RECOGNITION OF INDIGENOUS PEOPLES IN ACCESS AND BENEFIT SHARING (ABS) LEGISLATION AND POLICIES OF THE PARTIES TO THE NAGOYA PROTOCOL
Bibliographic record
Abstract
The Nagoya Protocol on Access and Benefit Sharing (ABS) provides for the rights of indigenous peoples and local communities (ILCs) in accordance with the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP). States Parties are obliged to take legislative, administrative and technical measures to recognize, respect and support/ensure the prior informed consent of indigenous communities and their effective involvement in preparing mutually agreed terms before accessing genetic resources and associated traditional knowledge or utilizing them. Within the ambit of contemporary debates encompassing indigenous peoples’ right to self-determination, this paper examines the effectiveness of the percolation of the legal intent of international law into existing or evolving domestic laws, policies or administrative measures of the Parties on access and benefit sharing. Through an opinion survey of indigenous organizations and the competent national authorities of the Parties to the Convention on Biological Diversity (CBD), the findings indicate that the space, recognition and respect created in existing or evolving domestic ABS measures for the rights of indigenous communities are too inadequate to effectively implement the statutory provisions related to prior informed consent, mutually agreed terms and indigenous peoples’ free access to biological resources as envisaged in the Nagoya Protocol. As these bio-cultural rights of indigenous peoples are key to the conservation and sustainable use of biodiversity, the domestic ABS laws need reorientation to be sufficiently effective in translating the spirit of international ABS law and policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.026 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".