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Record W2262056843

Twelve years after Canada's access to medicines regime : should South Africa follow the path?

2015· article· en· W2262056843 on OpenAlexaffabout
Mélanie Bourassa Forcier, Beatrice Stirner

Bibliographic record

VenueSouth African Law Journal · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsLegislationExportationOrder (exchange)BusinessMechanism (biology)Drug industryInternational tradeDeveloping countryEconomic growthLawPolitical scienceEconomicsFinanceEngineering
DOInot available

Abstract

fetched live from OpenAlex

On 30 August 2003, the World Trade Organization decided that eligible countries without manufacturing capacities would be allowed to import generic drugs once they had been issued with a compulsory licence from an exporter country. Canada was the first country to implement this decision in its patent law and subsequently to apply it. Considering the fact that improving drug accessibility is a priority in sub-Saharan Africa, it is relevant for countries with manufacturing capacities, like South Africa, to consider implementing the August 30th decision into their legislation. This mechanism represents an opportunity for South Africa to develop its pharmaceutical industry and to increase drug accessibility in Africa. In exploring this option, the Canadian drug exportation mechanism could serve as a model for legislation in South Africa. In this article we review the Canadian experience, including the weaknesses of the Canadian platform. Based on lessons from this review, we suggest that South Africa should consider implementing a new drug exportation mechanism in its national patent law in order to rebuild its pharmaceutical manufacturing capacities and to improve access to drugs in Africa. In essence, by supplying sub-Saharan African countries, and thus using the compulsory licensing mechanism created following the Pretoria lawsuits, South Africa would close the loop.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.631
Threshold uncertainty score0.989

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.098
GPT teacher head0.285
Teacher spread0.187 · 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 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

Citations0
Published2015
Admission routes2
Has abstractyes

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