Traditional Healthcare Delivery Systems in the 21st Century Nigeria: Moving beyond Misconceptions
Bibliographic record
Abstract
One of the most notable features of medicine in the later part of the preceding century were vigorous criticisms against traditional systems of healthcare delivery, almost to a point of suffocation. Although most of the issues raised to affirm the seemingly inadequate status of this system are compelling, its absolute undesirability has been difficult to establish. Part of the misconception derives from lumping Nigeria into one integrated and indivisible indigenous unit, notwithstanding differences in values, beliefs and practices among communities. Against this backdrop, this study invites a reassessment and possible integration of Nigerian traditional medicine with the introduced systems of healthcare delivery. This will ensure not only a holistic approach to dealing with complex health issues among Nigerians, but also the continued relevance of indigenous medicine. Critical issues examined include forms and factors affecting traditional medicine, and conflicts between indigenous and introduced systems of healthcare delivery. Consequently, a framework for explaining traditional medicine in the context of Nigeria was designed through a triangulation of Rational Choice theory, Ethnomethodology and the Health Belief Model.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".