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Record W4394904923 · doi:10.56367/oag-042-10775

The critical role of governments in benefit sharing

2024· article· en· W4394904923 on OpenAlexaboutno aff
Dominic Muyldermans, Frank Michiels

Bibliographic record

VenueOpen Access Government · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessPolitical science

Abstract

fetched live from OpenAlex

The critical role of governments in benefit sharing Dominic Muyldermans and Frank Michiels outline the key role governments can play in making a new multilateral mechanism for benefit sharing a success. The fair and equitable sharing of benefits from using biodiversity is one of the key objectives of the Convention on Biological Diversity (CBD, 1992). (1) In 2010, a supplementary agreement to the CBD was adopted, the ‘Nagoya Protocol on Access and Benefit-sharing’, (2) which aimed to establish more concrete guidelines for access to genetic resources and the sharing of benefits. Due to a continued lack of meaningful benefit sharing and the shifting nature of biological research and innovation, moving away from access to physical genetic resources towards DNA sequences accessed in public, open-access databases or generated on the computer, there have been increasing calls for benefit sharing from the use of ‘Digital Sequence Information’ (DSI). As a result, at COP15 at the end of 2022, the Parties decided to establish, as part of the Kunming- Montreal Global Biodiversity Framework, (3) a multilateral mechanism for benefit-sharing from the use of DSI, including a global fund. (4) How this mechanism will function and be implemented has yet to be determined. This article aims to emphasise the key role governments can play in making this new mechanism a success.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.861
Threshold uncertainty score0.996

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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.063
GPT teacher head0.465
Teacher spread0.402 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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