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Record W4403207917 · doi:10.1123/jpah.2024-0442

Physical Activity Report Card Indicators and the United Nations Sustainable Development Goals: Insights From Global Matrix 4.0

2024· article· en· W4403207917 on OpenAlexaff
Diego Augusto Santos Silva, Salomé Aubert, Taru Manyanga, Eun‐Young Lee, Deborah Salvo, Mark S. Tremblay

Bibliographic record

VenueJournal of Physical Activity and Health · 2024
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsCarleton UniversityChildren's Hospital of Eastern OntarioUniversity of OttawaUniversity of Northern British ColumbiaQueen's UniversityUniversity of British ColumbiaActive Healthy Kids
Fundersnot available
KeywordsSustainable developmentGovernment (linguistics)BusinessGlobal healthPerformance indicatorEconomic growthPolitical scienceEnvironmental resource managementEconomicsMarketingHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: The World Health Organization recognizes that physical activity (PA) during childhood is crucial for healthy development, aligning well with the achievement of several United Nations (UN) Sustainable Development Goals (SDGs). This study aimed to explore the associations between 10 key indicators of PA for children and adolescents assessed in the Global Matrix 4.0 project, and the UN SDGs. METHODS: Data from 57 countries/jurisdictions of the Global Matrix 4.0 project were used. The UN SDG indicators were sourced from the SDG Transformation Center, which publishes each country's performance on each of the 17 SDGs. Given the robust evidence supporting plausible links between PA and SDGs 3 (good health and well-being), 9 (industry, innovation, and infrastructure), 11 (sustainable cities and communities), 13 (climate action), and 16 (peace, justice, and strong institutions), these SDGs were investigated. RESULTS: Countries/jurisdictions with good and moderate performance in achieving SDG 3, SDG 9, SDG 11, and SDG 16 had higher grades than countries/jurisdictions with fair performance in achieving these SDGs for the following indicators: Organized Sports and PA, Community and Environment, and Government Investments and Strategies. However, countries/jurisdictions with good performance in achieving SDG 13 had lower grades than countries/jurisdictions with fair performance in achieving SDG 13 for the following indicators: Organized Sports and PA, Community and Environment, and Government Investments and Strategies. CONCLUSIONS: Organized Sports and PA, Community and Environment, and Government Investments and Strategies were the indicators that demonstrated differences between countries/jurisdictions with good and poor performance in achieving the SDGs.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.357
Teacher spread0.335 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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