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Record W2027751246 · doi:10.1007/s00038-015-0673-z

Beyond nutrition: hunger and its impact on the health of young Canadians

2015· article· en· W2027751246 on OpenAlexafffundabout
William Pickett, Valerie Michaelson, Colleen Davison

Bibliographic record

VenueInternational Journal of Public Health · 2015
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsKingston General HospitalQueen's University
FundersCanadian Institutes of Health ResearchUniversitetet i BergenQueen's UniversityUniversity of St Andrews
KeywordsEnvironmental healthPublic healthDisadvantageLogistic regressionCross-sectional studyMedicineConsistency (knowledge bases)GerontologyPsychologyNursingPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: In a large Canadian study, we examined: (1) the prevalence of hunger due to an inadequate food supply at home; (2) relations between this hunger and a range of health outcomes, and; (3) contextual explanations for any observed associations. METHODS: A cross-sectional survey was conducted of 25,912 students aged 11-15 years from 436 Canadian schools. Analyses were descriptive and also involved hierarchical logistic regression models. RESULTS: Hunger was reported by 25 % of participants, with 4 % reporting this experience "often" or "always". Its prevalence was associated with socio-economic disadvantage and family-related factors, but not with whether or not a student had access to school-based food and nutrition programs. The consistency of hunger's associations with the health outcomes was remarkable. Relations between hunger and health were partially explained when models controlled for family practices, but not the socio-economic or school measures. CONCLUSIONS: Societal responses to hunger certainly require the provision of food, but may also consider family contexts and basic essential elements of care that children need to thrive.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.616
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.282
GPT teacher head0.509
Teacher spread0.226 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations24
Published2015
Admission routes3
Has abstractyes

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