Understanding the influence of librarians cognitive frames on institutional repository innovation and implementation
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
Abstract An institutional repository (IR) is an information system (IS) that has the potential to promote open access to scientific knowledge and the visibility and reputation of scholars. The small number of universities in developing countries that have successfully innovated and implemented an IR hampers the actualization of these benefits. This situation calls for effort toward understanding the factors responsible. We used the snowball sampling technique to select 45 academic librarians from three university libraries in Nigeria that were involved in IR innovation. Data were collected through in‐depth interviews and participatory observation for 15 months. Thematic data analyses show that the relationships between academic librarians' IR innovation cognitive frames (belief, scripts, and resistance routines) influence IR innovation outcomes. The result is a research model that explicates how the relationships between academic librarians' cognitive frames and internal functioning of libraries constitute IR innovation barriers to IR innovation and implementation.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 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