Equity, Fairness and Universal Access – The Key to Better Health: A Comparative Analysis of Nigerian, British and Canadian Health Systems
Bibliographic record
Abstract
A common feature of all high performing health systems is their anchor on equity, fairness and universal access to health services – the trinity of better health. While some countries, such as Britain and Canada, have attained this threshold, others with nascent and fragile health systems, like Nigeria, are still struggling to lay the necessary foundations. These foundations are represented in Nigeria’s National Health Act 2008 (NHA) and National Health Insurance Scheme Act 1999 (NHIS). In Canada, the central health legislation is the Canada Health Act 1985(CHA), itself a consolidation of two prior federal legislation, namely, the Hospital Insurance and Diagnostic Services Act 1957 and the Medical Care Act 1966, and the principal health legislation in Britain is the British National Health Service Act (NHSA) 1946. This paper compares the legal and policy frameworks in Nigeria with key provisions of the NHSA and CHA as a basis for improving health in the former. By juxtaposing the health frameworks in the three countries, the paper brings to the fore the deficiencies in the Nigerian system and shows how to remedy them.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".