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.     

Disciplined freedom,branded authenticity,and dependable independence: how tensions enact flexibility in lifestyle blogging careers

Analyzing 219 blog posts from 52 self-employed women lifestyle bloggers in North America, this study shows how these digital professionals navigate tensions and communicatively constitute work flexibility. In their narratives, women bloggers employed tension management approaches such as reframing, continual connections, and reflective practice in response to tensions in enacting temporal–spatial, identity, and financial flexibility. Specifically, women followed oxymoronic constructions – disciplined freedom, branded authenticity, and dependable independence – to embrace and transform competing poles of fluidity?structure, authenticity?marketability, and independence?interconnection. Expanding work–life research to the self-employed digital labor context, this study responds to recent calls to uncover more-than tension management strategies in empirical settings and contributes to a tension-centered, contextual, and processual analysis of workplace flexibility construction.     

The impact of coworker support and stigma on breastfeeding after returning to work

This study assessed the impact of coworker support on lactating mothers’ breastfeeding self-efficacy after maternity leave. A cross-sectional survey of 1000 working adults assessed effects of perception of fairness, coworkers’ support for breastfeeding colleagues, and ick response on willingness to help mothers needing breaks to pump breastmilk at work. The study also examined how coworker support affected mothers’ self-efficacy to continue breastfeeding. One out of four coworkers showed moderate to strong stigma, saw breaks to pump breastmilk as unfair, and showed less intention to help new mothers. These results suggest that while the majority of coworkers are generally supportive, lactating women are likely to encounter disapproving coworkers who may discourage them from continuing to breastfeed. The data showed that the majority of organizations included in this study have only passively fostered mother-friendly workplaces and could do more to encourage employees to be supportive of lactating colleagues.     

A Model for Quantitatively Analyzing Representations of Social Class in Screen Media

Content analyses of prime-time television provide a picture of predominant cultural stereotypes and social trends. The present research is a quantitative content analysis of social class in popular broadcast and cable television in the United States. This research advances scholarship by systematically analyzing character class in addition to more commonly examined variables such as race and gender. A model for the operationalization of class for quantitative content analyses of mediated texts is offered. This proof of concept study demonstrates the viability of studying media representations of class quantitatively to systematically document patterns of portrayal.     

On the same page: Improving the connection between public services units in academic libraries

Communication quality between public service units in academic libraries can make the difference between mediocre and exceptional service. If units do not communicate well, patrons may receive inaccurate information and experience short-term frustration, leading to long-term damage to the library's reputation. Poor communication creates adverse effects on employees through decreased productivity, negative work culture, and low morale. This article explores the importance of quality communication through a review of the literature and a case study at one academic library. The authors share practical communication improvement strategies for libraries of every size and fiscal ability.     

Setting a Non-Agenda: Effects of a Perceived Lack of Problems in Recent News or Twitter

The mere perception that news has given certain problems more coverage can lead the audience to assume that those problems are more important. Given that the news media, at times, obsesses over relatively trivial matters, and given that the audience is increasingly able to filter media exposure, it is worth asking what happens when audience members perceive that recent media coverage has not emphasized any very important problems. In such cases, audience members might assume that any problems facing the nation must not be particularly important. We explicate this attitude of political complacency, test whether perceived media agendas lacking important problems can influence it, and explore whether complacency helps explain political disengagement. We also explore whether these effects generalize beyond news, to new media gatekeepers such as Twitter. Two experiments tested effects of a perceived absence of important problems in recent news or Twitter content. In the case of news, but not Twitter, this increased complacency in both studies. Study 2 added a no-exposure control and found that effects on complacency were driven by the cueing of nonproblem stories, not by the absence of problem story cues. Both studies validated complacency as a predictor of political disengagement.