MétaCan
Menu
Back to cohort
Record W4389040563 · doi:10.5304/jafscd.2023.131.015

Food insecurity in Yukon communities during COVID-19: A qualitative study

2023· article· en· W4389040563 on OpenAlexafffundabout
Sara McPhee-Knowles, David Gatensby

Bibliographic record

VenueJournal of Agriculture Food Systems and Community Development · 2023
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of SaskatchewanYukon University
FundersMitacs
KeywordsFood securityFood insecurityQualitative researchFood systemsScope (computer science)PandemicCoronavirus disease 2019 (COVID-19)SociologyPolitical scienceGeographyBusinessAgricultureSocial scienceMedicine

Abstract

fetched live from OpenAlex

Food insecurity increased in Canada during the COVID-19 pandemic; in the Yukon Territory, the Whitehorse Food Bank saw its scope increase sig­nificantly as smaller Yukon communities were requesting deliveries of food while travel restrictions were in place. In this qualitative study, the researchers conducted semi-structured inter­views with food bank clients in Whitehorse and two smaller Yukon communities, as well as repre­sentatives of other organizations that were involved in community food security initiatives. The results revealed five main themes emerging from shared client experiences and impacts from the pandemic: emphasis on the hamper as core food on an ongoing basis, the importance of tradi­tional foods, food insecurity and access, the role of the Whitehorse Food Bank in supporting informal networks in communities, and ideal food situations that focused on an abundance of fresh and land-based foods. The results show some contrast between needs in Whitehorse and needs in smaller, more remote Yukon communities. Because of lim­ited access to fresh foods in communities outside of Whitehorse, merely increasing income supports would not completely alleviate food insecurity for these participants, who they lack physical access as well as economic access to fresh, preferred foods.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.275
GPT teacher head0.462
Teacher spread0.187 · 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

Citations2
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Agriculture Food Systems and Community DevelopmentSame topicFood Security and Health in Diverse PopulationsFrench-language works237,207