Understanding the Development of Elite Parasport Athletes Using a Constraint-Led Approach: Considerations for Coaches and Practitioners
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
For the past half-century, the Paralympic Games has continued to grow, evident through increased participation, media recognition, and rising research focus in Para sport. While the competitive pool of athletes has increased, athlete development models have stayed relatively the same. Currently, coaches rely mainly on experiential knowledge, informal communication with colleagues, and theory transferred from able-bodied contexts as main resources to support development for themselves and their athletes. The purpose of this paper was to introduce Newell's constraint-led model and its multidimensional spectrum and practical scope to address the complexities of athlete development. The model consists of three overarching constraint categories (i.e., individual, task, and environment) along with proposed additional sub-categories to capture nuances associated in Para sport in order to provide additional context to coaches regarding athlete development. Utilizing this theoretical framework, we present a holistic approach for coaches and practitioners to consider while addressing athletes' short- and long-term developmental plans. This approach highlights the interactions among factors from a wide range of categories that indirectly and directly impact one another and ultimately influence athletes' developmental processes. It is important to consider the dynamic interaction of constraints over various timescales during development and identify underlying issues to improve athlete experience and maximize developmental opportunities. Coaches and practitioners can use the proposed framework as a guide to key factors to consider for their cohort of athletes. This approach provides a context-specific approach that considers unique factors associated with athletes and their environment.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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