Waking OA's “Slumbering Giant”: The University's Mandate To Mandate Open Access
Bibliographic record
Abstract
Universities (the universal research-providers) as well as research funders (public and private) are beginning to make it part of their mandates to ensure not only that researchers conduct and publish peer-reviewed research (“publish or perish”), but that they also make it available online, free for all. This is called Open Access (OA), and it maximizes the uptake, impact, and progress of research by making it accessible to all potential users worldwide, not just those users whose universities can afford to subscribe to the journal in which it is published. Researchers can provide OA to their published journal articles by self-archiving them in their own university's online repository. Students and junior faculty—the next generation of research providers and consumers—are in a position to help accelerate the adoption of OA self-archiving mandates by their universities, ushering in the era of universal OA.
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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 | 0.082 | 0.205 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.030 | 0.028 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".