resources. Conclusions. In the end analysis, civic environmentalism faces significant barriers when applied to large‐scale, complex environmental problems such as the Gulf of Mexico's dead zone. In this case, the Mississippi River/Gulf of Mexico Task Force will continue to have difficulties in generating a more successful implementation plan unless it broadens its base of support, develops the social capacity of its stakeholders, and resolves the debate over the science behind its action plan.     

Order selection in finite mixtures of linear regressions

Finite mixture models can adequately model population heterogeneity when this heterogeneity arises from a finite number of relatively homogeneous clusters. An example of such a situation is market segmentation. Order selection in mixture models, i.e. selecting the correct number of components, however, is a problem which has not been satisfactorily resolved. Existing simulation results in the literature do not completely agree with each other. Moreover, it appears that the performance of different selection methods is affected by the type of model and the parameter values. Furthermore, most existing results are based on simulations where the true generating model is identical to one of the models in the candidate set. In order to partly fill this gap we carried out a (relatively) large simulation study for finite mixture models of normal linear regressions. We included several types of model (mis)specification to study the robustness of 18 order selection methods. Furthermore, we compared the performance of these selection methods based on unpenalized and penalized estimates of the model parameters. The results indicate that order selection based on penalized estimates greatly improves the success rates of all order selection methods. The most successful methods were \(MDL2\) , \(MRC\) , \(MRC_k\) , \(ICL\) – \(BIC\) , \(ICL\) , \(CAIC\) , \(BIC\) and \(CLC\) but not one method was consistently good or best for all types of model (mis)specification.     

Generalized linear models and transformations for unreplicated factorial experiments in the presence of dispersion effects

For the analysis of replicated designs, many different methods have been suggested. These allow for the estimation of functional dependencies between mean and variance as well as possible dispersion effects within the same model framework. However, in the situation of unreplicated designs, most methods known so far rely on the assumption of constant variances, or a functional relationship between mean and variance as the only source of heteroscedasticity. In this paper, we propose two methods for dealing with unreplicated data, when dispersion effects might also be of importance. One of these is an extension of the Box–Cox-method [Box, G.E.P., Cox, D.R., 1964. An analysis of transformations. Journal of the Royal Statistical Society B 26, 211–252], the other is based on double generalized linear models. Both these methods turn out to yield approximately equivalent results in the case of comparable assumptions, whereas the double generalized linear model is the more general one and allows further extensions. If this class of models is assumed, consistency, asymptotic efficiency and normality of the resulting estimates are shown.     

Optimal two-level conjoint designs with constant attributes in the profile sets

We propose a simple strategy to construct D-, A-, G- and V-optimal two-level designs for rating-based conjoint studies with large numbers of attributes. In order to simplify the rating task, the designs hold one or more attributes at a constant level in each profile set. Our approach combines orthogonal designs and binary incomplete block designs with equal replication. The designs are variance-balanced meaning that they yield an equal amount of information on each of the part-worths.     

Researching Race: Identifying a Social Construction through Qualitative Methods and an Interactionist Perspective

Although much of the sociological community now views race as a social construction, empirical research does not always identify it in this way. Many practices of designating a research participant's race approach this process uncritically, implicitly framing race as uncomplicated. Although this is more common in survey‐based work, in this article I explore the tendencies and difficulties of studying race using qualitative methods. I discuss two prevalent but potentially problematic ways of “operationalizing” race in qualitative methodology, and then elaborate on the difficulties of identifying race in practice, using examples from my own ethnographic research. I suggest that symbolic interactionism provides a unique perspective from which to express race as socially situated, as long as this process is approached reflectively.     

Chronic Homelessness Among Working-Age Adults: Personal Problems and Public Assistance

As rapid changes have occurred in the economic and cultural structures of society, some have found themselves more disadvantaged than others. The mismatch between income and the cost of housing means that some of the poor will inevitably become homeless. Given the economics of the situation, prevention of homelessness is a non-issue; more germane is the question of chronic homelessness. This paper takes the position that determining who is most likely to be chronically homeless is related to the cultural ideology of individualism and, more specifically, that the situations likely to create the greatest vulnerability are problems for which individuals are seen as personally responsible. The distress brought about by societal-level changes is manifested in the “personal” problems of individuals. The social welfare system, acting as a substitute for failed social institutions, recreates their failures by relying on a cultural ethos that blames individuals for occupying positions to which the society has relegated them.     

Fortune,Risk, and Remittances: An Application of Option Theory to Participation in Village‐Based Migration Networks1

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An empirical analysis of stressors for gay men and lesbians

This research describes the empirical classification of stressors for gay men and lesbians. Volunteer respondents were recruited through a free local gay and lesbian newspaper, through gay and lesbian student organizations nationwide, through gay and lesbian bookstores nationwide, and at a gay festival in St. Louis. Nine hundred seventy-nine (979) participants completed a 70-item measure with stressors that had been identified in previous qualitative research. Participants were asked to indicate the degree to which they had experienced stress associated with a variety of experiences. Participants also completed a measure of dysphoria (CES-D), responded about their degree of openness regarding sexual orientation, and provided information about their relationship status and involvement with gay groups and activities. Using confirmatory factor analysis, a six-factor model was predicted to account for the data. One-factor, six-factor, and ten-factor models were tested. The ten-factor model yielded the best fit with the data and accounted for 63.5% of the variance. The factor structure remained stable when gay men were compared to lesbians, when those endorsing a predominantly gay versus exclusively gay orientation were compared, and when those in a relationship were compared to those who were not in a relationship. Increased gay stress was associated with more dysphoria. Implications of these findings are discussed and directions for future research are considered.