Bibliographic record
Abstract
Over the years, sport programmers have struggled to marry the development of excellence in youth sport while encouraging positive participation and personal development (Cote & Hancock, 2016). To assist in bridging this gap, the introduction of physical literacy to sport and physical education has been introduced through the Canadian Sport for Life model. The definition of physical literacy not only includes physical and cognitive outcomes, but also psychological outcomes. Within a youth sport context, coaches and other sport leaders (i.e., volunteers, administrators) are taxed with providing positive and well-rounded sport experiences to children and youth. Coaches and program leaders tend to focus mostly on the development of physical competence but are less confident in the delivery of psychological concepts (McCallister et al., 2000), including those related to the growth of physical literacy (i.e., confidence, motivation). This presentation will discuss aspects of child development and the role of coaches/leaders in understanding physical literacy from a psychological perspective. The presentation will also review a resource, Project SCORE (www.projectscore.ca), that can be used as a tool to help coaches and program leaders to teach confidence, competence, and motivation with youth sport programs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.184 | 0.035 |
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".