Coercive Vaccination Policy in Nigeria: Legal Perspectives
Bibliographic record
Abstract
Background: In December 2021, the Nigerian federal government declared a compulsory COVID-19 immunisation for all employees of government. This declaration by the government has been viewed by some Nigerians as a contravention of the fundamental rights of Nigerian citizens. Aim: This study was aimed at identifying the human rights concerns surrounding vaccination mandates from the perspective of legal practitioners in Nigeria. Methods: This study was a cross-sectional study that used a semi-structured self-administered questionnaire to interview legal practitioners practicing in Uyo, Nigeria. The survey focused on identifying human right concerns surrounding vaccination mandates. Results: One hundred and five legal practitioners participated in the study. Data analysis revealed that 79 (75.2%) of our respondents agreed that vaccination mandates to prevent an epidemic is well within the powers of the state, while 97 (92.4%) asserted that the Nigerian constitution gives the state authority to enact health laws including quarantine and vaccination laws to protect its citizens. According to 59% (n=62) of our respondents, the only exception to a mandatory vaccination is an offer of apparent or reasonably certain proof to the state’s board of health that the vaccination would seriously impair health or probably cause death. Conclusion: In the opinion of majority of the legal practitioners interviewed, the Nigerian constitution gives the state the power to implement measures established by legislation to protect the health of her citizens. Thus, coercive vaccination policies by the state to protect the public from an epidemic outbreak of a disease which threatens the safety of citizens may be legally binding on the citizens.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".