Institutional repositories in Canadian post‐secondary institutions
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine and provide an insight into Canadian post‐secondary institutional repositories (IRs) with respect to user interface features and knowledge organization systems (KOS) used. Design/methodology/approach The approach is to explore all Canadian post‐secondary institutions and their user interfaces to establish the type of searching and browsing features they have used and whether or not they have made use of KOS such as subject heading lists or classification schemes. Findings A directory of 27 IRs in Canada is created. Incorporation of KOS in institutional repository is evaluated. The examination is focuses on accessibility, searching, KOS use, and retrieval. Evaluation shows that few IRs have incorporated complex KOS such as controlled vocabularies. Browsing and searching options are available, but user interfaces are usually not modified to enhance information retrieval. Originality/value This is the first paper examining Canadian IRs from the perspectives of searching, browsing and the use of KOS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.015 | 0.038 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".