A REVIEW ON THE CHANGES OF THE EVALUATION SYSTEM AFFECTING ARTISTIC GYMNASTS’ BASIC PREPARATION: THE ASPECT OF CHOREOGRAPHY PREPARATION
Bibliographic record
Abstract
The Code of Points, the International Gymnastics Federation document directing gymnasts’ training process in every Olympic Cycle, evaluates artistic gymnastics performances. The aim of this study was twofold: first to examine the most important changes of the Code of Points since 1996, affecting gymnasts’ basic preparation and in particular the changes concerning choreography. Second, this paper aimed to review the relevant literature on the topic of choreography preparation in artistic gymnastics and to analyze finalists’ performances in official competitions, thus exploring the contribution of choreography preparation in gymnasts’ difficulty score. For the purpose of the present study Women’s Artistic Gymnastics Codes of Points since 1996 were analyzed. In addition, the content of the finalists performances on floor exercises and balance beam in the Olympic Games of London 2012, World Championship in Antwerp, 2013 and European Championship in Moscow 2013 were also analyzed. The results of this study demonstrated that basic preparation of artistic gymnasts is an ongoing process, structured on the principles of “profile elements” and virtuosity of execution. Gymnasts’ basic preparation focuses on choreography as a means of faultless execution and at the same time choreography preparation provides a new direction of developing difficulty while slowing down the “acrobatisation” and preserving the aesthetic quality of the sport.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".