Health Sector Industrial Labour Troubles in Nigeria: Implication for Leaders and Other Stakeholders
Bibliographic record
Abstract
Nigeria’s health sector has been challenged with frequent industrial labour troubles, commonly called strikes. Industrial labour disputes are the existence of incompatibility of goals, interests, and values of different persons or groups in an organization. Several causes have been identified for the strikes in Nigeria. This review focuses on the various causes of industrial troubles in Nigeria, and the consequences of the industrial action on the stakeholders. Causes were identified as: poor administration, incompetent leaders, the failure of government to keep the agreement that was signed with the unions, poor funding and poor infrastructure in the health sector, and supremacy challenge between doctors and other health workers were identified amongst other factors to be the cause of strikes in the Nigerian health sector. Unfortunately, patients were the greatest affected during these strikes, especially when the public health facilities were shut down and the patients were discharged to go home or moved to other private hospitals.
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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 | 0.004 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".