Using agency data for evidence-based programming: a university-agency collaboration

Agencies providing residential treatment are encouraged, or even mandated, to collect outcomes data and to implement evidence based practices, yet little guidance has been provided on how to do so using agency administrative data that are collected on an ongoing basis. We examined data on Child and Adolescent Functional Assessment Scale (CAFAS) scores for 1608 admissions to a residential treatment center from 2002 through 2008. CAFAS scores were measured every 90 days, providing multiple CAFAS scores for each individual. Results demonstrated that on average residents improved in functioning over time. Sensitive to the evolving needs of residents who had been entering the program, the treatment center made significant program changes in 2006 to attempt to better serve residents through a broad array of specialized programming. Compared to the overall results, the analysis suggested that residents who entered the program since October 2006 appeared to have made larger improvements in their CAFAS scores. Results were derived by employing multilevel models appropriate for estimating growth trajectories with repeated measures data. Conversations with agency staff suggested that using administrative data, and advanced statistical models, were extremely helpful for organizational decision making and evidence-based programming.     

Children and Families’ Involvement in Social Work Decision Making

This review summarises the research literature on children’s and parents’ involvement in social work decision making, which is regarded, in policy terms, as increasingly important. In practice, however, it tends to be messy, difficult and compromised. Different individuals or groups may have different understandings of participation and related concepts, while differences of age and disability also mediate effective user engagement. The literature highlights common themes in effective participatory practice with both children and their parents. Central to this are the establishment of relationships of trust and respect, clear communication and information and appropriate support to participate.     

The Subjectivity of Fairness: Managerial Discretion and Work–Life Balance

We use organizational justice theory to examine how perceptions of fairness affect the decision‐making process of line managers. In‐depth interviews were conducted with 35 Irish managers to explore how managers make organizational allocation decisions in cases where it is impractical to offer work–life balance accommodations to all employees. The findings suggest that firstly, managers construct the ‘life’ aspect of work–life balance within a heteronormative framework, where the emphasis is on caregiving and most usually parenting. Secondly, managers actively use their decision‐making powers around both formal and informal work–life balance supports to minimize injustice within their departments. By bringing together ideas about organizational justice and managerial decision‐making, we indicate how managers determine fairness through a decision‐making process narrowed by embedded gender role beliefs. Implications for future research and practice are discussed.     

Occupational Engagement and Academic Major Satisfaction: Vocational Identity's Mediating Role

This study examined vocational identity as a mediator of the relationship between occupational engagement (i.e., participation in a breadth of activities and interactions) and academic major satisfaction. Furthermore, the authors evaluated whether satisfaction with academic major related to academic success (i.e., grade point average). The mediational model was tested in a sample of undergraduate students (N = 215). Results indicated that occupational engagement significantly predicted academic major satisfaction and that vocational identity fully mediated that relationship. These findings support occupational engagement as an important contributor to adaptive career decision making and encourage research on occupational engagement as an intervention point for career counselors.     

论行政决策中的公众参与权

突破公众参与有效性瓶颈依赖于对公众参与权的依法确认、不断充实及有效保护。鉴于我国对公众参与权的研究比较迟缓、参与权制度发展仍然非常缓慢的现实困境,应当在准确界定公众参与权的性质、明确公众参与权的内容构成基础上,尽快构建起一系列具体的、可操作的法律制度,真正实现公众参与权的民主价值。     

“载道”的乌鸟——辞赋中的乌意象论略

由于地区和时代风俗的不同,人们对乌鸦的喜恶或有差异。但乌鸟意象作为中国文学中较为复杂的意象之一,却一直为文人墨客所喜爱。此意象不仅涵义丰富,而且在辞赋中又和其在诗词中有显著的区别。唐前,辞赋中的乌鸟是作者借以表达"出"、"处"生存观念的寄托,乌意象亦随辞赋作者表情达意的需要"出""处"儒道两家,其中《神乌傅》正反映了作者在"出"、"处"间的徘徊和抉择。有唐一代,乌意象的灵异祥瑞成为辞赋书写的重要内容。宋以降,辞赋中的乌鸟渐渐摆脱了其作为祥瑞之兆的使命,而被赋予了更多的儒家道德品性。此时的乌意象集忠、孝、仁等儒家大加称扬的道德于一身,堪称"奉行"儒家伦理道德的典范。而明代《孝乌赋》,凸显乌鸟意象的"孝"德,是彰扬乌意象孝行的典型作品。     

Considerations on jury size and composition using lower probabilities

The use of lower probabilities is considered for inferences in basic jury scenarios to study aspects of the size of juries and their composition if society consists of subpopulations. The use of lower probability seems natural in law, as it leads to robust inference in the sense of providing a defendant with the benefit of the doubt. The method presented in this paper focusses on how representative a jury is for the whole population, using a novel concept of a second ’imaginary’ jury together with exchangeability assumptions. It has the advantage that there is an explicit absence of any assumption with regard to guilt of a defendant. Although the concept of a jury in law is central in the presentation, the novel approach and the conclusions of this paper hold for representative decision making processes in many fields, and it also provides a new perspective to stratified sampling.     

Modeling Correlated Discrete Uncertainties in Event Trees with Copulas

Modeling the dependence between uncertainties in decision and risk analyses is an important part of the problem structuring process. We focus on situations where correlated uncertainties are discrete, and extend the concept of the copula‐based approach for modeling correlated continuous uncertainties to the representation of correlated discrete uncertainties. This approach reduces the required number of probability assessments significantly compared to approaches requiring direct estimates of conditional probabilities. It also allows the use of multiple dependence measures, including product moment correlation, rank order correlation and tail dependence, and parametric families of copulas such as normal copulas, t‐copulas, and Archimedean copulas. This approach can be extended to model the dependence between discrete and continuous uncertainties in the same event tree.     

Efficient Bayesian sampling plans for exponential distributions with type-I-censored samples

The aim of this paper is to introduce an efficient Bayesian sampling procedure for exponential distribution with type-I censoring. An online inspection method is suggested to reach a Bayes decision prior the termination time of life test. Bayesian sampling plans (BSPs) with quadratic loss function are established to illustrate the use of the proposed method. Some BSPs are tabulated, and the performance of the proposed BSPs is compared with two existing competitive methods. Numerical results indicate that a significant reduction in the experimental time over the conventional BSP can be achieved when the online inspection method is applied.     

The Role of Behavioral Responses in the Total Economic Consequences of Terrorist Attacks on U.S. Air Travel Targets

U.S. airports and airliners are prime terrorist targets. Not only do the facilities and equipment represent high‐value assets, but the fear and dread that is spread by such attacks can have tremendous effects on the U.S. economy. This article presents the methodology, data, and estimates of the macroeconomic impacts stemming from behavioral responses to a simulated terrorist attack on a U.S. airport and on a domestic airliner. The analysis is based on risk‐perception surveys of these two scenarios. The responses relate to reduced demand for airline travel, shifts to other modes, spending on nontravel items, and savings of potential travel expenditures by U.S. resident passengers considering flying domestic routes. We translate these responses to individual spending categories and feed these direct impact results into a computable general equilibrium (CGE) model of the U.S. economy to ascertain the indirect and total impacts on both the airline industry and the economy as a whole. Overall, the estimated impacts on GDP of both types of attacks exceed $10B. We find that the behavioral economic impacts are almost an order of magnitude higher than the ordinary business interruption impacts for the airliner attack and nearly two orders of magnitude higher for the airport attack. The results are robust to sensitivity tests on the travel behavior of U.S. residents in response to terrorism.