Who's next? Research predicts museum leadership gap

A brief commentary from the Museum Association of New York (MANY) on the unprecedented gap posed by baby-boomer retirement. Based, in part, on MANY's white paper, “Who's Next? Questioning the Future of Museum Leadership in New York State,” this essay deals with questions of succession, leadership and general differences in New York's museum community.     

Effects of Mass and Interpersonal Communication on Breast Cancer Screening: Advancing Agenda-Setting Theory in Health Contexts

Drawing on components of agenda-setting theory and the two-step flow of information from mass media to news audiences, this study examines the effects of mass and interpersonal communication on breast cancer screening practices among college- and middle-aged women (n = 284). We theorized that screening behaviors among younger women would be influenced more by interpersonal sources of information while screening among middle-aged women would be more influenced by exposure to mass-mediated information. Findings supported anticipated patterns, revealing important and varying roles for both mass and interpersonal communication in the health behaviors of women. Implications for health practitioners and campaign planners, as well as recommendations for future research, are discussed.     

Editorial

This issue of the Journal contains three interesting articlesabout central aspects of public opinion research, as well asan equal number of research notes that reflect the range oftopics that interest all public opinion researchers. Toshio Takeshita takes a turn at reconceptualizing agenda-settingstudies, using a taxonomy     

Organizational Power and the Institutional Review Board

In this essay, we respond to the narratives and essays in this issue by examining organizational power issues related to researchers and institutional research boards (IRBs). Rather than taking a singular perspective on power, we use multiple perspectives and suggest that the cumulative analyses provide the best understanding of IRBs and organizational power.     

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.     

Relational turbulence and perceptions of partner support during reintegration after military deployment

The transition from deployment to reintegration can be stressful for returning military personnel and at-home partners, and support plays a key role in their ability to transition effectively. We draw on relational turbulence theory to advance predictions about how parameters of the relationship between returning service members and at-home partners predict their perceptions of their partner’s support during the post-deployment transition. We surveyed 235 individuals (117 returning service members, 118 at-home partners) who had experienced the transition within the past 6 months. Findings consistent with the theory indicated that relational turbulence partially mediated the negative associations that relational uncertainty and interference from a partner shared with partner support. Partner uncertainty was a direct negative predictor of partner support as well. We consider how these results extend theory, research, and practice.