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Record W1997821786 · doi:10.1080/02614367.2014.994549

Health matters: the social impacts of street-involved youth’s participation in a structured leisure programme

2015· article· en· W1997821786 on OpenAlexaff
Carolyn McClelland, Audrey R. Giles

Bibliographic record

VenueLeisure Studies · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMainstreamYouth studiesSociologyInterpersonal tiesPositive Youth DevelopmentLeisure studiesPublic relationsSocial engagementPsychologyGender studiesPolitical scienceSocial scienceDevelopmental psychologyRecreation

Abstract

fetched live from OpenAlex

In this ethnographically informed study, we used a Foucauldian approach to examine the social impacts of street-involved youth’s participation in a structured leisure programme. Our findings suggest that structured leisure activities help to facilitate social ties between the youth participants as well as the youth and programme staff/volunteers. Nevertheless, we found that structured leisure does not necessarily assist in the formation of relationships between street-involved youth and members of the mainstream community outside of the programme. We show how the ways the youth took up dominant discourses concerning street-involved youth and engaged with technologies of the self-influenced their social relationships and their ties to the community. These findings complicate our understanding of structured leisure’s potential benefits for street-involved youth.

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 score0.005
Threshold uncertainty score0.013

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 communication0.0020.001
Open science0.0000.004
Research integrity0.0010.001
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 head0.211
GPT teacher head0.492
Teacher spread0.281 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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