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Record W3095015631 · doi:10.5206/elip.v3i1.8575

An Exploration of Canadian LIS Programs

2020· article· en· W3095015631 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEmerging Library & Information Perspectives · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsWestern University
Fundersnot available
KeywordsLibrary scienceInclusion (mineral)Diversity (politics)Higher educationPolitical scienceEquity (law)SociologyPublic relationsComputer scienceSocial science

Abstract

fetched live from OpenAlex

It is well known that there is a lack of diverse professionals within the field of library and information science (LIS). As the entry point for future LIS professionals, university library programs are in a unique position to proactively address this issue. Websites serve as digital representations of Canadian LIS programs and are several programs’ main recruitment tool. This project adds to the growing body of Canadian focused data on diversity within LIS, and it is the first study to exclusively observe Canadian LIS higher learning institutions. Through a content analysis of Canadian LIS program websites, this project seeks to explore the following research questions: (1) How are Canadian LIS programs addressing issues like diversity, inclusion, and equity?; and (2) How do the LIS programs’ diversity initiatives relate to their recruitment of students? Emergent themes drawn from literature related to diversity efforts in higher education were analyzed alongside data collected from websites of LIS programs in order to frame the larger discussion of how issues like diversity, inclusion, and equity are addressed within higher learning institutions.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.234
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.283
Teacher spread0.239 · 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