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Record W2345897127 · doi:10.1017/cbo9780511750786.005

The TRIPS Waiver as a recognition of public health concerns in the WTO

2010· book-chapter· en· W2345897127 on OpenAlexaboutno aff
Andrew D. Mitchell, Tania Voon

Bibliographic record

VenueCambridge University Press eBooks · 2010
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
Fundersnot available
KeywordsWaiverTRIPS AgreementTRIPS architectureIntellectual propertyBusinessPublic healthInternational tradeWorld tradeDeveloping countryObstacleAccess to medicinesPolitical scienceEconomic growthLawMedicineEconomicsEngineering

Abstract

fetched live from OpenAlex

Introduction Patent protection for pharmaceutical products as mandated in the Agreement on Trade-Related Aspects of Intellectual Property Rights (‘TRIPS Agreement’ or ‘TRIPS’) of the World Trade Organization (‘WTO’) represents a potentially significant obstacle to public health measures, particularly for developing countries seeking to import medicines to deal with serious public health concerns, such as the HIV/AIDS crisis. Since 2001, WTO members have acknowledged this tension while working slowly towards a formal amendment of WTO rules that would facilitate compulsory licensing of pharmaceuticals for the benefit of least-developed country (‘LDC’) members, as well as other members lacking sufficient manufacturing capacity to use the existing flexibilities in the TRIPS Agreement in respect of public health. As the first shipment of drugs from Canada to Rwanda under the new arrangements has recently taken place (in September 2008), we take the opportunity to reflect on the steps taken to date within the WTO to resolve the patent/public health tension. In section 2, we explain why WTO members needed to reform the TRIPS Agreement in order to improve access to medicines for public health reasons, before turning in section 3 to the temporary solution reached in the form of a waiver of certain TRIPS obligations. In section 4 we then consider the more permanent solution of a formal amendment that is envisaged for the future. This chapter then turns in section 5 to consider how the waiver has been used in practice.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.008
Scholarly communication0.0090.012
Open science0.0010.003
Research integrity0.0130.013
Insufficient payload (model declined to judge)0.0100.006

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 head0.221
GPT teacher head0.226
Teacher spread0.005 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations5
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooks→Same topicIntellectual Property and Patents→French-language works237,207→