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Record W2885427592

Life skills development in young high-level athletes

2018· article· en· W2885427592 on OpenAlexaffabout
Helene Jørgensen

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLife skillsPsychologyPositive Youth DevelopmentAthletesSocial skillsContext (archaeology)Developmental psychologyPromotion (chess)Skills managementApplied psychologyMedical educationPedagogyMedicinePolitical science
DOInot available

Abstract

fetched live from OpenAlex

The purpose of the current study was to examine the development of life skills through sport participation among young high-level athletes who are part of a talent development program. Life skills are identified as an outcome of positive youth development (PYD; Holt, 2016), which is a commonly used framework in youth sport research with a focus on using sport to develop well-rounded individuals (Fraser-Thomas, Côté, & Deakin, 2005). Talent development in sport, on the other hand, tends to focus on the development of better athletes. However, researchers have suggested that PYD and talent development are not necessarily mutually exclusive aspects of high-level youth sports (Strachan, Fraser-Thomas, & Nelson-Ferguson, 2016). That is, talent development programs can achieve PYD outcomes if an inclusive approach is present, emphasizing the teaching of both athletic and life skills (Harwood & Johnston, 2016).\n\nTo date, PYD within talent development programs has not been extensively studied. The current study addresses this gap in the literature using a qualitative approach. Individual semi-structured interviews were conducted with nine young high-level athletes (5 female, 4 male, Mage = 19.2 years, SD = 1.2) from the Canadian junior biathlon national team. Interviews focused on what life skills were developed through sport participation, how they were learned, and how the athletes transferred these from sport to other life settings. The data was analyzed using Thorne’s (2016) interpretive description (ID) methodology. The model of PYD through sport (Holt et al., 2017) was used as a conceptual framework to develop the interview guide and organize the results (explaining what life skills are developed). Three categories were identified, namely: life skills learning contexts, PYD climate, and implicit processes. The results revealed that life skills were learned in multiple contexts (i.e., school, work, home). In sport, social agents (i.e., parents, coaches, peers) create a PYD climate that can contribute to athletes’ development of life skills. Athletes revealed implicitly learning life skills through cognitive processes of observational learning and reflections related to experiences, both within and outside sport. A key applied implication of the findings is that coaches and sport psychologists should consider initiatives aimed at allowing development of life skills through implicit transfer in young high-level athletes.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.056
GPT teacher head0.309
Teacher spread0.253 · 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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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