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Building Community and Social Capital through Children's Leisure in the Context of an International Camp

2005· article· en· W214431146 on OpenAlexaff
Felice Yuen, Alison Pedlar, Roger C. Mannell

Bibliographic record

VenueJournal of Leisure Research · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSocial capitalFocus groupSociologyContext (archaeology)Participant observationPublic relationsQualitative researchSocial engagementCommunity developmentSense of communitySociology of leisureSocial psychologyPsychologyEconomic growthSocial sciencePolitical scienceGeographyEconomics

Abstract

fetched live from OpenAlex

The purpose of the study was to explore the extent to which participation in leisure activities directed towards cooperation and effective communication affected the development of social capital and sense of community in a group of children at an international camp. Methods of data collection included participant observation and focus groups, which included drawings as a part of the focus group procedure. Through an inductive analysis of qualitative data gathered from 32 eleven-year old campers, leisure was observed to provide a common ground for the children's relationship building and the development of shared meanings. The findings suggest that leisure can provide a foundation for the development of shared meanings through the process of participation and social learning, which in turn is conducive to the emergence of social capital and community.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.004
Scholarly communication0.0030.001
Open science0.0010.005
Research integrity0.0000.001
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 head0.106
GPT teacher head0.443
Teacher spread0.337 · 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 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

Citations63
Published2005
Admission routes1
Has abstractyes

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