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Record W2097088173

Preserving Cultural Diversity through the Preservation of Biological Diversity: Indigenous Peoples, Local Communities, and the Role of Digital Technologies

2000· article· en· W2097088173 on OpenAlexaffabout
Rosemary J. Coombe

Bibliographic record

VenueSSRN Electronic Journal · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsYork University
Fundersnot available
KeywordsIndigenousDiversity (politics)Cultural diversityGeographyPolitical scienceEnvironmental ethicsEconomic geographyEcologyBiologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Rosemary Coombe was unable to attend the workshop, but she graciously agreed to contribute this paper. In this article, Rosemary Coombe outlines the links that exist between cultural diversity and biological diversity (biodiversity). “Biodiversity preservation, ” she writes, “is an inherently multicultural process. ” Coombe’s focus is an international legal instrument which is principally concerned with the preservation of biodiversity: the Convention on Biological Diversity (CBD). She also examines the contested role of intellectual property rights (IPRs) in relation to the preservation of cultural diversity, and the ways of amending conventional IPR approaches so as to limit their role in the misappropriation of traditional cultural knowledge. Coombe’s examination of the efforts and obligations of council parties to the CBD (of which Canada is one) suggests that Canadian policy relating to IPRs cannot focus solely on the obligations created by membership in the World Trade Organization (WTO). Where the latter organization enjoins members to expand IPR protection. Parties to the CBD are also obliged to concern themselves with the preservation of biological diversity – obligations which enjoin more restrictive approaches to domestic and international IPR rights. Coombe’s article suggests that the recently established Canadian Biotechnology Advisory Committee would be well advised to consider Canada’s obligations under the CBD when it examines issues of IPR. PLEASE NOTE: This article was prepared for the Council of Europe under its Cultural Diversity, Cultural Policy Programme. The author circulates it for comment with the request that it not be reproduced or cited without permission.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.244
Teacher spread0.220 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations2
Published2000
Admission routes2
Has abstractyes

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