Bakhtin Applied: Employing Dialogism to Analyze the Interplay of the Ideologies of Individualism and Community Within the Discourse of Alcoholics Anonymous

An ongoing debate regarding the nature of therapeutic communities concerns the extent to which these communities reinforce the ideologies of individualism and community. This article engages this discussion through a process of social text analysis informed by the dialogism theory of Russian philosopher and literary scholar Mikhail Bakhtin. Dialogism seeks to understand the multiple voices interpenetrating particular utterances, revealing an emergent social construction of meaning. Applying this approach to examples of discourse from a prominent therapeutic community, Alcoholics Anonymous, illustrates how meaning in the discourse of this movement can be understood to emerge among the interplay between the ideologies of individualism and community as expressed within the movement's narrative practice.     

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.     

Measuring Cultural Dimensions of Classroom Interactions

We trace the development and analyze the generalizability of the Classroom Assessment of Sociocultural Interactions (CASI), an observation system designed to measure cultural dimensions of classroom interactions. We establish CASI measurement properties by analyzing panoramic videos of 4th and 5th grade classrooms from the Measures of Effective Teaching project, and argue for its significance in terms of achievement opportunity for minoritized students and needed evidence regarding equitable teaching. We frame ten dimensions of sociocultural interactions within three domains: Life Applications (i.e., connections with what students know and do outside of school); Self in Group (i.e., interdependence to motivate learning and foster social identities); and Agency (i.e., how freedom and choice are managed).

We demonstrate how measurement error is associated with raters, lessons, and lesson segments, and discuss implications for CASI refinement, as well as appropriate instrument uses to enrich learning opportunities for minoritized students across a variety of classroom settings.     

Crowdfunding for Academic Libraries: Indiana Jones Meets Polka

Crowdfunding – or creatively presenting a case for funding to like-minded individuals – is becoming an effective development strategy for academic libraries. The crowdfunding projects described offer multiple approaches to consider, from an adventure-themed video to embracing polka music to entice donors to give. Social media, used in conjunction with the web and well-established email communication formed the basis of successful project promotion. Developing a robust communication plan ahead of campaign launch is critical for success. Thanking donors for their transformational gifts and follow up communication describing the impact of their participation six months later raises friends for the library potentially for many years to come. With proper planning, an active and enthusiastic committee and effective donor stewardship, crowdfunding campaigns will help libraries raise funds to support strategic initiatives.     

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.     

Spatial Discovery of Linked Research Datasets and Documents at a Spatially Enabled Research Library

Current publishing practices in academia tend to result in datasets that are difficult to discover. This is because datasets are not well-integrated across academic domains and they are often not linked to the documents that reference them. For these reasons, discovering datasets across domains can be challenging; for example, discovering archeological observations and biological specimens using the same search is not widely supported, even if both datasets share a similar spatial extent, like Mesoamerica. It is also challenging to retrieve relevant documents that reference datasets; for example, retrieving a series of field reports that reference archeological observations is typically not supported. Our work develops an extensible method for: (1) geographically integrating collections across disciplinary repositories and (2) connecting datasets to related documents. We describe a collection of spatially-referenced researcher datasets, capturing their metadata elements and encoding them as linked open data. We then leverage existing library services to formalize links from datasets to documents. The system described in this work has been deployed, resulting in an experimental open data site for the UCSB campus. Results indicate that this system can be scaled-up with support from an institutional repository in the near future.