How green is our valley?: five-year study of selected LIS journals from Taylor & Francis for green deposit of articles
Bibliographic record
Abstract
This study reviews content from five different library and information science journals: Behavioral & Social Sciences Librarian, Collection Management, College & Undergraduate Libraries, Journal of Electronic Resources Librarianship and Journal of Library Administration over a five-year period from 2012–2016 to investigate the green deposit rate. Starting in 2011, Taylor & Francis, the publisher of these journals, waived the green deposit embargo for library and information science, heritage and archival content, which allows for immediate deposit of articles in these fields. The review looks at research articles and standing columns over the five years from these five journals to see if any articles were retrieved using the OA Button or through institutional repositories. Results indicate that less than a quarter of writers have chosen to make a green deposit of their articles in local or subject repositories. The discussion outlines some best practices to be undertaken by librarians, editors and Taylor & Francis to make this program more successful.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".