Patterns of performance development in elite athletes
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.
Bibliographic record
Abstract
This investigation sought to contrast generalised models of athlete development with the specific pathway trajectories and transitions experienced by 256 elite athletes across 27 different sports. All participants completed the National Athlete Development Survey and within it, the Athlete Development Triangle featuring the differentiation of junior and senior competition experience and progression. Developmental initiation; prevalence, magnitude and direction of pathway trajectory; extent of concurrent junior and senior competitive experience; and variability between sports were examined. Three major trajectories were identified in relation to athlete transition from Nil competition to Elite competition, via junior and senior competition phases. These included Pure ascent (16.4%), Mixed ascent (26.2%) and Mixed descent (57.4%). These were further partitioned into eight sub-trajectories, demonstrating a mix of linear, crossover and concurrent competition profiles. Substantial variability with regard to starting age, pattern of ascent and magnitude of transition was apparent. Non-linear trajectories were experienced by the majority of athletes (83.6%), with pure junior to senior developmental linearity evident in less than 7% of cases. Athletes in cgs sports (those measured in centimetres, grams or seconds) were less likely (43%) to experience a descending trajectory in comparison with non-cgs athletes (70%; p<0.001). The collective findings of this investigation demonstrate that, contrary to the popular pyramidal concept of athlete development, a single linear assault on expertise is rare, and that the common normative junior to senior competition transition is mostly characterised by complex oscillations featuring highly varied transitions. More developmental 'granularity' is needed to advance our understanding of sport expertise.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it