Coaches’ Adoption and Implementation of Sport Canada’s Long-Term Athlete Development Model
Bibliographic record
Abstract
This work explores the adoption and implementation of Sport Canada’s long-term athlete development (LTAD) model by coaches and tries to understand the barriers to and enablers of these processes. LTAD adoption was studied in 14 coaches (5 female, 9 male) in seven sports while implementation was assessed among 10 different coaches (2 female, 8 male) from nine sports. Semistructured interviews ascertained coaches’ perceptions of and experiences with the LTAD model in their coaching practice. Coaches adhered to the global vision and general principles of LTAD. However, several barriers to LTAD adoption and implementation were identified. A mismatch between the model’s long-term and the short-term visions of results in sport was perceived as deterrent to LTAD adoption and implementation. Coaches involved in early development sports mentioned a lack of compatibility of LTAD with the demands of their sport. Coaches also perceived complexity in LTAD athlete’s developmental stage determination and the identification of “windows of opportunity” or critical periods. These barriers should be addressed to complete diffusion of LTAD among Canadian coaches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".