Implementing the World Intellectual Property Organization’s Development Agenda
Bibliographic record
Abstract
The newly adopted World Intellectual Property Organization (WIPO) Development Agenda presents a real opportunity to revolutionize the international governance of intellectual property law and policy. The litmus test for its success, however, will be if and how the agenda is implemented in practice. This edited collection brings together a series of incisive essays written by leading thinkers from emerging economies, Canada, and elsewhere to develop concrete strategies for implementing the agenda. The essays cover a range of fundamental issues surrounding the agenda and examine its recommendations from multidisciplinary and multi-regional perspectives. Several essays explore the role of WIPO and its member states in steering the direction of future reform as well as potential approaches to achieve this goal. Other contributions examine specific recommendations on WIPO’s activities within the broader context of development. This volume will be a useful source of reference for informed but non-expert readers, including government officials and delegates at international and “capital” levels, leaders of the international business community, individuals in inter- and non-governmental organizations, and scholars in the fields of law and international governance. Co-published with the International Development Research Centre and the Centre for International Governance Innovation
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| 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".