Open access for the medical librarian
Bibliographic record
Abstract
In this article open access is defined, and the resources and issues of greatest relevance to the medical librarian are discussed. The economics of open access publishing is examined from the point of view of the university library. Open access resources, both journals and articles in repositories, are already significant and growing rapidly. There are close to 2300 fully open-access peer review journals listed in the Directory of Open Access Journals (DOAJ) (320 health sciences titles are included). DOAJ is adding titles at a rate of 1.5 per day. An OAIster search of resources in repositories includes more than 7.6 million items (a rough estimate of the number of articles in repositories, although not all items are full text), and this number will exceed one billion items before the end of 2007. Medical research funders, including the US National Institutes of Health, the Wellcome Trust, the UK Medical Research Council, and the Canadian Institutes of Health Research, either have implemented or are considering open access policies. This will drive greater growth in open access resources, particularly in the area of medicine. There are implications and leadership opportunities for librarians in the open access environment.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.279 | 0.121 |
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".