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Record W4365135523 · doi:10.1177/14034948221139005

Exploring community perspectives on the impacts of COVID-19 on food security and food sovereignty in Nunavut communities

2023· article· en· W4365135523 on OpenAlexafffundabout
Sidney Horlick, Susan Chatwood

Bibliographic record

VenueScandinavian Journal of Public Health · 2023
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsQaujigiartiit Health Research CentreUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsFood securityFood sovereigntyCommunity resiliencePandemicEconomic growthPolitical scienceFood systemsResilience (materials science)Psychological resilienceSovereigntyBusinessCoronavirus disease 2019 (COVID-19)Public relationsDevelopment economicsEconomicsGeographyMedicinePsychologyAgriculturePoliticsDiseaseLawResource (disambiguation)Social psychology

Abstract

fetched live from OpenAlex

BACKGROUND: In Nunavut, where 70% of children are food insecure, many households rely on school breakfast or community food programmes for nourishment. The COVID-19 pandemic and resulting policies to reduce the spread of the disease have the potential to exacerbate existing issues, including increasing food insecurity in households. Funding programmes were implemented to limit the impact of public-health measures on household and community food security. The overall effects of the actions are not yet understood. METHODS: This project used a qualitative approach to examine the determinants of food security and sovereignty and the impact of the COVID-19 pandemic policy responses on these determinants in Arviat and Iqaluit. Narrative analysis applied within a relational epistemology was used to describe the experiences of community members in Iqaluit and Arviat during the COVID-19 pandemic. RESULTS: =4). Key themes included the importance of decolonisation for food sovereignty, the importance of food sharing to communities and the resilience of communities during COVID-19. Community members wished to see greater support and strengthening of the country (locally harvested) food economy to increase knowledge of food and harvesting skill, and for communities to find ways to reach residents who may fall through the cracks during times of need or crisis.

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)0.015
metaresearch head score (Gemma)0.002
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 score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.000
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 head0.361
GPT teacher head0.426
Teacher spread0.065 · 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

Citations5
Published2023
Admission routes3
Has abstractyes

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