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Record W2096053659 · doi:10.1080/10413200802163549

Examining Adolescent Sport Dropout and Prolonged Engagement from a Developmental Perspective

2008· article· en· W2096053659 on OpenAlexaff
Jessica Fraser‐Thomas, Jean Côté, Janice Deakin

Bibliographic record

VenueJournal of Applied Sport Psychology · 2008
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsQueen's UniversityYork University
Fundersnot available
KeywordsPsychologyCoachingDropout (neural networks)ClubAthletesPerspective (graphical)PsychosocialDevelopmental psychologyDevelopmental MilestoneErikson's stages of psychosocial developmentPhysical therapyMedicine

Abstract

fetched live from OpenAlex

This study examined youth sport dropout and prolonged engagement from a developmental perspective focusing on physical and psychosocial factors. Twenty-five dropout and 25 engaged adolescent swimmers, matched on key demographic variables, participated in a retrospective interview. Results indicated that dropouts were involved in fewer extra-curricular activities, less unstructured swimming play, and received less one-on-one coaching throughout development. Dropouts reached several developmental milestones (i.e., started training camps, started dry land training, and were top in club) earlier than engaged athletes. Dropouts were more likely to have had parents who were high-level athletes in their youth, were more likely to be the youngest in their training group, and were less likely to have a best friend at swimming. Findings are discussed in relation to past research; future directions and implications for researchers, sport programmers, coaches, and parents are suggested.

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)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.059
GPT teacher head0.318
Teacher spread0.259 · 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

Citations301
Published2008
Admission routes1
Has abstractyes

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