Group Rights Under the African Charter on Human and Peoples’ Rights: Concept, Praxis and Prospects
Bibliographic record
Abstract
It is particularly meet, on the thirtieth anniversary of the adoption of the African Charter on Human and Peoples’ Rights, to re-examine the ways in which its group rights provisions has been interpreted and applied. What is the concept of group rights that animates the “peoples’ rights” provisions in the African Charter? How have these group rights been actually interpreted and applied in the jurisprudential praxis of the African Commission on Human and Peoples’ Rights, which (despite the establishment of the as yet young, and in any case, soon to be replaced African Court of Human Rights) remains to date its main interpretive body? And what are the future prospects of these provisions in that jurisprudence? These are the main questions that this chapter tackles through analytical examinations of the African Charter itself, the relevant primary and secondary literature, and the jurisprudence of the African Commission. To this end, section 2 examines the general debate regarding the concept of group rights and its place in international human rights praxis. Section 3 briefly considers the conception of group rights that animated the “peoples’ rights” provisions in the African Charter. In section 4, a fairly detailed examination of the jurisprudence of the African Commission with respect to each one of the major group rights provisions of the Charter is conducted. Following that tour d’ horizon, some brief more general closing thoughts on the future of group rights in the African Human Rights System are offered in section 5.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.035 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| 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".