Accessibility in Collection Development in Academic Libraries in Manitoba, Nova Scotia, and Ontario
Bibliographic record
Abstract
Accessibility in collection development policies (CDPs) and practice in Canada is understudied. Two studies focusing on academic libraries in provinces with accessibility legislation were done to investigate both policy and practice. The first study employed a content analysis of publicly available CDPs of academic libraries in Manitoba, Nova Scotia, and Ontario to determine if accessibility was explicitly mentioned in them. The study aimed to explore possible legislative influence in the wording of CDPs. Since CDPs show only part of the picture as to how selectors make their acquisition decisions, in the second study, a multiple-choice and short answer survey was administered to selectors at academic libraries in these three provinces, in order to discover the factors that influence selectors in deciding if and how they use accessibility as a selection criterion. This article presents the research undertaken and sheds new light on how accessibility functions in collection development in the Canadian academic library context.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.013 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".