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Record W2737104139

Exploring sport involvement and development: A case study of one child-athlete's journey through the sampling years

2014· article· en· W2737104139 on OpenAlexaff
Robert Caratun, Benjamin Alavie, Jessica Fraser‐Thomas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsYork University
Fundersnot available
KeywordsCoachingPsychologyPsychosocialRecreationDevelopmental psychologyAthletesApplied psychologyMedicinePhysical therapyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

The Developmental Model of Sport Participation (DMSP) describes trajectories young athletes commonly follow in their sport participation, involving sampling, specializing, investing, and recreational phases of development (Côté & Fraser-Thomas, 2011). Several physical and psychosocial factors characterize each trajectory (e.g., types of activities, influences of families, coaches, and peers), in turn leading to differing performance, health, enjoyment, and psychosocial development outcomes. While the DMSP has been widely used as a framework to understand youths’ sport development (e.g., McCarthy & Jones, 2007), few studies have explored the interactions among the DMSP’s key factors over time using a holistic framework. The purpose of this longitudinal case study was to examine the sport development of a young athlete throughout the sampling years of the DMSP. Participants included the female child-athlete, her father, mother, and coach. Semi-structured interviews were conducted with participants at yearly intervals, from the time the child was aged seven to ten. In addition, practices and competitions were observed, and the child’s mother completed demographic and sport history questionnaires. Findings offer a comprehensive understanding of the child’s sport development experiences through the lens of key stakeholders, with themes relating to key factors within the DMSP. For example, given the child’s involvement in numerous sporting activities, parents were conflicted between promoting sport diversification or specialization. As the child worked with several coaches over the course of the study, findings shed light on her adaptation – or lack thereof - to different coaching philosophies. Further, the child was a top performer, regularly training/practicing with older athletes, yet her sport enjoyment was inconsistent throughout these experiences. This case study captures some of the nuances of children’s early sport experiences and enhances understanding of how young athletes eventually achieve performance, health, and psychosocial outcomes. Key areas for future research are discussed.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.053
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0160.004
Scholarly communication0.0040.002
Open science0.0030.007
Research integrity0.0030.004
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 head0.192
GPT teacher head0.324
Teacher spread0.132 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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