Equitable public library services for Canadians with print disabilities
Bibliographic record
Abstract
Purpose CELA, the Centre for Equitable Library Access, is a national not-for-profit organization whose mission is to support public libraries in providing accessible collections for Canadians with print disabilities and to champion the fundamental right of Canadians with print disabilities to access media and reading materials in the format of their choice. This paper aims to examine the history of the organization, the events that led to its creation, the issues with which it has and continues to struggle with – political, technological, structural – and the successes it has enjoyed. Design/methodology/approach This is a case study intended shine light on the development of a service sorely lacking in Canadian public libraries – consistent and sustainable publicly funded access to reading materials for Canadians with print disabilities – by providing related history and context and outlining current and future offerings. Findings The decision to centralize a service that most public libraries struggled to deliver within their own capacities was wise and has greatly benefited Canadians with print disabilities. Originality/value This paper provides a profile in determination, collaboration and the value of inclusivity in public libraries.
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 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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".