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Record W2033437600 · doi:10.1159/000078166

Benefit Sharing in Smaller Markets: The Case of Newfoundland and Labrador

2003· article· en· W2033437600 on OpenAlexaffabout
Daryl Pullman, Andrew Latus

Bibliographic record

VenuePublic Health Genomics · 2003
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsMemorial University of Newfoundland
FundersHealth Research Board
KeywordsLegislationPopulationBusinessProtocol (science)Scale (ratio)GeographyHomogeneousEnvironmental planningEnvironmental resource managementPolitical scienceMedicineEnvironmental healthCartographyEconomics

Abstract

fetched live from OpenAlex

This case report describes recent efforts in the Canadian province of Newfoundland and Labrador to establish an appropriate benefit-sharing model for human genetic research conducted there. The relatively homogeneous population of this island province has proven to be attractive to the drug development industry. However, unlike large-scale national projects that include broad benefit-sharing arrangements from the outset such as those proposed for places like Iceland and Estonia, there are no plans in Newfoundland and Labrador to establish a large gene bank. Hence a benefit-sharing protocol that will assess individual genetic studies on a case by case basis has been proposed. The province is moving toward legislation to establish a Provincial Health Research Ethics Board (PHREB) that will ensure that all human health research conducted in the province receives local ethics review. The proposed benefit-sharing protocol calls for the establishment of a Standing Committee on Human Genetic Research (SCHGR) that will operate in concert with the PHREB and will ensure that research sponsors enter into appropriate benefit-sharing arrangements with the province.

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)0.012
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.007
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 head0.387
GPT teacher head0.500
Teacher spread0.113 · 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 designObservational
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

Citations7
Published2003
Admission routes2
Has abstractyes

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