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The Influence of Physical and Social Contexts of Eating on Lunch-Time Food Intake Among Southern Ontario, Canada, Middle School Students

2010· article· en· W2059817267 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of School Health · 2010
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMealContext (archaeology)Added sugarFood intakeEnvironmental healthEating behaviorPsychologyFood scienceSugarMedicineObesityGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Among students, little is known about the physical and social context of eating lunch. The objective of this study was to determine if food intake (including the type of food and beverages and portion sizes) was associated with specific aspects of the physical and social lunch environment (location, with whom lunch was consumed, who prepared the food, and where the food was originally purchased). METHODS: A total of 1236 participants (males = 659, females = 566) in grades 6 (n = 359), 7 (n = 409), and 8 (n = 463) from southern Ontario, Canada, completed the Food Behavior Questionnaire during the 2005-2006 academic year. RESULTS: A total of 8159 foods and 2200 beverages were consumed during the lunch meal, which contributed to 552 kcal (SD = 429) or 30% (SD = 16) of total daily energy intake (kcal/day). Higher amounts of energy, meats and alternatives, other foods, fried foods, and pizza were consumed when participants ate in between places or at a restaurant/fast food outlet (compared with at home or school, p < 0.05) and/or when prepared by friends or others (compared with themselves or family members, p < 0.05). A large number of participants (46%) reported consuming sugar-sweetened beverages during lunch, despite a school board-level policy restricting the sales of "junk food," which appears to be brought from home. CONCLUSIONS: Our findings support schools in policy efforts that restrict fast food access (by leaving school grounds, preventing fast food companies from coming onto school grounds, or restricting sugar-sweetened beverage sales in vending machines) and that eating in between places should be discouraged.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.366
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.286
Teacher spread0.271 · 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