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Record W2423530761

Towards a Canadian Policy for Patenting Disease Genes

2002· article· en· W2423530761 on OpenAlexaffvenueabout
Stephanie Gallagher

Bibliographic record

VenueDalhousie journal of legal studies · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsDalhousie University
Fundersnot available
KeywordsIntellectual propertyCommodificationMonopolyGenetic testingLaw and economicsLawPolitical scienceBusinessSociologyEconomicsBiologyGenetics
DOInot available

Abstract

fetched live from OpenAlex

Thousands of human genes, many associated with human disease processes and diagnosis, have been patented in Canada. The scope of these patents has restricted public access to genetic testing and raised the question of whether human genetic material should be subject to differential treatment by our patent law regime. The Canadian Intellectual Property Office (CIPO) has failed to offer guidelines on the application of patent laws to genetic material, symptomatic of the broader problem of a lack of strong federal leadership in this area. In this paper I will engage the debate over patenting of human genes specifically as it relates to disease gene patents and will critically discuss various proposals for reform. For the purpose of my discussion I have assumed that access to genetic testing (specifically for breast cancer susceptibility) is desirable, that restricting access to testing is not ethically justifiable and that commodification of human genes can be harmful. Re-establishing an appropriate balance between private and public interests in biotechnology requires patent reform. In arguing for patent reform, I will focus on Myriad Genetics, a company that holds patent rights to breast cancer susceptibility genes [discussed infra] and is attempting to establish a worldwide monopoly on breast cancer susceptibility testing. Myriad's claims have begun to stir a debate in the public over the application of patent law to the human genome and the potential harms of permitting commercial monopolies over genetic testing services.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.197
GPT teacher head0.273
Teacher spread0.075 · 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 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
Published2002
Admission routes3
Has abstractyes

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