Factors Influencing Research Collaboration in LIS Schools in South Africa.
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
The study sought to explore the underlying factors that influence research collaboration in Library and Information Science (LIS) schools in South Africa. The population for the study consisted of 85 academic teaching staff employed by LIS schools in South African universities. A survey design was used to obtain data for the study, through a questionnaire containing open- and close-ended questions. A total of 85 teaching staff in 10 LIS schools in South Africa were alerted, through email, to the location of the Web-based questionnaires, developed using the Stellarsurvey software. A total of 51 questionnaires were completed and returned for analysis. The findings suggest that factors such as networking, sharing of resources, enhancing productivity, educating students, overcoming intellectual isolation, and accomplishments of projects in a short time as well as learning from peers influenced research collaboration in LIS in South Africa. Factors that are likely to hinder effective collaboration in LIS research include bureaucracy, lack of funding, lack of time, as well as physical distance between researchers. The findings further suggest that even though there are drawbacks to collaboration, majority of LIS researchers thought that collaboration is beneficial and should be encouraged.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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