A Critical Examination of the African Legal Framework for Indigenous Knowledge
Bibliographic record
Abstract
Abstract Indigenous or traditional knowledge (TK) systems are the springboard of authentic African innovation and creativity. However, there has been no adequate attempt to determine whether Africa internalizes its comparative advantage in Indigenous knowledge systems in its continental frameworks for socio-economic and development collaboration and aspirations. Despite TK's presumed significance and Africa's proactive promotion of Indigenous knowledge in international fora, TK is treated marginally in key instruments, perhaps as a legacy of colonially entrenched contempt for Indigenous knowledge systems. For Africa to effectively participate in the science and technology revolution, it is necessary to have an introspective and critical appraisal of the present traction around Indigenous knowledge, which is a logical starting point for effective science, technology and innovation policy-making in furtherance of African socio-economic and development collaboration in the knowledge economy.
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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 | 0.037 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.024 | 0.077 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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".