Harnad Comments on Canada’s NSERC/SSHRC/CIHR Draft Tri-Agency Open Access Policy. Canadian Tri-Agency Call for Comments
Bibliographic record
Abstract
The Draft Canadian Draft Tri-Agency Open Access Policy is excellent in preserving fundees’ free choice of journal, and afree choice about whether or not to use the research funds to pay to publish in an OA journal. However, deposit in the fundee’s institutional repository immediately upon acceptance for publication needs to be required, whether or not the fundee chooses to publish in an OA journal and whether or not access to the deposit is embargoed for 12 months. This makes it possible for the fundee’s institution to monitor and ensure timely compliance with the funder OA policy and it also facilitates providing individual eprints by the fundee to individual eprint requestors for research purposes during any embargo. Institutional repository deposits can then be automatically exported to any institutional-external repositories the fundee, funding agency or institution wishes. On no account should compliance with funding agency conditions be left to the publisher rather than the fundee and the fundee’s institution.
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 | 0.022 | 0.115 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.028 | 0.017 |
| Insufficient payload (model declined to judge) | 0.099 | 0.037 |
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".