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Record W2553777391 · doi:10.1123/jpah.2016-0299

Is our Youth Cycling to Health? Results From the Netherlands’ 2016 Report Card on Physical Activity for Children and Youth

2016· article· en· W2553777391 on OpenAlexaff
Marcella Burghard, Karlijn Knitel, Iris van Oost, Mark S. Tremblay, Tim Takken

Bibliographic record

VenueJournal of Physical Activity and Health · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsChildren's Hospital of Eastern Ontario
FundersUniversiteit UtrechtNational Science Foundation
KeywordsReport cardPhysical activitySedentary behaviorGovernment (linguistics)CyclingActive livingPsychologyMedicineEnvironmental healthPhysical therapyGeography

Abstract

fetched live from OpenAlex

BACKGROUND: The Active Healthy Kids the Netherlands (AHKN) Report Card consolidates and translates research and assesses how the Netherlands is being responsible in providing physical activity (PA) opportunities for children and youth (<18 years). The primary aim of this article is to summarize the results of the 2016 AHKN Report Card. METHODS: Nine indicators were graded using the Active Healthy Kids Global Alliance report card development process, which includes a synthesis of the best available research, surveillance, policy and practice findings, and expert consensus. RESULTS: Grades assigned were: Overall Physical Activity Levels, D; Organized Sport Participation, B; Active Play, B; Active Transportation, A; Sedentary Behaviors, C; Family and Peers, B; School, C; Community and the Built Environment, A; Government Strategies and Investments, INC. CONCLUSIONS: Sedentary behavior and overall PA levels are not meeting current guidelines. However, the Dutch youth behaviors in sports, active transportation, and active play are satisfactory. Several modifiable factors of influence might be enhanced to improve these indicators or at least prevent regression. Although Dutch children accumulate a lot of daily PA through cycling, it is not enough to meet the current national PA guidelines of 60 minutes of moderate-to-vigorous PA per day.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.085
GPT teacher head0.392
Teacher spread0.307 · 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

Citations31
Published2016
Admission routes1
Has abstractyes

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