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Record W3114763500 · doi:10.3389/fsufs.2020.596237

“The Old Foods Are the New Foods!”: Erosion and Revitalization of Indigenous Food Systems in Northwestern North America

2020· article· en· W3114763500 on OpenAlexafffund
Leigh Joseph, Nancy J. Turner

Bibliographic record

VenueFrontiers in Sustainable Food Systems · 2020
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of CanadaPierre Elliott Trudeau FoundationTula Foundation
KeywordsIndigenousFood systemsPsychological resilienceGeographyGovernment (linguistics)Traditional knowledgeFood securityEcologyAgricultureBiologyPsychology

Abstract

fetched live from OpenAlex

The global “nutrition transition” has had an immense impact on Indigenous Peoples of Northwestern North America. From an original diet comprised of mostly local plant and animal foods, including salmon, game, diverse plants, seaweed and other marine foods, many Indigenous people are now eating mostly imported, refined marketed foods that are generally less healthy, and many are at risk of diet-related diseases such as type 2 diabetes. Nevertheless, Indigenous people have always valued their ancestral foods, and over the last few decades there have been many initiatives throughout the region to restore and revitalize these original foods, and to re-learn Indigenous methods of processing and harvesting them. In this paper we describe the original Indigenous food systems in the study region, and the methods used to sustain and promote the ancestral food species and habitats. We then discuss the impacts of colonization, and describe recent and ongoing Resilience and Resurgence in relation to ancestral foods and food practices, including firsthand experiences with renewing food traditions. These initiatives are often connected with language revitalization and cultural resurgence programs. Led by Indigenous communities, they are undertaken with support of academic, government, and other partners. In all, they have resulted in stronger, more vibrant cultures and generally healthier communities.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.272
Teacher spread0.251 · 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 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

Citations62
Published2020
Admission routes2
Has abstractyes

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