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Record W2886574520 · doi:10.18865/ed.28.s1.247

Commentary: The Invention of Aboriginal Diabetes: The Role of the Thrifty Gene Hypothesis in Canadian Health Care Provision

2018· editorial· en· W2886574520 on OpenAlexaffabout
Travis Hay

Bibliographic record

VenueEthnicity & Disease · 2018
Typeeditorial
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsLakehead UniversityThunder Bay Regional Research Institute
Fundersnot available
KeywordsGeneticistContext (archaeology)IndigenousHealth careMedicineGenealogyHistoryPolitical scienceGeneticsBiologyLawEcologyArchaeology

Abstract

fetched live from OpenAlex

The purpose of this study was to analyze the extent to which the 'thrifty gene hypothesis' remains embedded within regimes of Canadian health care. The thrifty gene hypothesis, formulated by the American geneticist and travelling scientist James V. Neel in 1962, proposed that Indigenous peoples were genetically predisposed to Type 2 diabetes due to the foodways of their ancestors. The hypothesis was functionally racist and based on what biological anthropologists now call 'the myth of forager food insecurity.' Importantly, Neel reconsidered his own hypothesis in 1982 before he ultimately rejected it in 1999; nonetheless, in the mid-1990s, a team of Canadian scientists led by the endocrinologist Robert Hegele of Western University conducted a genetic study on the OjiCree community of Sandy Lake First Nation in northern Ontario. Thereafter, Hegele told the academic world and news media that he had discovered a thrifty gene in Sandy Lake. Like Neel, Hegele later came to reject his own study in 2011. Nonetheless, the 'thrifty gene hypothesis' and Hegele's Sandy Lake study continue to be cited, referenced, and reproduced in the current Clinical Guidelines of the Canadian Diabetes Association, as well as across state-related health literature more broadly. The purpose of this study, then, will be to apply the PHCRP to the thrifty gene hypothesis in a Canadian context.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.325
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.352
Teacher spread0.338 · 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 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

Citations20
Published2018
Admission routes2
Has abstractyes

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