Describing Strategies Used by Elite, Intermediate, and Novice Ice Hockey Referees
Bibliographic record
Abstract
UNLABELLED: Much is known about sport officials' decisions (e.g., anticipation, visual search, and prior experience). Comprehension of the entire decision process, however, requires an ecologically valid examination. To address this, we implemented a 2-part study using an expertise paradigm with ice hockey referees. PURPOSE: Study 1 explored the strategies referees indicated they used to make decisions. For Study 2, we sought to confirm the emergent codes of Study 1 and further examine referee expertise and evaluations of decision making. METHOD: In Study 1, 2 elite, 2 intermediate, and 2 novice referees wore helmet cameras for 1 game and participated in stimulated recall interviews, which were coded using theoretical and focused codes. Study 2 involved focus groups that each watched and commented on 2 helmet camera videotapes from Study 1; 1 videotape consisted of an elite referee's game and the other included an intermediate referee's game. The focus-group data were analyzed using the same coding structure from Study 1. RESULTS: Combined, 3 distinct theoretical codes were identified: (a) primary referee strategies, (b) secondary referee strategies, and (c) cognitive and situational influences on refereeing. Study 1 showed that elite referees demonstrated more sophisticated knowledge of the 3 theoretical codes. In Study 2, elite referees demonstrated enhanced declarative knowledge compared with intermediate and novice participants. CONCLUSIONS: Elite referees have more elaborate knowledge bases than do nonelite referees. In the discussion, we explain our results and link them with the action plan profiles framework.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".