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Record W2091152063 · doi:10.1080/19398440802673275

High school athletes’ perspectives on support, communication, negotiation and life skill development

2009· article· en· W2091152063 on OpenAlexafffund
Martin Camiré, Pierre Trudel, Tanya Forneris

Bibliographic record

VenueQualitative Research in Sport and Exercise · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsAthletesNegotiationLife skillsPsychologyApplied psychologyPositive Youth DevelopmentMedical educationDevelopmental psychologyPedagogyMedicinePhysical therapyPolitical science

Abstract

fetched live from OpenAlex

There is a widespread belief that sport can be used as a tool to promote life skills and positive youth development. However, little research has examined athletes’ perspectives on the development of life skills in school‐based sport programmes, in which a vast amount of youth are involved. In addition, research has yet to examine how youth experience support, communication, and negotiation processes with parents and coaches in high school sport, elements that play a crucial role in life skill development. Taking this into consideration, the purpose of the study was to document high school athletes’ perspectives on support, communication, negotiation and life skill development. Results indicated that: (1) while variability was observed, many athletes believed they were able to negotiate many aspects of their sport participation with parents and coaches, (2) a large number of athletes believe they received adequate support from parents and were able to communicate with coaches, and (3) athletes believed high school sport participation allowed them to develop a number of life skills that could be transferred to other life domains.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.005
Scholarly communication0.0050.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.096
GPT teacher head0.459
Teacher spread0.363 · 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

Citations121
Published2009
Admission routes2
Has abstractyes

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