Drift of Patented Genetically Engineered Crops: Rethinking Liability Theories
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
Drift of Patented Genetically Engineered Crops: Rethinking Liability Theories^ I. Introduction The issue of engineered food has generated enormous discussion among consumers, corporations, non-profit organizations, and governments. Proponents of the technology tout engineered food as the solution to world hunger.1 Supporters also argue that engineered crops will lessen the environmental impact of traditional2 agriculture by reducing the use of chemical pesticides and herbicides.3 Opponents of engineered food warn of myriad problems, including allergies in humans,4 pesticide and antibiotic resistance in other plants,5 increased use of pesticides and herbicides,6 loss of biodiversity,7 damage to non-targeted IMAGE FORMULA5 organisms,8 crop failure,9 unexpected changes in the altered plants,10 and ethical considerations.11 Despite these potential concerns, the prevalence of engineered organisms in agriculture is increasing at an alarming rate.12 The pervasiveness of products in food warrants a closer look at some of the risks involved. This Note will focus on one particular problem associated with engineered organisms-genetic in agriculture. The phrase drift is used to describe the problem of inadvertent spreading of organisms (GMOs) from a farm choosing to use that technology to a neighboring farm that has chosen not to include GMOs as part of its crop.13 The Note uses the case of Monsanto Canada Inc. v. Schmeiser 14 as a factual predicate for discussion. Because many GMOs are protected by patents,15 this phenomenon requires a balancing of patent rights against farmers' rights. Courts must evaluate the relative importance of the patent rights of the biotech companies, the farmers' interests, environmental concerns, and long-range economic considerations.16 This Note will argue that the unique nature of the patents involved in genetic cases necessitates a reformulation of these IMAGE FORMULA7 patent infringement claims. Specifically, the Note advocates the addition of the element of intent as a component of an infringement claim for patents of plants. As a secondary response to the problem of genetic drift, this Note will suggest modifications to the patents themselves and the strengthening of common-law remedies for farmers; both techniques could be helpful in rectifying the current problems associated with genetic jurisprudence. II. Scientific and Legal Background on Genetically Altered Foods A. Scientific Background Genetically engineered crops are produced by taking a gene from one organism and inserting it into the genetic make-up of another species.17 The spliced genes are chosen from organisms with some desirable trait lacking in the to-be-modified organism.18 Genes are moved not only between species but also between the plant and animal kingdoms. For example, a coldresistant gene from fish has been inserted into tomatoes to improve their hardiness to cold.19 Because genes are translated from one organism to another, the result is often labeled transgenic.20 The phrases transgenic, genetically engineered, and genetically modified all describe the same process and may be used interchangeably.21 B. Legal History of Genetically Engineered Plants The products of genetic-engineering technology have been patentable since 1980, when the Supreme Court decided the case of Diamond v. Chakrabarty.22 Since that time, thousands of patents have issued for engineered organisms.23 The type of patent held by Monsanto Canada Inc.24 protects not only the genetic material in the seeds purchased but also the next generation of seeds and any plants resulting from a hybrid IMAGE FORMULA11 of engineered plants and non-GMO plants. …
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it