MétaCan
Menu
Back to cohort
Record W4411887678 · doi:10.3390/youth5030064

Sport, Physical Activity, and Health Inequalities Among Youth Who Are Incarcerated: Perspectives of Youth Custody Workers in Ontario, Canada

2025· article· en· W4411887678 on OpenAlexafffundabout
Mark Norman, Rubens Heller Mandel

Bibliographic record

VenueYouth · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsSt. Francis Xavier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInequalityCriminologyPsychologySociologyGender studiesPolitical science

Abstract

fetched live from OpenAlex

The current article seeks to understand, and critically analyze the implications of, how youth custody workers understand the relationship between sport, physical activity, and health among youth who are incarcerated. Data was collected through surveys (n = 15) and semi-structured interviews (n = 16) with youth custody workers in Ontario, Canada. We present and analyze three themes emerging from participants’ narratives: the potential for sport and physical activity to contribute, in a holistic way, to the physical, mental, and social health of youth who are incarcerated; the possibility for sport and physical activity to create space for building “therapeutic alliances” between staff and youth, which can improve the mental and social health of youth who are incarcerated; and perceptions of health deficits among youth who are incarcerated and their implications for social inequality. Through an analysis of these themes, we deepen the limited scholarly analysis of sport, physical activity, and health among young persons who are incarcerated and connect these discussions to broader considerations of social determinants of health (that is, structural and social factors that create health inequities) as a matter of social justice.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.204
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.305
Teacher spread0.270 · 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.

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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueYouthSame topicCriminal Justice and Corrections AnalysisFrench-language works237,207