MétaCan
Menu
Back to cohort
Record W1526042368

The Creation of University Intellectual Property: Confidential Information, Data Protection, and Research Ethics

2010· article· en· W1526042368 on OpenAlexaffabout
Mark Perry, Margaret Ann Wilkinson

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldComputer Science
TopicLaw, AI, and Intellectual Property
Canadian institutionsWestern University
Fundersnot available
KeywordsIntellectual propertyConfidentialityData Protection Act 1998Political scienceContext (archaeology)Statutory lawPublic administrationLibrary scienceLawGeographyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Protection of commercial confidences is both required as part of the intellectual property provisions of current trade agreements and routinely prerequisite for achieving patent protection. This paper discusses the protection of such commercial confidences and the relationship of this protection with the statutory regime in Canada of personal data protection, but does so within the specific context of an examination of these matters in light of the governance of the processes of research conducted in universities. The nexus of university research and commercial research occurs frequently - for example, in the area of the development and testing of drugs in Canada. The paper demonstrates that there are problems in bringing together and integrating the law of protection of confidential information and personal data protection with university practices in Canada. We analysed the research policies of research-intensive public universities across Canada; the Tri-council policy statement, which governs their research practices; and the legal requirements applicable to the universities in Canada's provinces. The paper demonstrates that there is a disjunction between the law, university policies, and Tri-Council policy.

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)0.011
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0020.001
Research integrity0.0000.004
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 head0.060
GPT teacher head0.298
Teacher spread0.238 · 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.

Study designTheoretical or conceptual
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
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicLaw, AI, and Intellectual PropertyFrench-language works237,207