Are Africans States Willing to Ratify and Commit to Human Rights Treaties? The Example of the Maputo Protocol
Bibliographic record
Abstract
This paper sheds light on factors affecting the ratification and commitment of African countries to treaties, to change and to improve their conduct according to the obligations present in those treaties. As a way of example, this work uses the Protocol to the African Charter on Human and Peoples’ Rights on the Rights of Women in Africa (“Maputo Protocol”), considered as the pillar of women’s human rights protection in Africa. This paper considers the effect of the breaches on the sovereign rights of African states to determine the content of their domestic law and if they have made any progress in the protection of women’s rights on the continent. I wonder that because there is significant concern as to how the Maputo Protocol can be implemented given that, for example, several rights in the Protocol clash with established cultural and national traditions. That is why many of the provisions contained in the Maputo Protocol are not currently achievable given also the present socio-economic conditions in many countries of the continent. In addition, the Maputo Protocol fails to recognise several rights, deemed particularly relevant for refugees in Africa, such as the right to a fair trial and the rights of convicted and detained women. When human rights norms are emerging, as it is the case with those contained in the Maputo Protocol, strong international legal commitment generates greater public support for compliance compared to weak commitment. Conversely, when a human rights norm is domesticated, stronger state commitment does not always generate greater public support compared to a weaker commitment. That is why the effort to promote the Maputo Protocol should be dine at a continental level and not leaving it to a single country or to a small group of 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 | 0.032 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".