Comparative Health Law and Policy Critical Perspectives on Nigerian and Global Health Law
Bibliographic record
Abstract
Health law and policy in Nigeria is an evolving and complex field of law, spanning a broad legal landscape and drawn from various sources. In addressing and interacting with these sources the volume advances research on health care law and policy in Nigeria and spells the beginning of what may now be formally termed the ’Nigerian health law and policy’ legal field. The collection provides a comparative analysis of relevant health policies and laws, such as reproductive and sexual health policy, organ donation and transplantation, abortion and assisted conception, with those in the United Kingdom, United States, Canada and South Africa. It critically examines the duties and rights of physicians, patients, health institutions and organizations, and government parastatals against the backdrop of increased awareness of rights among patient populations. The subjects, which are discussed from a legal, ethical and policy-reform perspective, critique current legislation and policies and make suggestions for reform. The volume presents a cohesive, comparative, and comprehensive analysis of the state of health law and policy in Nigeria with those in the US, Canada, South Africa, and the UK. As such, it provides a valuable comparison between Western and Non-Western countries. [From https://www.routledge.com/Comparative-Health-Law-and-Policy-Critical-Perspectives-on-Nigerian-an/Iyioha-Nwabueze/p/book/9781472436757]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.033 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".