UNRAVELLING THE RULE AGAINST THE DISCRIMINATION OF FIELDS OF TECHNOLOGY UNDER THE PATENT RULES OF THE TRIPS AGREEMENT
Bibliographic record
Abstract
The rule against the ‘discrimination’ of fields of technology in TRIPS Article 27.1 has the potential to contradict the very technology-specific nature of patent law and to disallow the WTO membership from specifically addressing public interest and right-holder related concerns in a given field of technology. However, in Canada- Patent Protection of Pharmaceuticals (DS114), the only report by a WTO tribunal to have substantively dealt with this obligation to date, the Panel indicated that this rule is not absolute by formulating the concept of ‘discrimination’ in Article 27.1 as the ‘unjustified imposition of differentially disadvantageous treatment’. Nevertheless, this thesis argues that the Panel left some vital elements of its formulation open-ended, thereby making it difficult for a member to comprehend the circumstances in which the ‘differential treatment’ of field of technology constitutes ‘discrimination’. To bring clarity to this ambiguity, this thesis interprets this obligation afresh and identifies some fundamental rationales that should have, and in fact appear to have influenced the Panel in its formulation. To this end, this thesis draws some vital influences from the context relating to WTO’s substantive non-discrimination norms (National Treatment and Most-Favoured Nation Treatment) under its covered agreements that deal with goods and services and explores the type and extent of autonomy that has been preserved within TRIPS’s Objectives and Principles. Whilst this thesis argues that an ambiguous obligation such the prohibition of ‘discrimination’ of fields of technology found in TRIPS Article 27.1 should be interpreted in a manner that seeks a balance between the obligation and the autonomy of the WTO membership, it also sheds light on the future of TRIPS’s own National Treatment and Most-Favoured Nation treatment obligations for which WTO tribunals have not yet recognized the applicability of any general exceptions or justificatory concepts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".