Containing the GMO Genie: Cattle Trespass and the Rights and Responsibilities of Biotechnology Owners
Bibliographic record
Abstract
Genetically modified organisms (GMOs) have caused substantial economic losses by contaminating non-GMO crops and threatening the economic self-determination of non-GMO farmers. After Monsanto v. Schmeiser, biotech IP owners hold most of the rights in the property "bundle" with respect to bioengineered organisms. This commentary highlights the disequilibrium between these broad patent rights and the lack of legal responsibility for harms caused by GMO products. The authors propose that there is a role for tort law--specifically the tort of cattle trespass--in fairly allocating risk and responsibility. The doctrine of cattle trespass reflects a policy of distributive justice, positing that the unique risks associated with keeping living creatures ought to import liability based on the owner's creation and control of those risks. We suggest that GM canola and its bioengineered kin represent the next generation of "livestock," and that biotechnology companies release their transgenic organisms onto the market in the knowledge that these organisms may escape and do harm. As such, biotech creators and patent holders are properly liable when risk ripens into harm.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.026 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".