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Record W2999961755 · doi:10.5860/crl.81.1.122

Perceptions of Academic Librarians toward LGBTQ Information Needs: An Exploratory Study

2020· article· en· W2999961755 on OpenAlexafffund
John Siegel, Martin Morris, Gregg Stevens

Bibliographic record

VenueCollege & Research Libraries · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsMcGill University
FundersMcGill University
KeywordsLesbianSexual orientationTransgenderQueerExploratory researchPsychologyInformation needsPerceptionVulnerability (computing)Sexual identityHomosexualityVisibilitySocial psychologyPublic relationsSociologyHuman sexualityLibrary scienceComputer sciencePolitical scienceGender studiesSocial science

Abstract

fetched live from OpenAlex

While previous studies have examined lesbian, gay, bisexual, transgender, and queer (LGBTQ) information needs, none have addressed librarian confidence in addressing LGBTQ-themed information needs or the factors affecting this confidence. The authors used a mixed-methods survey to assess the knowledge and perspectives of academic librarians in responding to information inquiries related to sexual orientation and gender identity. Based on an exploratory factor analysis, three variables were identified: duty of care/vulnerability of inquirer, public visibility of work conducted, and personal biases and prejudices. These factors can reduce or otherwise influence the ability to meet LGBTQ information needs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.034
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0060.003
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.157
GPT teacher head0.383
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2020
Admission routes2
Has abstractyes

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