Development of the Assessment of Coach Emotions systematic observation instrument: A tool to evaluate coaches’ emotions in the youth sport context
Bibliographic record
Abstract
Current research on emotions in sport focuses heavily on athletes’ intrapersonal emotion regulation; however, interpersonal consequences of emotion regulation are garnering recent attention. As leaders in sport, coaches have the opportunity to regulate not only their own emotions, but also those of athletes, officials, and spectators. As such, the present study set out to develop an observational tool, demonstrating evidence of validity and reliability, for measuring coaches’ overt emotions in the youth sport context. Categories were derived and refined through extensive literature and video review, resulting in 12 categories of behavioural content and eight emotion modifiers ( Neutral, Happy, Affectionate, Alert, Tense, Anxious, Angry and Disappointed). The final coding system is presented herein, complete with supporting evidence for validity and reliability. As a tool for both researchers and practitioners in sport, the Assessment of Coach Emotions (ACE) offers enhanced insight into the contextual qualities underlying coaches’ interactive behaviours.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".