Vulnerability to Brain-Drain among Academics in Institutions of Higher Learning in Ethiopia
Bibliographic record
Abstract
This study investigated the extent, causes, and correlates of vulnerability to brain-drain among Ethiopian academics in higher education institutions (HEIs). The sample constituted a total of 103 faculty members (Females 9.3% and Males 90.7%) drawn from three colleges and four faculties affiliated to the Debub University. Data were collected through self-reported measures assessing vulnerability to brain-drain (external brain-drain conceptualized as intention to remain in a western country given that they would have opportunities for further study or research; and internal brain drain defined as a brain circulation within the country), affective job characteristics (job satisfaction and organizational commitment), and work environment factors. The results show that affective job characteristics and work environment variables significantly predicted vulnerability to internal brain-drain. While external brain drain is associated with vulnerability to internal brain drain and organizational citizenship behavior (OCB). A closer investigation into the prominence of the pull and push factors further disclosed that working condition and the salary are the outstanding ones. Implications of the findings for policy making are also discussed.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".