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Record W2120690708 · doi:10.1123/jpah.2014-0165

Results from England’s 2014 Report Card on Physical Activity for Children and Youth

2014· article· en· W2120690708 on OpenAlexaboutno aff
Martyn Standage, Hannah J. Wilkie, Russell Jago, Charlie Foster, Mary A. Goad, Sean P. Cumming

Bibliographic record

VenueJournal of Physical Activity and Health · 2014
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersLoughborough University
KeywordsReport cardPhysical activityGovernment (linguistics)PsychologyMedical educationMedicinePhysical therapyPedagogy

Abstract

fetched live from OpenAlex

BACKGROUND: The Active Healthy Kids 2014 England Report Card aims to provide a systematic assessment of how England is performing in relation to engaging and facilitating physical activity (PA) in children and young people. METHODS: The systematic methods and processes that underpin the Active Healthy Kids Canada Report Card were used and adapted. Data and evidence were consolidated, reviewed by a panel of content experts, and used to inform the assignment of letter grades (A, B, C, D, F) to 9 core indicators related to PA. RESULTS: Children's Overall Physical Activity received a grade of C/D. Active Transportation and Organized Sport Participation received grades of C and C-, respectively. The indicators of School and Community and the Built Environment were graded favorable with grades of A- and B, respectively. Active Play, Sedentary Behaviors, Family and Peers, and Government Strategies and Investments were graded as INC (incomplete) due to a lack of nationally representative data and/or as a result of data not mapping onto the benchmarks used to assign the grades. CONCLUSIONS: Substantial provision for PA opportunities in England exists. Yet more effort is required to maximize use of these resources to increase PA participation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.540
Threshold uncertainty score0.926

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.003

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 head0.035
GPT teacher head0.333
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2014
Admission routes1
Has abstractyes

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