社会工作质性评估研究的回顾(1990-2003)对中国社会工作的启示

在社会科学的历史中,定量和定性研究的争论持续了差不多半个世纪。随着研究者对实证主义的质疑,质性研究的数目逐渐增加。根据布瑞曼(Bryman,1988)的看法,质性研究有以下特点:(1)透过被访者的眼睛看世界;(2)描述日常生活情境的细节;(3)了解在不同社会范畴的背景中的行为及意义;(4)强调过程;(5)倾向采用文字及结构灵活的研究设计;(6)尽量避免在研究初期确立理论和观念。邓泽和林肯(Denzin & Lincoln,1998)也指出,质性研究有以下元素:(1)采用多元的研究手法;(2)涉及自然和诠译的角度;(3)在自然的情况下作出研究;(4)尝试理解和分析不同现象的…     

大学竞争力的内涵、指标与构筑

竞争力是大学获得相对优势并在竞争中生存与发展的关键。可以从价值取向与发展定位的角度来理解大学竞争力的内涵。大学竞争力是一个由制度与机制要素、文化与精神要素、物质与财力要素、学科与管理要素有机组合而成的复杂系统。其评价指标由社会竞争力、学科竞争力、服务竞争力、国际竞争力、资源效率竞争力等综合而成。应从主体与客体两方面构筑与提升大学竞争力。     

A classification approach based on the outranking model for multiple criteria ABC analysis

The multiple criteria ABC analysis is widely used in inventory management, and it can help organizations to assign inventory items into different classes with respect to several evaluation criteria. Many approaches have been proposed in the literature for addressing such a problem. However, most of these approaches are fully compensatory in multiple criteria aggregation. This means that an item scoring badly on one or more key criteria could be placed in good classes because these bad performances could be compensated by other criteria. Thus, it is necessary to consider the non-compensation in the multiple criteria ABC analysis. To the best of our knowledge, the ABC classification problem with non-compensation among criteria has not been studied sufficiently. We thus propose a new classification approach based on the outranking model to cope with such a problem in this paper. However, the relational nature of the outranking model makes the search for the optimal classification solution a complex combinatorial optimization problem. It is very time-consuming to solve such a problem using mathematical programming techniques when the inventory size is large. Therefore, we combine the clustering analysis and the simulated annealing algorithm to search for the optimal classification. The clustering analysis groups similar inventory items together and builds up the hierarchy of clusters of items. The simulated annealing algorithm searches for the optimal classification on different levels of the hierarchy. The proposed approach is illustrated by a practical example from a Chinese manufacturer. Furthermore, we validate the performance of the approach through experimental investigation on a large set of artificially generated data at the end of the paper.     

Can Carbon Nanomaterials Improve CZTS Photovoltaic Devices? Evaluation of Performance and Impacts Using Integrated Life‐Cycle Assessment and Decision Analysis

In emergent photovoltaics, nanoscale materials hold promise for optimizing device characteristics; however, the related impacts remain uncertain, resulting in challenges to decisions on strategic investment in technology innovation. We integrate multi‐criteria decision analysis (MCDA) and life‐cycle assessment (LCA) results (LCA‐MCDA) as a method of incorporating values of a hypothetical federal acquisition manager into the assessment of risks and benefits of emerging photovoltaic materials. Specifically, we compare adoption of copper zinc tin sulfide (CZTS) devices with molybdenum back contacts to alternative devices employing graphite or graphene instead of molybdenum. LCA impact results are interpreted alongside benefits of substitution including cost reductions and performance improvements through application of multi‐attribute utility theory. To assess the role of uncertainty we apply Monte Carlo simulation and sensitivity analysis. We find that graphene or graphite back contacts outperform molybdenum under most scenarios and assumptions. The use of decision analysis clarifies potential advantages of adopting graphite as a back contact while emphasizing the importance of mitigating conventional impacts of graphene production processes if graphene is used in emerging CZTS devices. Our research further demonstrates that a combination of LCA and MCDA increases the usability of LCA in assessing product sustainability. In particular, this approach identifies the most influential assumptions and data gaps in the analysis and the areas in which either engineering controls or further data collection may be necessary.     

Identifying design criteria for urban system ‘last-mile’ solutions – a multi-stakeholder perspective

Abstract

This study presents a novel approach to design and evaluate ‘last-mile’ solutions – encompassing the social and economic perspectives of key stakeholders. While urban system initiatives have been implemented in practice, theoretical gaps remain at the operational design level. A theoretical framework is developed, based on design criteria identified from a critical synthesis of supply chain and operations management literature, and ‘operationalised’ using an in-depth case study demonstrating implementation of a Consumer Choice Portal-Package Consolidation Centre solution, within a densely populated urban geography. Findings suggest that there is a need to re-define the role of institutional actors beyond that of the traditional governance task, to one of being able to facilitate performance outcomes. Similarly, industrial efficiency dimensions need to be reorientated to include consumer participation, social considerations and multi-stakeholder service outcomes. Finally, implications for operations theory and practising managers in city logistics are highlighted, with suggested directions for future research.     

Topics on Dynamic Panel Data Models with Random Effects Using Semi-Parametric Bayesian Approach

A common assumption in fitting panel data models is normality of stochastic subject effects. This can be extremely restrictive, making vague most potential features of true distributions. The objective of this article is to propose a modeling strategy, from a semi-parametric Bayesian perspective, to specify a flexible distribution for the random effects in dynamic panel data models. This is addressed here by assuming the Dirichlet process mixture model to introduce Dirichlet process prior for the random-effects distribution. We address the role of initial conditions in dynamic processes, emphasizing on joint modeling of start-up and subsequent responses. We adopt Gibbs sampling techniques to approximate posterior estimates. These important topics are illustrated by a simulation study and also by testing hypothetical models in two empirical contexts drawn from economic studies. We use modified versions of information criteria to compare the fitted models.     

Inference after separated hypotheses testing: an empirical investigation for linear models

Model selection problems arise while constructing unbiased or asymptotically unbiased estimators of measures known as discrepancies to find the best model. Most of the usual criteria are based on goodness-of-fit and parsimony. They aim to maximize a transformed version of likelihood. For linear regression models with normally distributed error, the situation is less clear when two models are equivalent: are they close to or far from the unknown true model? In this work, based on stochastic simulation and parametric simulation, we study the results of Vuong's test, Cox's test, Akaike's information criterion, Bayesian information criterion, Kullback information criterion and bias corrected Kullback information criterion and the ability of these tests to discriminate between non-nested linear models.     

规范性与个体发展性:大学生人生价值观教育中的冲突与调适

大学生人生价值观教育中的规范性与个体发展性之间是辩证统一的关系.然而在现实教育的实践中,却存在着片面强调规范性,忽视个体发展性的倾向,从而导致了一些不良现象的产生.树立现代化德育理念,培养和塑造大学生人生价值观的主体意识,就是要将规范性与个体发展性之间的张力转化为锻造大学生正确人生价值观的合力.     

Bootstrap estimation and model selection for multivariate normal mixtures using parallel computing with graphics processing units

In applications of multivariate finite mixture models, estimating the number of unknown components is often difficult. We propose a bootstrap information criterion, whereby we calculate the expected log-likelihood at maximum a posteriori estimates for model selection. Accurate estimation using the bootstrap requires a large number of bootstrap replicates. We accelerate this computation by employing parallel processing with graphics processing units (GPUs) on the Compute Unified Device Architecture (CUDA) platform. We conducted a runtime comparison of CUDA algorithms between implementation on the GPU and that on a CPU. The results showed significant performance gains in the proposed CUDA algorithms over multithread CPUs.     

Exploring rigour in autoethnographic research

Abstract

The changing face of qualitative research has opened up discourses on the validity and rigour of research processes and products. A current debate is whether the criteria traditionally used to judge the rigour of quantitative research are appropriate to assess the academic integrity of qualitative research including autoethnography. The purpose of this article is to appraise views on the academic rigour, validity and scientific accountability of research in general and autoethnographic research in particular. The researcher reports on issues of rigour in conducting autoethnographic research from her own experience and that of published autoethnographic researchers. The issue of relevant appraisal criteria against which the research integrity and rigour of autoethnographic studies can be assessed is investigated. It is concluded that the academic rigour of autoethnographic studies should be established to enhance its credibility and value and that the criteria used need to be judiciously determined and applied.