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Record W2104600894 · doi:10.3148/72.4.2011.e212

Implementing the Alberta Nutrition Guidelines for Children and Youth: In a Recreational Facility

2011· article· en· W2104600894 on OpenAlexafffundvenueabout
Dana Lee Olstad, Jessica Lieffers, Kim D. Raine, Linda J. McCargar

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2011
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchHealth CanadaUniversity of Alberta
KeywordsRecreationQuality (philosophy)Resource (disambiguation)Environmental healthBusinessMedicineMedical educationPolitical scienceComputer science

Abstract

fetched live from OpenAlex

PURPOSE: In this mixed-methods case study, we explored factors influencing the adoption and implementation of the Alberta Nutrition Guidelines for Children and Youth within recreational facilities, and assessed the impact of their implementation on the food environment. METHODS: Qualitative data were generated via interviews, observations, and document reviews. The quality of the food environment was assessed using validated and newly developed food environment assessment tools. RESULTS: Whereas few barriers existed in terms of adopting the guidelines, implementing them proved much more challenging. Implementation was impeded by concerns about the lack of profitability of healthy items, time, and resource constraints. Guidelines that do not restrict the availability of unhealthy options are better accepted by stakeholders. Implementation of the guidelines supported creation of a healthy food environment, but the availability of healthy items remained very limited within the concession (16%) and vending machines (20%), and children continued to purchase primarily unhealthy items. CONCLUSIONS: Findings suggest that children choose healthy options insufficiently when unhealthy items are present. Thus, although introducing the nutrition guidelines in a nonrestrictive format may have been advantageous in some ways, they should be strengthened over time so that they recommend near or total elimination of unhealthy options.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.096
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
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 head0.203
GPT teacher head0.423
Teacher spread0.221 · 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

Citations33
Published2011
Admission routes4
Has abstractyes

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