Decision-making skills and deliberate practice in elite association football referees
Bibliographic record
Abstract
We examined sport expertise as a function of role. In study 1, referees were better than players in a video-based decision-making task. This provides evidence that there are role-specific skills within one domain or sport. In study 2, we examined the training activities that could be influential in the development of skills in sports officials. Elite association football (soccer) referees retrospectively reported time spent in and perceptions of training activities for three periods: their first year of formal refereeing, 1998 (before formal training programmes were available), and the current year (2003). This allowed us to examine an area of skill with a limited culture of practice, where performance simulations with direct feedback are usually not feasible. The results showed that referees specialize early and, as they develop, they engage in greater volumes and types of training. Competitive match refereeing is considered a relevant activity for skill acquisition that does not fit Ericsson and colleagues' (1993) original definition of deliberate practice. Our findings indicate that actual performance is a significant activity for skill acquisition and refinement.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".