Non-finite loss and challenges to communication between parents and professionals

Elizabeth Bruce PhD, a psychologist in private practice, and Cynthia Schultz PhD, honorary associate at LaTrobe University, both live and work in Australia. Their work on supporting parents who have children with special needs, however, has been published around the world. In this article Bruce and Schultz explore the notion of 'non-finite loss', defined as the ongoing sense of grief experienced by parents caring for children with severe disabilities. The authors discuss the issues that professionals need to consider when working with parents in these circumstances. The article closes with a set of recommendations for promoting more effective partnerships between parents and professionals.     

Book reviews

Association of Research Libraries     

Untangling the jungle of e-journal access issues using CRM software

Librarians have been struggling for years with the variety of issues arising while troubleshooting access to electronic journals. This article outlines the advantages and disadvantages of using a Customer Relations Management (CRM) software, originally designed for a call center, to communicate with patrons and track access issues. Utilizing the e-mail software used by the Reference Department at the University of South Florida, we assign incidents, correspond with patrons and staff, write internal notes, maintain transactions, and pull statistics. Hopefully, library vendors will develop software oriented to the needs of libraries to assist in managing access problems for e-journals.     

Paving Consensus: Enacting, Challenging, and Revising the Consensus Process in a Cohousing Community

This study focused on a cohousing community's use of consensus to make a decision about surfacing a parking area. It revealed that the community's use of consensus decision making allowed the residents to balance three goals: making an appropriate decision, meeting members' needs, and maintaining the community's well-being. Reaching agreement, however, was complicated by members' value differences and discontinuity in their participation. The analysis of this case reveals three qualities characteristic of the enactment of consensus: the role of structured communication within and between group meetings, a tension between maintaining process openness and reaching decision closure, and the expectation that group members will work within the consensus process. The analysis also highlights the importance of timing in the interpretation of conflict in a consensus-oriented group and the role of process change when a group reaches the limits of members' commitment to consensus.     

Analysis of Statistical Question Classification for Fact-Based Questions

Question classification systems play an important role in question answering systems and can be used in a wide range of other domains. The goal of question classification is to accurately assign labels to questions based on expected answer type. Most approaches in the past have relied on matching questions against hand-crafted rules. However, rules require laborious effort to create and often suffer from being too specific. Statistical question classification methods overcome these issues by employing machine learning techniques. We empirically show that a statistical approach is robust and achieves good performance on three diverse data sets with little or no hand tuning. Furthermore, we examine the role different syntactic and semantic features have on performance. We find that semantic features tend to increase performance more than purely syntactic features. Finally, we analyze common causes of misclassification error and provide insight into ways they may be overcome.     

Explaining Media Choice: The Role of Issue-Specific Engagement in Predicting Interest-Based and Partisan Selectivity

This study analyzes the predictors of 2 types of media selectivity: interest-based (i.e., choice of entertainment over politics) and partisan (i.e., choice of pro-attitudinal over counter-attitudinal or balanced news). Relying on a large survey-based experiment, we find that issue-specific engagement variables, including perceived issue understanding, issue importance, and issue attitude strength, predict interest-based and partisan selectivity above and beyond the influence of general political knowledge, news interest, and strength of political leanings. These results show that the drivers of selectivity are more complex than general political attributes; rather, they are contextual and reflect people’s engagement with particular issues.