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Record W3043034039 · doi:10.3390/ijerph17145110

The Talent Development Pathway for Elite Basketball Players in China

2020· article· en· W3043034039 on OpenAlexaboutno aff
José Bonal, Sergio Lorenzo Jiménez Sáiz, Alberto Lorenzo Calvo

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2020
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsBasketballEliteExcellenceAthletesContext (archaeology)ChinaPsychologyTalent developmentAnthropometryApplied psychologyElite athletesPolitical scienceSociologyPedagogyPhysical therapyMedicineGeography

Abstract

fetched live from OpenAlex

A large portion of previous sport talent development research has been conducted using Western countries study subjects such as Canadian, Swedish, Spanish, British, or American athletes. However, the factors that affect oriental culture athletes remain an unexplored field. The aims of this investigation were to consolidate the exploration of the pilot study that studied the key factors for Chinese elite basketball players' careers and understand what facts have helped them to achieve the highest sportive level through qualitative research. The pathway to excellence of 11 Chinese elite basketball players were analyzed through a semi-structured interview with different categories such as social context, sport context, tactical factors, or anthropometric factors. Results showed that cultural factors, family tradition, academic studies, coaches, mental strength, training structuration, and international competitions had a great effect and influence in the talent development of Chinese basketball players.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.108
GPT teacher head0.420
Teacher spread0.311 · 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 designOther design
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

Citations26
Published2020
Admission routes1
Has abstractyes

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