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Record W2117252281 · doi:10.1080/01459740.2013.828722

Canadian Residential Schools and Urban Indigenous Knowledge Production about Diabetes

2013· article· en· W2117252281 on OpenAlexfundaboutno aff
Heather Howard

Bibliographic record

VenueMedical Anthropology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsIndigenousContext (archaeology)Urban communityIntervention (counseling)Traditional knowledgeWork (physics)Health careCommunity healthGerontologySociologyNursingMedicineGeographyEnvironmental healthEconomic growthPublic healthEngineering

Abstract

fetched live from OpenAlex

The construction of illness as an inscription on the body of colonization figures importantly among Indigenous community-based service and health care providers. While residential schools and diabetes have both been characterized as products of colonization, little work has been done to examine how they are connected to and informative for health provider practice. The research data presented in this article come from a collaborative urban Indigenous community-based study examining the legacy of negative relationships with food that was instilled in residential schools and used in diabetes intervention. I illustrate how residential school disciplined eating, providing a context for understanding the contemporary production of Indigenous health knowledge and practice in the urban setting, and the diet-related management of diabetes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score0.419

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0150.009
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.008
GPT teacher head0.303
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations38
Published2013
Admission routes2
Has abstractyes

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