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Record W4225787422 · doi:10.1093/heapro/daac036

Implementing active play standards: a qualitative study with licensed childcare providers in British Columbia, Canada

2022· article· en· W4225787422 on OpenAlexafffundabout
E. Jean Buckler, Louise C. Mâsse, Guy Faulkner, Eli Puterman, Jennifer McConnell‐Nzunga, Patti‐Jean Naylor

Bibliographic record

VenueHealth Promotion International · 2022
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsBC Children's HospitalUniversity of British ColumbiaUniversity of Victoria
FundersSocial Sciences and Humanities Research CouncilBC Children's Hospital
KeywordsMandateThematic analysisCapacity buildingEarly childhood educationQualitative propertyPublic relationsQualitative researchEarly childhoodPsychologyMedical educationBusinessPolitical sciencePedagogyMedicineSociology

Abstract

fetched live from OpenAlex

With an increasing number of children attending regular early childhood education and care (ECEC), this setting presents an opportunity to develop physical activity habits and movement skills of children. These behaviours play an important role in the development and well-being of children. In 2017, an Active Play Standard was introduced in British Columbia, Canada, to mandate practices related to physical activity, screen time and movement skill development in licensed ECEC. A capacity-building initiative including training and online resources was released alongside these guidelines to support implementation. The purpose of this study was to qualitatively examine the barriers and facilitators ECEC practitioners faced in implementing the standard, and to explore the role of the capacity-building initiative. Data were collected via semi-structured telephone interviews with educators (n = 23). Data were coded using thematic analysis and sorted into three major themes influencing provision of physical activity opportunities: attributes and impact of the Active Play standard and capacity-building workshop, characteristics of providers and characteristics of ECEC settings. Future studies should consider targeting factors including organizational culture and climate, and provider capacity to provide physical activity and fundamental movement skill programming, and support for facility level policies and collaborative planning processes that create a positive physical activity culture.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.364
Teacher spread0.343 · 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

Citations9
Published2022
Admission routes3
Has abstractyes

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