The Adoption of Open Access Funds Among Canadian Academic Research Libraries, 2008-2012
Bibliographic record
Abstract
As a result of changes in scholarly communication created by the open access movement, some academic libraries established open access (OA) publishing funds. OA funds are monies set aside at an institution to fund open access publishing of the results of scholarly research. OA funds are a recent innovation in the type of services offered by academic libraries. Adoption of an innovation can be examined in the light of established theories of innovation adoption among social systems. To examine academic libraries’ responses to OA publishing charges, this article explores the adoption of OA funds among Canadian academic research libraries from 2008 to 2012 by analyzing results from a series of previously published surveys. The findings are then examined in light of Everett Rogers’ Innovation Diffusion Theory (IDT) to consider the question of whether or not OA funds are becoming a standard service in Canadian academic research institutions. Adoption in Canada is briefly compared to that in the United States and United Kingdom. The paper concludes that, as of 2012, OA funds were becoming common but were not a standard service in Canadian academic research libraries and that libraries were actively participating in the development of OA funding models. Given the current Canadian context, the need of researchers for OA publishing support is likely to create pressure for continued adoption of OA funds among Canadian academic research institutions. However, assessment of existing OA funds is needed.
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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 | 0.008 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.024 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".