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Record W4407046286 · doi:10.1177/00084298241313143

Fire in the contemporary cuisines of Indigenous peoples in Canada

2025· article· en· W4407046286 on OpenAlexafffundvenueabout
Laurence Hamel-Charest

Bibliographic record

VenueStudies in Religion/Sciences Religieuses · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndigenousSpiritualityConceptualizationValue (mathematics)FranchiseTasteGeographyEthnologySociologyHistoryEnvironmental ethicsEcologyMedicinePsychology

Abstract

fetched live from OpenAlex

Spiritual dish, medicine wheel flatbread, flamed game and smoked fish are all examples of the intersection of Indigenous food and spirituality. This article explores this intersection by examining the conceptualization of fire in Indigenous cultures in Canada, particularly in Quebec, through an analysis of cuisines. How do contemporary Indigenous cuisines in Canada express their relationship to fire? What is the significance of fire in Indigenous cuisines? What is the symbolic value of smoke, both as a smell and a taste, in Indigenous foods? The analysis is based on two studies: one conducted with a First Nations community in Quebec and another focused on Indigenous restaurants in Canada. The discussion suggests that fire has a relational potential and helps to signify, through cuisine, the connection between Indigenous peoples and the land.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0150.008
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.294
Teacher spread0.248 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes4
Has abstractyes

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