Commentary: The Invention of Aboriginal Diabetes: The Role of the Thrifty Gene Hypothesis in Canadian Health Care Provision
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.033 | 0.040 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".