Do stronger intellectual property rights promote seed exchange: evidence from U.S. seed exports?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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 it