Ethical Considerations in Authorship and Postgraduate Supervision in Universities in Kenya
Bibliographic record
Abstract
The emergence of knowledge economy has put premium on higher education. This has led to a rise in the number of postgraduate training and reforms in higher education. Research, a core mandate of institutions of higher learning, should enable states to meet development needs. Research for development will require the highest standards possible in the conduct of research. This has led to calls for research ethics to protect individuals, communities and the environment. In this study, we explore ethical considerations in authorship and postgraduate supervision in universities in Kenya using a desktop survey. The study established that in Kenya, Universities Standards and Guidelines 2014 and Harmonized Criteria and Guidelines for Appointment and Promotion of Academic Staff in Universities in Kenya have apportioned the highest score on research and publication for appointment and promotion of academic staff in universities. This is likely to trigger unethical practices, increase authorship disputes and undermine collaborative research. The existing framework does not provide for a criteria on authorship listing; and the mandate of Institutional Ethics Review Committees (IERCs) is limited to approval of research proposal and treatment of human participants. Universities in Kenya have developed procedures for appointment and specified the responsibilities of supervisors of postgraduate students. However, very little has been done to train and inculcate research ethics in postgraduate students and supervisors. To mitigate these, universities should develop criterion for awarding publication credit. IERCs should expand their mandate to include ethical consideration beyond a research proposal and universities should train supervisors on supervision and research ethics before appointment. Further research is required to determine the preparedness of supervisors of postgraduate students in Kenya in the responsible conduct of research. Keywords: research ethics, authorship, supervision, universities. Kenya DOI: 10.7176/JEP/14-15-03 Publication date: May 31 st 2023
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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 | 0.046 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".