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Record W2146472857 · doi:10.1177/1049732314546753

Problematizing “Play-for-Health” Discourses Through Children’s Photo-Elicited Narratives

2014· article· en· W2146472857 on OpenAlexafffundabout
Stéphanie Alexander, Katherine L. Frohlich, Caroline Fusco

Bibliographic record

VenueQualitative Health Research · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversity of TorontoUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchHealth Canada
KeywordsCognitive dissonanceAmbivalenceNarrativeMeaning (existential)PsychologyPublic healthDevelopmental psychologySocial psychologyMedicinePsychotherapistNursing

Abstract

fetched live from OpenAlex

There are growing concerns in many industrialized Western societies about declining opportunities for children to play, and fears that this will have adverse health consequences for them. Informed by anti-obesity efforts, public health institutions have recently begun to advance active forms of play as a way of improving children's physical health; however, promoting play for physical health might reshape meanings of play for children. We conducted photography and interview sessions with 25 Canadian children aged 7 to 11 years to examine their representations of play. Our findings suggest that for children, (a) play is an end in itself, (b) play involves but is more than active play, (c) there is ambivalence about scheduled play, and (d) risk is considered a pleasurable component of play. These findings point to a dissonance between children's play promoted for physical health and the meaning of play for children as emotionally contingent, intrinsically motivated, and purposeless.

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)0.024
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
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 head0.417
GPT teacher head0.624
Teacher spread0.207 · 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 designQualitative
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

Citations30
Published2014
Admission routes3
Has abstractyes

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