Environmental Influences on Well-Being: A Dyadic Latent Panel Analysis of Spousal Similarity

This article uses dyadic latent panel analysis (DLPA) to examine environmental influences on well-being. DLPA requires longitudinal dyadic data. It decomposes the observed variance of both members of a dyad into a trait, state, and an error component. Furthermore, state variance is decomposed into initial and new state variance. Total observed similarity between members of a dyad is decomposed into trait similarity, initial state similarity, new state similarity, and error similarity. Dyadic similarity in new state variance reveals that both members of a dyad change in the same direction, which is a strong indication of environmental effects. DLPA is used to examine environmental influences on life satisfaction and domain satisfaction based on 22 annual assessments of married couples in the German Socio-Economic Panel Study (N’s = 607–740). The results show high similarity in new state variance for life satisfaction and objectively identical domains (household income, housing), and less similarity for objectively less similar domains (recreation, health). This finding provides strong evidence for environmental influences on well-being. In addition, the results show high trait similarity. The implications of the latter finding for interpretation of behavioral genetics studies of well-being are discussed.     

Social Enterprise Among University-Based Centers in US Schools of Social Work

Globally, social enterprise is used increasingly by nonprofit organizations to create new funding streams in the face of dwindling public funds. In light of evidence that institutions of higher education are making similar adaptations, this study explores the extent to which academic centers in US schools of social work are using social enterprise strategies to fund mission efforts. Interviews with the directors of 16 social work research centers in 14 states reveal incentives and barriers that exist at multiple levels and considerably impact the potential viability of social enterprise in the social work academic setting. Implications for institutions of higher education and social work scholars are discussed.     

Trust,Social Capital,and the Coordination of Relationships Between the Members of Cooperatives: A Comparison Between Member-Focused Cooperatives and Third-Party-Focused Cooperatives

In recent years, nonprofit scholars have increasingly studied the phenomenon of social enterprises which has become a generic term describing a wider reorientation among third sector organizations. The emergence of social enterprises has also led to a dynamic of hybridization and broadening in the cooperative sector, similar to an earlier dynamic of “economization”, but this time on the other end of the organizational spectrum. This paper aims at developing a fine-grained conceptual understanding of how this organizational dynamic is shaped in terms of member coordination, thus contributing to a more comprehensive theoretical understanding of different organizational forms of cooperatives. Specifically, to highlight the difference to traditional member-focused cooperatives, the paper introduces the term third-party-focused cooperatives for those social enterprises which emphasize economic goals as well as control and ownership by a particular community (typically place-based). The key result of the paper is that with the shift from member- to community-focus in cooperatives, the main coordination mechanism becomes one of norm-based trust on the basis of generalized reciprocity. In contrast to traditional maxim-based trust member coordination on the basis of relation-specific reciprocity, this enables third-party-focused cooperatives to mobilize bridging and linking social capital, facilitating collective action aimed towards the community interest. The findings suggest that this identity shift requires a mutual re-positioning between the cooperative and the nonprofit sector, in terms of umbrellas as well as regulatory and legislative bodies.     

A UNIVERSITY EXAMINATION-SCHEDULING MODEL TO MINIMIZE MULTIPLE-EXAMINATION DAYS FOR STUDENTS

Scheduling university examinations is often done with the objective of spreading a student's required examinations over an examination week. That is the equivalent of the problem of minimizing the number of examinations a student must take on any one day. An approach to scheduling exams which relates the problem to the classical assignment problem is discussed. The model developed is a symmetry-constrained assignment model, and the solution method requires use of a branch-and-bound algorithm. Results from application of the algorithm to six semesters of actual data are presented.     

Concepts,Theory, and Techniques PRINCIPLES OF MULTIOBJECTIVE OPTIMIZATION*

This paper attempts to isolate and analyze the principal ideas of multiobjective optimization. We do this without casting aspersions on single-objective optimization or championing any one multiobjective technique. We examine each fundamental idea for strengths and weaknesses and subject two—efficiency and utility—to extended consideration. Some general recommendations are made in light of this analysis. Besides the simple advice to retain single-objective optimization as a possible approach, we suggest that three broad classes of multiobjective techniques are very promising in terms of reliably, and believably, achieving a most preferred solution. These are: (1) partial generation of the efficient set, a rubric we use to unify a wide spectrum of both interactive and analytic methods; (2) explicit utility maximization, a much-overlooked approach combining multiattribute decision theory and mathematical programming; and (3) interactive implicit utility maximization, the popular class of methods introduced by Geoffrion, Dyer, and Feinberg [24] and extended significantly by others.     

Improving outcomes for children in out‐of‐home care: the role of therapeutic foster care

How best to support children and young people in foster care remains a challenge for child welfare. There has been little Australian research on the outcomes for children and young people placed in therapeutic foster care (TFC). This article aims to address this knowledge gap, presenting the evaluation of a state‐wide model of TFC known as the Circle Program operating in Victoria, Australia. Data sources for the study were case assessment analysis; surveys of foster carers, program workers and other stakeholders in the sector; and both focus groups and individual interviews with foster care workers. The evaluation found that the Circle Program lessened the number of unplanned exits of children from foster placements compared with generalist foster care. Another important finding was that the Circle Program positively influenced foster carers' decisions to stay in the carer role. Key components perceived as contributing to outcomes of the Circle Program included enhanced training of foster carers, intensive carer support, specialist therapeutic support to the child and carer, therapeutic service to family members and a network of services to provide support to the child.     

Doing Good and Selling Goods

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This paper explores a network of organizations and their perspectives on the social enterprise commodity. Based on...     

A Bayesian mixture of experts approach to covariate misclassification

This article considers misclassification of categorical covariates in the context of regression analysis; if unaccounted for, such errors usually result in mis-estimation of model parameters. With the presence of additional covariates, we exploit the fact that explicitly modelling non-differential misclassification with respect to the response leads to a mixture regression representation. Under the framework of mixture of experts, we enable the reclassification probabilities to vary with other covariates, a situation commonly caused by misclassification that is differential on certain covariates and/or by dependence between the misclassified and additional covariates. Using Bayesian inference, the mixture approach combines learning from data with external information on the magnitude of errors when it is available. In addition to proving the theoretical identifiability of the mixture of experts approach, we study the amount of efficiency loss resulting from covariate misclassification and the usefulness of external information in mitigating such loss. The method is applied to adjust for misclassification on self-reported cocaine use in the Longitudinal Studies of HIV-Associated Lung Infections and Complications.     

A Multilevel Analysis of Hispanic Youth,Exposure to the United States,and Retail Theft

Panel data in the National Longitudinal Survey of Youth (NLSY97) provide an excellent opportunity to examine the relationship between Hispanic immigration, assimilation, and retail theft. This study examines the relationship between length of time Hispanic youth have spent in America, with the probability of stealing from a store. After controlling for traditional predictors of crime that are correlated with adolescence and immigrant status, random effects logistic regression models indicate that immigrants are less likely to steal than non-immigrants. However, calculating the marginal effects of time spent in the United States reveals that their probability increases with assimilation. Supplementary analyses specify that Hispanic youth who enter the United States within their first 5 years of age will have higher odds of engaging in retail theft. Supportive parenting and a structured home environment is a consistent protective factor in the models. Policies targeting pro-family and social identification are likely to benefit immigrant youth as they acculturate to America.