Coaching and Transferring Life Skills: Philosophies and Strategies Used by Model High School Coaches
Bibliographic record
Abstract
Whether life skills are developed through sport greatly depends on how coaches create suitable environments that promote the development of youth (Gould & Carson, 2008). The purpose of this study was to examine, using Gould and Carson’s (2008) model of coaching life skills, the philosophies and strategies used by model high school coaches to coach life skills and how to transfer these life skills to other areas of life. Interviews were conducted with both coaches and their student-athletes. Results indicated that coaches understood their student-athletes preexisting make up and had philosophies based on promoting the development of student-athletes. Results also demonstrated that coaches had strategies designed to coach life skills and educate student-athletes about the transferability of the skills they learned in sport. Although variations were reported, coaches and student-athletes generally believed that student-athletes can transfer the skills learned in sport to other areas of life. These results are discussed using Gould and Carson’s model and the youth development literature.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".