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Record W2796440288 · doi:10.1111/chso.12268

Unsettling Food Security: The Role of Young People in Indigenous Food System Revitalisation

2018· article· en· W2796440288 on OpenAlexaboutno aff
Caroline Bagelman

Bibliographic record

VenueChildren & Society · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousFood securityFood systemsPolitical scienceExperiential learningFood sovereigntySociologyFood insecurityNeglectEconomic growthGeographyLawPsychologyEcologyEconomics

Abstract

fetched live from OpenAlex

Official assessments of Canadian food security, which greatly inform policy and perception, paint an insufficient picture of the ways many Indigenous peoples, and in particular Indigenous children who are most impacted by food insecurity, actually experience and understand the problem. This article begins with a discussion of how these metrics neglect the vital connection between access to Indigenous food systems and Indigenous food security. To address the serious food insecurity experienced by Indigenous peoples, this connection must be acknowledged, and revitalisation of these food systems, which are damaged by settler‐colonial practices, must become a focus of the discourse and action. Indigenous elders believe children will be pivotal in revitalisation. In this spirit, this article traces experiential learning projects on revitalisation, in which young people unsettle the settler discourse of food security and take action in small but important ways.

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)0.008
metaresearch head score (Gemma)0.006
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 score0.105
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.021
Scholarly communication0.0070.004
Open science0.0010.010
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.285
Teacher spread0.272 · 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

Citations27
Published2018
Admission routes1
Has abstractyes

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