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  • × author_ss:"Bullard, J."
  1. Bullard, J.; Dierking, A.; Grundner, A.: Centring LGBT2QIA+ subjects in knowledge organization systems (2020) 0.03 
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    Abstract
    This paper contains a report of two interdependent knowledge organization (KO) projects for an LGBT2QIA+ library. The authors, in the context of volunteer library work for an independent library, redesigned the classification system and subject cataloguing guidelines to centre LGBT2QIA+ subjects. We discuss the priorities of creating and maintaining knowledge organization systems for a historically marginalized community and address the challenge that queer subjectivity poses to the goals of KO. The classification system features a focus on identity and physically reorganizes the library space in a way that accounts for the multiple and overlapping labels that constitute the currently articulated boundaries of this community. The subject heading system focuses on making visible topics and elements of identity made invisible by universal systems and by the newly implemented classification system. We discuss how this project may inform KO for other marginalized subjects, particularly through process and documentation that prioritizes transparency and the acceptance of an unfinished endpoint for queer KO.
    Date
    6.10.2020 21:22:33
    Source
    Knowledge organization. 47(2020) no.5, S.393-403
  2. Lee, T.; Dupont, S.; Bullard, J.: Comparing the cataloguing of indigenous scholarships : first steps and finding (2021) 0.02 
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    Abstract
    This paper provides an analysis of data collected on the continued prevalence of outdated, marginalizing terms in contemporary cataloguing practices, stemming from the Library of Congress Subject Heading term "Indians" and all its related terms. Using Manitoba Archival Information Network's (MAIN) list of current LCSH and recommended alternatives as a foundation, we built a dataset from titles published in the last five years. We show a wide distribution of LCSH used to catalogue fiction and non-fiction, with outdated but recognized terms like "Indians of North America-History" appearing the most frequently and ambiguous and offensive terms like "Indian gays" appearing throughout the dataset. We discuss two primary problems with the continued use of current LCSH terms: their ambiguity limits the effectiveness of an institution's catalog, and they do not reflect the way Indigenous Peoples, Nations, and communities in North America prefer to represent themselves as individuals and collectives. These findings support those of parallel scholarship on knowl­edge organization practices for works on Indigenous topics and provide a foundation for further work.
    Content
    Beitrag innerhalb von: Best papers from the 2021 NASKO Conference: Resilience, Resistance and Reflection: Knowledge Organization at a Crossroads. Vgl.: doi.org/10.5771/0943-7444-2021-4-298.
    Source
    Knowledge organization. 48(2021) no.4, S.298-306
  3. Bullard, J.: Curated Folksonomies : three implementations of structure through human judgment (2018) 0.01 
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    Abstract
    Traditional knowledge organization approaches struggle to make large user-generated collections navigable, especially when these collections are quickly growing, in which currency is of particular concern, for which professional classification design is too costly. Many of these collections use folksonomies for labelling and organization as a low-cost but flawed knowledge organization approach. While several computational approaches offer ways to ameliorate the worst flaws of folksonomies, some user-generated collections have implemented a human judgment-centered alternative to produce structured folksonomies. An analysis of three such implementations reveals design differences within the space. This approach, termed "curated folksonomy," presents a new object of study for knowledge organization and represents one answer to the tension between scalability and the value of human judgment.
    Source
    Knowledge organization. 45(2018) no.8, S.643-652
  4. Howison, J.; Bullard, J.: Software in the scientific literature : problems with seeing, finding, and using software mentioned in the biology literature (2016) 0.00 
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    Abstract
    Recognizing negative and speculative information is highly relevant for sentiment analysis. This paper presents a machine-learning approach to automatically detect this kind of information in the review domain. The resulting system works in two steps: in the first pass, negation/speculation cues are identified, and in the second phase the full scope of these cues is determined. The system is trained and evaluated on the Simon Fraser University Review corpus, which is extensively used in opinion mining. The results show how the proposed method outstrips the baseline by as much as roughly 20% in the negation cue detection and around 13% in the scope recognition, both in terms of F1. In speculation, the performance obtained in the cue prediction phase is close to that obtained by a human rater carrying out the same task. In the scope detection, the results are also promising and represent a substantial improvement on the baseline (up by roughly 10%). A detailed error analysis is also provided. The extrinsic evaluation shows that the correct identification of cues and scopes is vital for the task of sentiment analysis.
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.9, S.2137-2155
  5. Bullard, J.; Howison, J.: Learning from Elitist Jerks : creating high-quality knowledge resources from ongoing conversations (2015) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2267-2276

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