Sleep and Fatigue of Elite Circus Student-Artists During One Year of Training
Bibliographic record
Abstract
AIMS: The development of elite circus artists requires extensive technical and artistic training, as well as a commensurate level of physical preparation in readiness for a demanding professional career as a performance artist. While sport research has identified the importance of monitoring sleep and fatigue in athletes to optimize performance and to prevent illness and injury, not a single study of circus artists exists. This study provides a longitudinal examination of sleep and fatigue in elite circus student-artists. METHODS: 92 student-artists (60 male, 32 female) were analyzed at 4 strategic time points over a preparatory year. At each time point, sleep parameters (duration, quality and latency), ratings of perceived exertion (RPE), wakefulness, and fatigue were obtained using questionnaires. RESULTS: Student-artists attained an average nightly sleep of 8 hours, 27 minutes, exceeding the recommended durations for general populations and those self-reported in athletes. The majority of the artists also indicated acceptable sleep latency (87%) and quality (83%) scores. Sleep parameters remained consistent throughout the year despite significant variations in training load and fatigue. Sleep parameters were not substantial predictors of overall fatigue. Fatigue covaried with yearly variation in sessional training loads. CONCLUSIONS: Although improvement in sleep could be postulated as a means to mitigate fatigue, it is likely that strategies aimed at optimizing the loading profile and additional recovery techniques be a first line approach.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".