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Record W4249264933 · doi:10.36950/2018ciss006

Innate talent in sport

2018· article· en· W4249264933 on OpenAlex
Joseph Baker, Nick Wattie

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Issues in Sport Science (CISS) · 2018
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsOntario Tech UniversityYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsContext (archaeology)Value (mathematics)Domain (mathematical analysis)Computer scienceBiology

Abstract

fetched live from OpenAlex

Twenty years ago, Howe, Davidson and Sloboda (1998) provided a state of the science review of innate talent. This paper was extremely influential although much has changed in the two decades since it was published. In this review, we revisit Howe et al’s assessment and discuss current research on innate talent in sport, a domain that was largely ignored in the original review. After re-evaluating Howe et al’s criteria for innate talent we conclude that with the exception of criterion 5 (i.e., talent is domain specific), these criteria are still useful in the context of existing evidence in sport. We subsequently examine two complementary issues: Is the concept of innate talent valid? Does the concept have any utility? We conclude the concept of innate talent is valid but currently has limited utility to those working in high performance sport. We highlight several areas of future research that will ultimately inform the value of innate talent to those working at the frontlines of athlete development.

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.040
GPT teacher head0.380
Teacher spread0.341 · 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