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Record W4307227827 · doi:10.1123/jpah.2022-0321

Association Between Physical Activity Indicators and Human Development Index at a National Level: Information From Global Matrix 4.0 Physical Activity Report Cards for Children and Adolescents

2022· article· en· W4307227827 on OpenAlexaff
Diego Augusto Santos Silva, Salomé Aubert, Kwok Ng, Shawnda A. Morrison, Jonathan Y. Cagas, Riki Tesler, Dawn Tladi, Taru Manyanga, Silvia A. González, Eun‐Young Lee, Mark S. Tremblay

Bibliographic record

VenueJournal of Physical Activity and Health · 2022
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsCarleton UniversityChildren's Hospital of Eastern OntarioUniversity of OttawaUniversity of Northern British ColumbiaQueen's UniversityUniversity of British ColumbiaActive Healthy Kids
Fundersnot available
KeywordsHuman Development IndexGeographyResidenceRural areaPopulationDemographyEnvironmental healthSocioeconomicsHuman development (humanity)MedicineEconomic growthSociology

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this study was to explore the associations between the 10 key indicators of the Global Matrix 4.0 project and human development index (HDI) at a national level according to sex, age, area of residence, and ability levels. METHODS: Information from the 57 countries/localities included in the Global Matrix 4.0 project was compiled and presented according to the HDI of each country/locality for each of the 10 key indicators. Grades were assigned based on the benchmarks of the Global Matrix 4.0 project ranged between "A+" (best performance) and "F" (worst performance). RESULTS: The population subgroups of females, children, rural residents, with/without disabilities from countries/localities with higher HDI performed better in the organized sport and physical activity indicator than their peers from countries/localities with lower HDI. Children and adolescents living in rural areas of countries/localities with higher HDI showed better performance for active play, and children and adolescents living in urban areas of countries/localities with lower HDI showed better performance for the active transportation. Countries/localities with higher HDI showed better grades for sources of influence than the countries/localities with lower HDI. CONCLUSIONS: Physical activity patterns in some population subgroups of children and adolescents differed according to the development level of countries/localities.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.043
GPT teacher head0.379
Teacher spread0.336 · 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 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

Citations29
Published2022
Admission routes1
Has abstractyes

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