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Record W4380356031 · doi:10.3390/children10061049

An Observational Study on Play and Physical Activity Associated with a Recreational Facility-Led Park-Based “Loose Parts” Play Intervention during the COVID-19 Pandemic

2023· article· en· W4380356031 on OpenAlexaffabout
Calli Naish, Gavin R. McCormack, Anita Blackstaffe, Levi Frehlich, Patricia K. Doyle–Baker

Bibliographic record

VenueChildren · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsObservational studyRecreationPandemicAttendanceIntervention (counseling)Coronavirus disease 2019 (COVID-19)PsychologyMedicinePolitical sciencePsychiatryDisease

Abstract

fetched live from OpenAlex

Play is a human right, yet opportunities for unstructured play are declining. The COVID-19 pandemic further reduced children's play opportunities. We conducted an observational study of a novel community-based intervention (play hubs) that facilitated unstructured play by offering loose parts in parks (Calgary, Canada) during the pandemic. Our descriptive study included systematic observation using the System for Observing Children's Activity and Relationships During Play (SOCARP) and Tool for Observing Play Outdoors (TOPO) to capture physical activity, play, and social and environment interactions among children participating in the play hubs for 10-weeks in 2021 (n = 160) and 2022 (n = 147). Play hub attendance was low. Most children observed were aged 5 to 12 years (2021: 93% and 2022 98%), with boys and girls represented (2021: 58% male/42% female and 2022: 52% male/48% female). Standing, sitting, and moderate activity were common activities. Physical, exploratory, and expressive play were common, while digital, bio, and rule-based play were less common. Children typically played alone or in small groups and engaged with loose parts or played in the open spaces. The play hubs encouraged unstructured play and promoted positive social interactions among children, despite the challenges of implementing a community-based intervention under pandemic public health restrictions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.974

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 studies0.0010.000
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 head0.158
GPT teacher head0.399
Teacher spread0.241 · 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
Published2023
Admission routes2
Has abstractyes

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