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Record W34542512 · doi:10.3390/ejihpe10030058

Negotiating a standard material transfer agreement under the International Treaty on Plant Genetic Resources for Food and Agriculture: issues and concerns for Africa

2006· article· en· W34542512 on OpenAlexfundaboutno aff
Edgar Tabaro

Bibliographic record

VenueComparative and International Law Journal of Southern Africa · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicInternational Maritime Law Issues
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNegotiationTreatyIndigenousAgricultureLatin AmericansPolitical scienceRealmGenetic resourcesInternational tradeInternational lawLawBusinessEcologyBiotechnologyBiology

Abstract

fetched live from OpenAlex

This contribution entails an analysis of the development of a standard material transfer agreement presently being negotiated under the International Treaty for Plant Genetic Resources for Food and Agriculture. In particular, the article explores the key concerns for the African negotiating group, and what ought to be looked out for in the design of a standard agreement. Case studies of agreements designed between bio-prospectors and indigenous communities are selected from Asia, the Pacific region, Latin America, and Africa for comparative purposes whereupon conclusions as to whether Africa will benefit are drawn. The recommendations are drawn from tested legal principles in the general realm of international law taking into consideration the African peculiarities that ought to inform the African negotiating group.

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 imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.012
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.031
GPT teacher head0.259
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2006
Admission routes2
Has abstractyes

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