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Survey of canteens and food services in Victorian schools

2005· article· en· W2133606651 on OpenAlexaboutno aff
Bronwyn Maddock, Carol Warren, Anthony Worsley

Bibliographic record

VenueNutrition & Dietetics · 2005
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersDepartment of Education and TrainingDeakin University
KeywordsFood serviceQuarter (Canadian coin)Government (linguistics)Quality (philosophy)Service (business)MedicineBusinessPsychologyEnvironmental healthMarketingMedical educationGeography

Abstract

fetched live from OpenAlex

Abstract Objective: To examine the characteristics of food services in Victorian government primary and secondary schools. Design and methods: A cross‐sectional postal survey of all high schools and a random sample of one quarter of primary school respondents in Victoria. A ‘School Food Services and Canteen’ questionnaire was administered by mail to the principal of each school. Subjects: Respondents included principals, canteen managers and home economics teachers from 150 primary and 208 secondary schools representing response rates of 48% and 67%, respectively. Main outcome measures: Responses to closed questions about school canteen operating procedures, staff satisfaction, food policies and desired additional services. Data analyses: Frequency and cross‐tabulation analyses and associated χ 2 ‐tests. Results: Most schools provided food services at lunchtime and morning recess but one‐third provided food before school. Over 40% outsourced their food services, one‐third utilised volunteer parents, few involved students in canteen operations. Half of the secondary schools had vending machines; one in five had three or more. Secondary school respondents were more dissatisfied with the nutritional quality of the food service, and expressed more interest in additional services than primary respondents. Schools with food policies wanted more service assistance and used volunteer parents, student and paid canteen managers more than schools without policies. Conclusion: Most schools want to improve the nutritional quality of their food services, especially via school food policies. There is a major opportunity for professional organisations to advocate for the supply of healthier school 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)0.000
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 score0.008
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.024
GPT teacher head0.279
Teacher spread0.255 · 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 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

Citations12
Published2005
Admission routes1
Has abstractyes

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