Justification of Women’s Right of Access to Safe and Legal Abortion in Nigeria
Bibliographic record
Abstract
Abortion remains one of the most controversial, emotional and burning political issues of our time. Unsafe abortion is a serious public health problem and human rights issue. The pervasive criminalization of abortion in Nigeria is a serious obstacle to improving access to safe and legal abortion. Women’s lack of access to safe legal abortion is a major cause of high rates of maternal mortality. The Nigerian government’s failure to fulfill its human rights obligations under national, regional and international law is largely responsible for this situation. Overcoming these considerable barriers requires governments to sustain a firm commitment to women’s human rights and to ensure access to safe and legal abortion services. Women’s restrictive legal access to safe abortion services violates their human rights and is perhaps one of the pervasive manifestations of unjustified discrimination against women. This article attempts a justification of women’s right of access to safe and legal abortions within national, regional and international laws to which Nigeria is a signatory. Criminalization of abortion leads women to obtain unsafe abortions which threaten their lives and health. The denial of free access to abortion service is a denial of their fundamental human right. Using an analysis of legislations and case laws, we posit that advancing access to safe abortion by the Nigerian government is a necessary requirement to save women’s lives, protect their rights to health, equality and human dignity as specified under the Constitution.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".