Open access and evolving scholarly communication: An overview of library advocacy and commitment, institutional repositories, and publishing in Canada
Bibliographic record
Abstract
The open access movement in Canada is very active in many areas. This is not surprising; of the 16 people at the Budapest meeting which was the foundation of the Budapest Open Access Initiative (BOAI), three were Canadians, all global leaders in this arena: Leslie Chan, Jean-Claude Guédon, and Stevan Harnad. The Canadian Association of Research Libraries (CARL) was among the earliest signatories of the BOAI, and quickly initiated a nationwide institutional repository program. The Canadian Library Association (CLA) recently approved an innovative “Position Statement on Open Access for Canadian Libraries,” calling for all libraries to participate in advocacy, educating patrons abut open access resources, and encouraging support for open access, including economic support. The Canadian Institutes of Health Research (CIHR) has an open access mandate policy, requiring open access to CIHR-funded research within six months. The Social Sciences and Humanities Research Council (SSHRC) has an Aid to Open Access Journals program. Other funding agencies in Canada either have, or are developing, open access policies and support. This article presents an overview of CLA advocacy and open access in Canada, with a focus on initiatives with a strong library involvement or leadership.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.014 | 0.037 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.020 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".