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Let the Children Play: Scoping Review on the Implementation and Use of Loose Parts for Promoting Physical Activity Participation

2016· article· en· W2524425352 on OpenAlexafffund
Natalie Houser, Lindsay Roach, Michelle Stone, Joan Turner, Sara Kirk

Bibliographic record

VenueAIMS Public Health · 2016
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsMount Saint Vincent UniversityIzaak Walton Killam Health CentreDalhousie University
FundersCanadian Institutes of Health ResearchLawson Foundation
KeywordsCLARITYPhysical activityPsychologyLiteracyFocus (optics)PedagogyMedicine

Abstract

fetched live from OpenAlex

Active play has become a critical focus in terms of physical activity participation in young children. Unstructured or child-led play offers children the opportunity to interact with the environment in a range of different ways. Unstructured materials, often called loose parts, encourage child-led play, and therefore may also promote physical activity. The purpose of this scoping review was to determine what is currently known about how loose parts may influence physical activity participation. Following a systematic literature search, a total of 16 articles were retrieved, reviewed and categorized according to: (1) types of loose parts; (2) types of play; and (3) types of thinking. We found that there are currently a range of loose parts being used to support play, but the way in which they are implemented varies and there is a lack of clarity around how they might support the development of active outdoor play and physical literacy skills.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.049
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0100.010
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0030.002
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 head0.120
GPT teacher head0.426
Teacher spread0.306 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations61
Published2016
Admission routes2
Has abstractyes

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