Open Access Literature Productivity of Library and Information Science
Bibliographic record
Abstract
DOAJ is an online directory that indexes and provides access to quality open access, peer-reviewed journals. This chapter shows that open Access literature productivity of Library and Information Science in DOAJ perspective. Totally in DOAJ 124 journals in general library science i.e. 56.12%. In the subject digital library there are 17 journals which is in the second position i.e. 11.80%. There are 3 journals (2.08%) in the subject bibliometrics. There are 40 countries who contributed journals in DOAJ in library science subject. USA is the top most country with 37 (25.69%) journals published. Second position is for Spain with 13 (9.039%) journals. Third and fourth positions are for Brazil, United Kingdom and India with 13 (9.03%), 6(4.17) and 6 (4.17%) journals respectively. For the countries like China, Germany and Canada there are 5 (3.47%) journals at their credit. The study shows that out of the 144 journals, 51 journals are having both print and electronic versions, while 93 journals are having only the electronic versions. The study also shows that academic institutions are the major contributors to OA in DOAJ in library science and second position is owned by commercial. The societies contribute about 7 journals. Many R & D organizations and Institutes are contributing to OA journals. Here 15 journals are contributed by other Organizations. The government organizations are contributing 5 journals which are less compared to others.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.043 | 0.054 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.022 | 0.975 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".