Academic Staff Turnover Intention in Madda Walabu University, Bale Zone, South-east Ethiopia
Why this work is in the frame
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Bibliographic record
Abstract
AbstractIntroduction: Employee retention is one of the challenges facing several organizations in both the developed and developing countries of the world. Higher education institutions serve as storehouses of knowledge for nurturing the manpower needs of the nation. Higher education institutions are therefore more dependent on the intellectual and creative abilities and commitment of the academic staff than most other organizations. This therefore makes it critically important to retain this cadre of staff. This research was carried out to determine the prevalence of academic staff turnover intention and the factors contributing for it among Madda Walabu University academic staff.Methods: An institution based cross sectional study design was employed. Two hundred and seventeen academic staff were selected randomly and interviewed using a structured self-administered questionnaire. An in-depth interview was carried out on six academic staff. Binary and multiple logistic regression analysis was used using SPSS version 16. To have a more accurate result, triangulation of quantitative findings and an in-depth interview was used. Results: A total of 217 academicians responded to the questionnaire. One hundred sixty four, (75.6%) respondents intended to leave Madda Walabu University and 24.4% of academic staff intended to retain their position or post. A bad work environment (lack of facilities like offices, chairs, internet and toilets) was the most frequently cited reason for leaving (71.3%) followed by 63.4% due to poor management and leadership and 63.4% due to inadequate salary. Academic staff who had worked five or more years in Madda Walabu University were 4.5 times more likely to leave their institution [AOR = 4.5, 95% CI: 1.37, 14.9]. Conclusion: The prevalence of academic staff intending to leave was found to be very high and as a result, Madda Walabu University will be in an alarming state of staff turnover. Before this happens, there should be staff retention mechanisms in place to improve the work environment, management and leadership and remuneration methods to retain senior and skilled academicians.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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