Indigenous peoples, UNDRIP and land conflict: an African perspective
Bibliographic record
Abstract
The 2007 adoption of the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) represented a watershed moment for Indigenous rights. Though wide-ranging in scope, a core element of UNDRIP is the recognition of rights to land; specifically, the right to free, prior and informed consent (FPIC) embedded in the Declaration. Given the widespread scale of insecurity and conflicts over land facing Indigenous peoples, FPIC represents a critical yet controversial development. This paper explores the links between UNDRIP/FPIC and land conflict in a unique context – sub-Saharan Africa. Notwithstanding the dismissive position of numerous African governments that ‘we are all Indigenous’, divisive debates around the politics of indigeneity are on the rise. Such debates regularly invoke the exclusionary concept of autochthony and centre on competing claims to rights to land. The paper thus considers the following questions: How have African governments responded to UNDRIP? What are the politics around applying the concept of Indigenous rights in the African context? Finally, could the right to FPIC provide a framework for preventing or possibly fuelling conflicts over land? By surveying key developments across the continent, the paper provides an African perspective on the promise and perils of UNDRIP.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".