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Record W4391964146 · doi:10.1080/19320248.2024.2314185

Food Insecurity and Sleep Duration Among Adults in Manitoba and Saskatchewan: Evidence from the 2015-16 Canadian Community Health Survey

2024· article· en· W4391964146 on OpenAlexaffabout
Joseph Asumah Braimah, Williams Agyemang‐Duah, Daniel Amoak, Evans Batung, Moses Mosonsieyiri Kansanga, Emmanuel Kyeremeh

Bibliographic record

VenueJournal of Hunger & Environmental Nutrition · 2024
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsWestern UniversityToronto Metropolitan UniversityQueen's University
Fundersnot available
KeywordsFood insecurityEnvironmental healthSleep (system call)Community healthDuration (music)Political scienceGerontologyPsychologyGeographySocioeconomicsFood securityMedicineSociologyHealth careAgriculture

Abstract

fetched live from OpenAlex

This study examined the association between sleep duration and food insecurity among Canadian adults (n = 8,406). We employed logistic regression models to estimate the association between sleep duration and food insecurity status among adults in Manitoba and Saskatchewan. The prevalence of short sleep (<7 hours), long sleep (>9 hours), and recommended sleep (7–9 hours) are 42%, 5%, and 53%, respectively. Short sleep duration (RRR = 1.40, p < .05) was found to be significantly associated with food insecurity after controlling for relevant sociodemographic, economic, lifestyle, and health-related variables. We conclude with a discussion of the findings in the context of implications and recommendations for policy and future research.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.013
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.009
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.090
GPT teacher head0.356
Teacher spread0.266 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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