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Record W2564973924 · doi:10.54648/bula2016013

Parallel Trade in Pharmaceuticals: Re-Aligning National Patent Exhaustion and Life-Saving Drugs

2016· article· en· W2564973924 on OpenAlexaboutno aff
Devarshi Mukhopadhyay

Bibliographic record

VenueBusiness Law Review · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Intellectual propertyPosition (finance)Order (exchange)Law and economicsEconomicsAccess to medicinesInternational tradeBusinessPublic economicsLawPolitical scienceFinance

Abstract

fetched live from OpenAlex

The author, through this paper, shall seek to determine whether parallel trade, especially in the context of life-saving drugs, increases potential healthcare access1 to the developing and developed nations or in crisis markets, without significantly jeopardizing either the general safety of the goods, or diluting the sanctity of the intellectual property purpose.2 In the first segment of the paper, the author shall seek to demonstrate the business law link between the economics of parallel trade with the international context of patent exhaustion, following which the author will then go on to examine global policy regimes which have dealt with this issue in specific consumer market situations. Special focus shall be drawn to the markets of Germany, the United Kingdom, the United States of America and Canada in order to narrow down on policy experiences. In the final and concluding segment of this paper, the author shall attempt to re-align the existing competing interests on the question of exhaustion, with the objective of reaching a suitable policy position on this. As part of this segment, a detailed study of existing litigation and case law shall also be studied in order to suggest suitable solutions to determining the parallel trade question.

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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.193
GPT teacher head0.338
Teacher spread0.146 · 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
GenreReview

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
Published2016
Admission routes1
Has abstractyes

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