Open Access and Academic Journals in Canada: A Political Science Perspective
Bibliographic record
Abstract
Abstract The push to implement Open Access (OA) as the new standard for academic research dissemination is creating very real pressures on academic journals. In Canada, the Social Science and Humanities Research Council (SSHRC) recently adopted a policy requiring that journals applying for its Aid to Scholarly Journals (ASJ) grant make their scholarly content freely accessible after no more than a 12-month delay. For journals such as the Canadian Journal of Political Science (CJPS) that not only publish high-quality, peer-reviewed articles to a specialized audience but also support the work of scholarly associations through the revenues they generate, the push to move to OA comes with a number of challenges. The Canadian Political Science Association (CPSA) and the Société québécoise de science politique (SQSP) established a committee to chart the best course of action for the CJPS in light of this changing landscape. This article summarizes the key findings of the committee and underscores some of the challenges of OA for journals with a profile similar to the CJPS, as well as for the broader research ecosystem that they support.
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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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.026 |
| Science and technology studies | 0.031 | 0.018 |
| Scholarly communication | 0.034 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.014 | 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".