MétaCan
Menu
Back to cohort
Record W2263239775

Plants, Torts, and Intellectual Property

2006· article· en· W2263239775 on OpenAlexaboutno aff
Stephen R. Munzer

Bibliographic record

VenueSSRN Electronic Journal · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
Fundersnot available
KeywordsTrespassIntellectual propertyStatuteTortLaw and economicsLiabilityLawPatent infringementBusinessProperty (philosophy)Political scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

This article makes the case for improving current systems for protecting plants and intellectual property rights in them. First, the U.S. system of separate and divergent intellectual property protection of new plants depending on the mode of propagation should be scrapped. A single statute for all plant varieties, as botanically defined, should complement utility patents. Second, on the matter of gene flow/genetic drift, there should be an alternative legal scheme if pervasive and enduring prejudice - whether pro or con genetically engineered crop plants - disrupts the application of otherwise fair rules of tort law. Third, a landowner should not be liable for patent infringement even for knowingly using genetically modified seeds or pollen that insects or winds carry onto his or her land from neighboring property. Monsanto Canada Inc. v. Schmeiser, (2004) 239 DLR (4th) 271 (Can.), was in significant part wrongly decided. What ties these proposals together is the late Professor Harris's concept of trespassory rules. The first and third proposals revise the trespassory rules applicable to intellectual property rights in plants. The second proposal conditionally adjusts the trespassory rules in the law of tort - especially those of negligence, trespass, nuisance, and strict liability - that govern neighboring farmers.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.198
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicGenetically Modified Organisms ResearchFrench-language works237,207