An Appraisal of Burnout among the University Lecturers in Ekiti State, Nigeria
Bibliographic record
Abstract
This survey investigated, identified and described the status of burnout among the university lecturers in EkitiState University. A sample consisted of 80 respondents made up of 52 male and 28 female lecturers. Oneresearch question was raised and one hypothesis was generated and tested at 0.05 level of significance usingt-test, mean and standard deviation. The result of the analysis showed that there was a high level of burnoutamong the lecturers. The study further revealed that there was a significant difference between burnout acrossthe ages of lecturers. Based on the findings, it was recommended that the university management should createan atmosphere that promotes health through recreation in form suitable to the age range of the lecturers, studyleave and a change of environment. Also, the university management should create job enrichment foremployees that perform same work. Also recommended was that all the lecturers should be allowed to go oncompulsory leave yearly to refresh themselves and get out of boredom.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".