Validating the Willingness to Self-Censor Scale: Individual Differences in the Effect of the Climate of Opinion on Opinion Expression

Hayes, Glynn, and Shanahan (2005) defined self-censorship asthe withholding of one’s opinion around an audience perceivedto disagree with that opinion. They argued that people differin their willingness to self-censor and introduced an 8-itemself-report instrument, the Willingness to Self-Censor scale,to measure this individual difference. The results of an experimentalstudy presented here provide further evidence of the constructvalidity of the scale. Each participant in the study was presentedwith a hypothetical scenario that contained information suggestinga group of people the participant was conversing with abouta controversial topic held opinions that were either uniformlysimilar to or different from the participant’s own opinion.Four weeks prior, each participant had responded to the Willingnessto Self-Censor scale and a measure of dispositional shyness.As expected, the manipulation of the climate of opinion affectedwillingness to express an opinion to the group, but more soamong those who scored relatively high on the Willingness toSelf-Censor scale. These results support the notion that somepeople rely on information about the climate of opinion moreso than do others when they decide whether or not to voice theiropinion publicly, and they suggest that the Willingness to Self-Censorscale measures this individual difference.     

State of the art of expert searching: results of a Medical Library Association survey.

OBJECTIVES: Medical Library Association (MLA) members were surveyed to gather background about the current state of expert searching in institutions. The survey results were intended to guide the recommendations of the Task Force on Expert Searching for promoting the importance of expert searching and implementing those recommendations. METHODS: MLA members were surveyed, and data obtained from the survey were compiled and analyzed to answer three general questions: what is the perceived value of searching skills to the institution, how do health sciences librarians maintain and improve their searching skills, and how are searching services promoted and/or mandated in the institution. RESULTS: There were 256 responses to the survey. Over 95% of the respondents saw their expert-searching skills were of value to their institutions, primarily through performing mediated searches and search consultations. Over 83% of the respondents believed that their searching skills had improved over the past 10 years. Most indicated that continued training was very important in maintaining and improving their skills. Respondents promoted searching services most frequently through orientations, brochures, and the libraries' Web pages. No respondent's institution mandated expert searching. Less than 2% of respondents' institutions had best practice guidelines related to expert searching, and only about 8% had guidelines or policies that identified situations where expert searching was recommended. CONCLUSIONS: The survey supports the belief that health sciences librarians still play a valuable role in searching, particularly in answering questions about treatment options and in providing education. It also highlights the need for more expert searching courses. There has been minimal discussion about the perceived need for expert-searching guidelines in the institutions represented by survey respondents.     

Consolidation of Black-dyed Māori Textile Artefacts: Evaluating the Efficacy of Sodium Alginate

Black-dyed artefacts are found in museums worldwide, many produced using an iron-tannate compound. Deterioration of iron-tannate dyed artefacts is an international preservation issue: in New Zealand the deterioration of paru (iron-tannate) dyed Māori textiles is widespread. This article reports experimental work testing the efficacy of sodium alginate, a consolidant developed for deteriorated paru-dyed muka (fibre from harakeke; Phormium tenax). The colour stability, strength retention, and acidity of paru-dyed muka consolidated with sodium alginate (0.25, 0.5, and 1% w/v in water) was tested pre- and post-artificial light ageing. This study found that sodium alginate had no negative effect on paru-dyed muka and in some cases provided benefit. Interestingly, the colour of paru-dyed muka is substantially more stable in UV-filtered light than previously recognised. Also microfading results were in agreement with visual assessments of colour change at 1 Mlux hour exposure, providing confidence in this relatively new technique to assess colour change.     

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.     

Google Scholar's Coverage of the Engineering Literature 10 years Later

In 2008 Meier and Conkling first tested Google Scholar's coverage of the engineering literature against citations gathered from the Compendex database. Since that time, other studies have used the same methodology and found improvement in Google Scholar's coverage. This study uses engineering dissertations from Proquest Dissertations & Theses to create a data set of citations for the comparison of fee-based databases, Compendex and Scopus, against Google Scholar. From 1950 to 2017 Google Scholar outperformed both Compendex and Scopus in discoverability of citations in nine engineering subjects. These results have implications for collection management and information literacy program planning for librarians.     

The Professional Career and Life of Valerie Bross

ABSTRACT

The career path and significant professional accomplishments of librarian Valerie Bross (1954–2016) are described in this article. The awards and recognition she received are recounted and the influence of outside activities on her career is assessed. An attempt is made to capture what she was like as a professional, as well as what her unique characteristics were. A bibliography of her writings and a photograph are included.     

Why Users Share the News: A Theory of Reasoned Action-Based Study on the Antecedents of News-Sharing Behavior

Social media have become an integral part of online news use, affecting how individuals find, consume, and share news. By applying the Theory of Reasoned Action (TRA), this study investigates the effects of motives, attitude, and intention on news-sharing behavior among German social media users (n = 333). Findings show that news-sharing attitude and subjective norms have a positive effect on news-sharing intention, which in turn has a positive effect on actual news-sharing behavior. Taken together, we see that a new media behavior in the early phases of its societal diffusion—like social media news sharing in Germany in 2015—can mainly be explained by a rational choice logic and is rooted in the motives of socializing and information seeking. This finding thus reflects the double nature of social media as a means for both information retrieval and social grooming.     

Online Celebrity Bashing: Wrecking Ball or Good for You? Adolescent Girls’ Attitudes Toward the Media and Public Bashing of Miley Cyrus and Selena Gomez

Journalists and readers of celebrity news regularly bash celebrities online, a behavior that is easily accepted among adolescents. This study investigates whether these attitudes of acceptance differ according to the perpetrator of the bashing (media versus public) and the likeability of the involved celebrity (liked versus disliked). Using a vignette study, we examine adolescent girls’ attitudes toward media (journalists’) and public (readers’) bashing of a generally disliked celebrity (Miley Cyrus) and a generally liked celebrity (Selena Gomez). All participants read an identical negative news story (media bashing) and two related negative reader comments (public bashing). Participants were randomly assigned to read this information about either Miley Cyrus or Selena Gomez. Results of a mixed-design ANOVA showed that the girls had less negative attitudes toward media bashing compared with public bashing. Moreover, they more easily accepted the bashing of a disliked celebrity than the bashing of a liked celebrity.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.