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Record W6906399969 · doi:10.17605/osf.io/xvq5d

Perspectives on the challenges and successes of school-based nutrition programs in Canada: a scoping review protocol

2022· other· en· W6906399969 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2022
Typeother
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)Principal (computer security)Key (lock)Function (biology)Systematic reviewProgram evaluation

Abstract

fetched live from OpenAlex

This is a protocol for a scoping review of perspectives on the challenges and successes of school-based nutrition programs in Canada. This review will aim to answer the following questions: 1. What are the challenges and successes regarding school-based nutrition programs in Canada? 2. Whose perspectives do these challenges and successes concern (parents/caregivers, children, school administrators, teachers, volunteers, stakeholders)? 3. What types of school-based nutrition programs do these challenges and successes concern (snack program, lunch program, breakfast program)? Given the demand for a national school food program in Canada, research is necessary to ensure the maximum effectiveness of program design and delivery. An important angle to examine is the perspectives of key groups and stakeholders, as they play a principal role in the function of existing programs. The objectives of this scoping review are to: 1. Discover the challenges and successes of school-based nutrition programs in Canada grounded in the perspectives of different groups 2. Determine whose perspectives are represented in the literature 3. Determine what challenges and successes are associated with different types of school-nutrition programs Through this scoping review, we hope to recognize the challenges and successes embedded in the experiences of key groups and stakeholders, to define key domains that can be used to direct future studies and inform a framework for a national school food policy.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.469
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.377
Teacher spread0.308 · 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.

Study designSystematic review
Domainnot available
GenreProtocol

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

Citations0
Published2022
Admission routes1
Has abstractyes

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