MétaCan
Menu
Back to cohort
Record W1996675543 · doi:10.1186/1471-2458-13-970

Community food program use in Inuvik, Northwest Territories

2013· article· en· W1996675543 on OpenAlexafffundabout
James D. Ford, Marie‐Pierre Lardeau, Hilary Blackett, Susan Chatwood, Denise Kurszewski

Bibliographic record

VenueBMC Public Health · 2013
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsInstitute for Circumpolar Health ResearchMcGill University
FundersCanadian Institutes of Health ResearchHealth CanadaArcticNet
KeywordsFood securityMedicineArcticWork (physics)Focus groupFood insecurityFood systemsEconomic growthEnvironmental healthGeographyBusinessMarketingEngineeringAgricultureEcology

Abstract

fetched live from OpenAlex

BACKGROUND: Community food programs (CFPs) provide an important safety-net for highly food insecure community members in the larger settlements of the Canadian Arctic. This study identifies who is using CFPs and why, drawing upon a case study from Inuvik, Northwest Territories. This work is compared with a similar study from Iqaluit, Nunavut, allowing the development of an Arctic-wide understanding of CFP use - a neglected topic in the northern food security literature. METHODS: Photovoice workshops (n=7), a modified USDA food security survey and open ended interviews with CFP users (n=54) in Inuvik. RESULTS: Users of CFPs in Inuvik are more likely to be housing insecure, female, middle aged (35-64), unemployed, Aboriginal, and lack a high school education. Participants are primarily chronic users, and depend on CFPs for regular food access. CONCLUSIONS: This work indicates the presence of chronically food insecure groups who have not benefited from the economic development and job opportunities offered in larger regional centers of the Canadian Arctic, and for whom traditional kinship-based food sharing networks have been unable to fully meet their dietary needs. While CFPs do not address the underlying causes of food insecurity, they provide an important service for communities undergoing rapid change, and need greater focus in food policy herein.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.000
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 head0.163
GPT teacher head0.413
Teacher spread0.250 · 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 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

Citations34
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueBMC Public HealthSame topicIndigenous Studies and EcologyFrench-language works237,207