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Record W4391590497 · doi:10.1080/14729679.2024.2312936

Children’s competitive microcultures: an examination of the social organization of rules and roles in gender inclusive and performance-based outdoor play

2024· article· en· W4391590497 on OpenAlexaffabout
Michelle E. E. Bauer, Ian Pike

Bibliographic record

VenueJournal of Adventure Education & Outdoor Learning · 2024
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOutdoor educationPsychologyPedagogyDevelopmental psychologySociologySocial psychology

Abstract

fetched live from OpenAlex

Children’s microcultures consist of small peer communities that they develop with distinct rules and roles operating outside of traditional daily activities. Presently, there is little understanding for how children may develop microcultures during competitive play, where they attempt to outperform their peers. In this study, we address the question, ‘How may competitive outdoor play shape children’s development of microcultures?’ We conducted unstructured interviews with 9- to 13-year-old children (7 girls, 6 boys) and engaged in naturalistic observations of their play in Vancouver, Canada, throughout a two-week period. Findings from our thematic analysis suggest children develop gender-inclusive microcultures during their competitive play and children are evaluated by one another on their physical and cognitive competencies. Importantly, these findings suggest microcultures can afford children with opportunities to participate in thrilling play that may otherwise be restricted by adults. Further, they suggest competition may serve as a catalyst for disrupting gender segregated play.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.302

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.297
Teacher spread0.291 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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