COMFORT ZONES AND OPTIMAL CHALLENGE POINTS: PERSPECTIVES FROM CANADIAN UNIVERSITY WOMEN’S BASKETBALL COACHES
Bibliographic record
Abstract
Abundant research has found that athletes’ mental states impact performance and learning. This paper examines two aspects of players’ mental health: comfort zone and optimal challenge point. While comfort zones have been examined previously and are relatively common in both academic and popular culture, the optimal challenge point (OCP) framework has been less well researched, particularly in relation to team sports. This study examined awareness and use of comfort zones and OCP specifically among Canadian university women’s basketball coaches. This sector was chosen as it represents university coaches in Canada while still comprising a relatively small potential sample. Results of the study show that although the respondent coaches generally are well aware of and use the concept of comfort zones in their coaching, OCP remains less well known despite coaches’ use of many of its principles in their respective practices. Article visualizations:
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".