Do stronger intellectual property rights promote seed exchange: evidence from U.S. seed exports?
Bibliographic record
Abstract
Abstract With increased private investment in crop breeding research in the developed world, intellectual property rights have gained importance in seed sector. Trade Related Aspects of Intellectual Property Rights (TRIPS)‐plus provisions included in recent free trade agreements between the developed and developing countries show a tendency of the developed world to impose their high standards for protection of plant intellectual property on the developing world. While stronger intellectual property rights can increase international exchange in seed, market power effect can lead to a reduction in exports of seed to foreign markets. This article estimates the impact of intellectual property rights on U.S. seed exports. The estimation is performed at a crop level using Heckman selection model. The results reveal that the impact of intellectual property rights varies across different types of crops—open‐pollinated, genetically modified, and hybrid crops. While TRIPS provisions are important to facilitate transfer of genetically modified crops, they play a minor role for open‐pollinated and hybrid crops. The results also show that plant breeders’ rights envisioned by the UPOV system can be important to promote seed exchange when proper mechanisms are put in place to enforce these rights.
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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 | 0.002 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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.
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".