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.     

Another Look at What Moves Public Opinion: Media Agenda Setting and Polls in the 2000 U.S. Election

This study examined two levels of media agenda effects on aggregatepublic opinion from different news sources. The effects wereinvestigated immediately and cumulatively. Content analysisdata from the 2000 U.S. presidential election coverage by fournational news organizations were related to the Gallup pre-electionpoll standings of each candidate. Regression analyses foundthat both the salience of a candidate and the salience of theattributes of a candidate cumulatively, but not immediately,influenced his standing in the polls. An analysis of news sourcessupported the finding that the two levels of agenda-settingeffects seemed mostly cumulative rather than immediate. Newsfrom different sources, however, tended to have effects of differentdegrees and sometimes different directions on candidate pollstandings. Cumulative effects of candidate salience on aggregateopinion change were found for non-partisan and neutral newssources—reporters, poll reporting and public documents—whereasthe effects of candidate attribute salience mostly came frompartisan sources—the candidate himself and members ofthe competing political party. Possible political implicationsof these findings 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.