Institutional Repositories as a Global Dissemination Tool of Educational And Scientific Information
Bibliographic record
Abstract
The authors present an overview of publications on the introduction and use of digital institutional repositories (DIR) in different countries and in Ukraine. A variety of reference and scientific literature, and publications in international scientometric databases have been analyzed. The role of digital institutional repositories in providing access to full-text electronic achievements, disseminating research results, and maximizing their accessibility and scientific influence is highlighted. The problem of creating and using digital institutional repositories in the training of specialists in higher education, as well as the formation of their information and research competence, is considered. It is substantiated that institutional repositories are a powerful tool in pedagogical universities to conduct and disseminate scientific research results in education, pedagogy, and psychology. Particular attention is paid to the role of library materials in the formation and operation of digital institutional repositories. The experience of Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University Library (Ukraine) is reflected separately. Keywords: digital institutional repository, information and research competence, open electronic scientific and educational systems, open science; pedagogical university library
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.021 | 0.029 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".