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Context and Ambiguity in the Making of Law: A Comment on Amending India's Patent Act

2007· article· en· W2158471647 on OpenAlexaboutno aff
Dwijen Rangnekar

Bibliographic record

VenueThe Journal of World Intellectual Property · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual propertyTRIPS architectureTRIPS AgreementAmbiguityContext (archaeology)Flexibility (engineering)Government (linguistics)Law and economicsLawExploitCopyright ActBusinessPolitical scienceEconomicsEngineeringManagementGeographyComputer security

Abstract

fetched live from OpenAlex

In implementing its patent‐related obligations to the Agreement on Trade‐Related Aspects of Intellectual Property Rights (TRIPS), India opted for the optional additional transitional provisions in article 65.4. This, delayed the introduction of product patents in exempt technologies, notably pharmaceuticals, until 1 January 2005. Ostensibly, this gave India the opportunity to exploit changing circumstances to and emergent views on TRIPS implementation, in particular exploring new interpretations to residual flexibility in TRIPS and any continuing legal ambiguity in TRIPS obligations. Here, the Panel Report in Canada: Patent Protection of Pharmaceutical Products is pertinent in having exhibited rare reticence in stepping back from defining the principle of non‐discrimination in article 27.1 of TRIPS. In maintaining legal ambiguity, this reticence also provides space for law‐making and regulatory diversity. The article reviews the three amendments to India's Patent Act 1970 and finds mixed use of residual flexibility and some evidence of efforts to explore legal ambiguity. Thus, despite a favourable climate to TRIPS implementation and an active transnational access to medicine campaign, legislators in India have demonstrated a degree of caution. The article concludes that this caution is best explained in terms of deepening ambivalence concerning intellectual property within the government and the changing economic interests of sections of Indian pharma.

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)0.022
metaresearch head score (Gemma)0.043
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: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.332
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.043
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.004
Science and technology studies0.0370.025
Scholarly communication0.0230.011
Open science0.0110.008
Research integrity0.0850.081
Insufficient payload (model declined to judge)0.0040.001

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 head0.272
Teacher spread0.080 · 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
GenreCommentary

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

Citations3
Published2007
Admission routes1
Has abstractyes

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