Institutional Repositories: Towards the Identification of Critical Success Factors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Institutional repositories (IRs) are digital collections that capture and preserve the intellectual output of a single or multi-university community. Their aim is to provide access to scholarly material without the economic barriers that currently exist in scholarly publishing. If successful, IRs hold the promise of being very advantageous to researchers everywhere, especially those in the developing world. The IR concept is very new and has yet to be studied in any comprehensive way. This paper describes a study being conducted by the Canadian Association of Research Libraries to determine some success factors of institutional repositories. Through the CARL Institutional Repositories Pilot Project, several variables are being examined to determine whether they contribute to the input activity and use of the IRs being implemented at several Canadian research libraries. The project is in its initial stages, and has yet to show significant results. However, the paper presents a detailed description of the IR concept; identifies and explains the variables that are being studied; and discusses some of the challenges involved in the study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.025 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it