Open Access Electronic Resources Use and Research Productivity of Faculty Members: A Case Study of a Selected University in Ghana
Bibliographic record
Abstract
Research is one of the key pillars in the teaching and learning situation in any university in the world. However, the approach to research varies from one university to the other. The purpose of this study was to find out how the level of awareness and satisfaction, the challenges and extent of use of open access resources impact research productivity of faculty in *Dartum University. A quantitative survey research method was adopted. A sample size of 62 full-time lecturers and 134 part-time lecturers was selected for the study using a stratified simple random sampling technique. The findings revealed that research productivity is low despite the high level of awareness and satisfaction with open access use. Again, the findings showed that faculty members use open access to a considerable extent and point out some challenges associated with open access use. It was concluded that there is a very weak but significant influence of open access use on research productivity in Dartum University. It is recommended that African universities, and in particular Dartum University, establish or patronise institutional repositories which support open access.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".