Research Promoting Guidelines for the College of Government, Rangsit University, Thailand
Bibliographic record
Abstract
Considering that researches are perceived as the main mission for every universities in Thailand, a key performance indicator representing performance quality of relevant agencies, as well as an assessment factor for world leading university ranking programmes. None the less, there are no clear guidelines set by the College of Government, Rangsit University with respect to the internal practices towards the promotion of research activities. Accordingly, this study aims to (i) examine all researches context and research promotion policy found within the College of Government, Rangsit University; (ii) conduct a strength-weakness analysis; (iii) analyse experiences and lessons learned of other institutes; and lastly; (iv) provide applicable recommendations, based on literature reviews of both primary and secondary materials, for the College. From the research findings, it is discovered that (i) supports given by the University have, in general, led to a higher number of research publications, however, more could still be achieved should they had utilised the support programme more effectively; (ii) despite the College’s research support programme including its fostering environment and favourable organization culture, a lack of research initiatives as well as limited number of competent staffs are essentially main challenges that restrict possible research potentials; (iii) the challenges faced by either the College or Rangsit University are also present amongst other institutions, of which they have laid down relevant guidelines aiming to promote research publications; (iv) there are three steps that the College could undergo, as an ad hoc response, the College should provide greater research incentives and more supporting environment for its academics, followed by creating appealing conditions to encourage publications and disseminations, and lastly as an ultimate long run solution, practical strategy and systematic regimes should be put in place.
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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 | 0.049 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.076 | 0.048 |
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".