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Record W3152476169 · doi:10.1080/07409710.2021.1901385

Can selling traditional food increase food sovereignty for First Nations in northwestern Ontario (Canada)?

2021· article· en· W3152476169 on OpenAlexafffundabout
Keira A. Loukes, Celeste Ferreira, Janice Cindy Gaudet, Michael A. Robidoux

Bibliographic record

VenueFood and Foodways · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of AlbertaUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndigenousFood sovereigntySovereigntyResource (disambiguation)Food securityOverexploitationGeographyEconomic growthEconomyPolitical scienceEconomicsAgricultureLawEcologyPolitics

Abstract

fetched live from OpenAlex

The disparity between rates of food insecurity experienced in households across Canada (8.3%) and in Indigenous households specifically (nearly half) is alarming. Many previous studies have demonstrated the physical, spiritual, mental, social and emotional benefits of consuming traditional foods (primarily wild animal food sources and wild edible plants), yet many Indigenous peoples in northern Ontario feel they do not have access to enough of them. Our research engaged in conversation with sixteen participants from four different First Nations communities in northern Ontario to explore the potential application of Greenland’s “Country Food Market” (CFM) as a model to increase accessibility of traditional food while maintaining community sovereignty over the resource. In this model, full-time hunters are financially sustained through selling their harvest at local markets. While participants were curious about the potential an economy around traditional food could have for improving access, this was tempered by cultural ethics, teachings and laws which instruct hunters to share their food and by concerns of resource overexploitation. As our research confirms, conversations and actions must move away from a binary approach to the question—either to sell or not to sell—and move toward a diverse range of economic models that center Indigenous peoples’ sovereignty.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.055
GPT teacher head0.268
Teacher spread0.213 · 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 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

Citations19
Published2021
Admission routes3
Has abstractyes

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