Intellectual Property Training and Education: A Development Perspective
Bibliographic record
Abstract
Since the TRIPS Agreement, IP training and education activities have become more prominent. The World Intellectual Property Organization (WIPO)'s Development Agenda and other IP reform efforts have included recommendations for IP education. WIPO and the WIPO Academy are prominent actors in IP education, engaging a wide audience in developing countries. WIPO has been particularly influential in Nigeria, but by focusing mainly on piracy and the enforcement concerns of rights holders, training and education activities have yet to facilitate more context-sensitive discourse about broader socio-economic and cultural implications of IP issues and human development. Most or all IP education activities currently fail to integrate a development dimension, despite its centrality in the WIPO DA. The DA provides an opportunity to re-evaluate the design and delivery of IP training and education, drawing on emerging best practices in development-oriented IP courses. The authors conclude by exploring next steps for improving training and education on IP and development.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".