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Record W4312206603

Intellectual Property over Seeds versus Civil Liberties

2013· article· en· W4312206603 on OpenAlexaboutno aff
Birgit Müller

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
Fundersnot available
KeywordsCivil libertiesIntellectual propertyPolitical scienceLawProperty (philosophy)Civil rightsLaw and economicsSociologyPhilosophyPoliticsEpistemology
DOInot available

Abstract

fetched live from OpenAlex

The spring and summer 2010 had been exceptionally wet in Saskatchewan, so wet that farmers were unable to seed certain fields. Yet some fields were covered thick with beautiful canola plants, which germinated from the seeds that had fallen to the ground at last year’s harvest. The weather was good and the price for canola as well. It was tempting to take the combine harvester and harvest this crop, which would be lower yielding than canola carefully seeded at uniform distances and depth, but which had cost nothing in inputs. However no farmer in the neighbourhood of Colonsay dared to take the step. Although the land belonged to them and they had bought the seed the preceding year they were afraid of intellectual property claims. They remembered well the Saskatchewan farmer Percy Schmeiser who lost his case against Monsanto at the Supreme Court. In 1996, one year after transgenic herbicide resistant canola varieties were introduced, he found herbicide resistant canola plants in his field and reseeded the grains of these volunteers. Monsanto persecuted him for patent infringement right up to the Supreme Court. The Supreme Court ruled that the ownership of the patent over the herbicide resistance gene conferred to Monsanto by extension intellectual ownership

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.002

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 head0.022
GPT teacher head0.189
Teacher spread0.167 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2013
Admission routes1
Has abstractyes

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