Tactical proficiency among table tennis players with and without intellectual disabilities
Bibliographic record
Abstract
The effect of intellectual impairment on sports performance has received limited attention by researchers. As a contribution to closing this gap, the purpose of the present investigation was to examine the differences in tactical proficiency between table tennis players with and without intellectual disabilities (ID). These groups were matched for training-volume and experience and consisted of 41 male (age = 27±8) and 30 female (age= 28±8) elite players with ID and a reference group of 12 male (age= 24±12) and 5 female (age= 20±9) players without ID. In two different test settings - one a World Championship and the other a training camp - the players in each group performed 60 semi-standardised rallies against the same opponent. Players were told that 12 sets of five identical services would be delivered, and their goal was to return the service with the intention of 'winning the point'. The test results were validated for this study, to compute tactical proficiency scores (maximal score of eight points) for each player. A two-way Analysis of Variance (ANOVA) revealed significantly lower proficiency scores for players with ID than for those without ID. Repeated-measures ANOVA revealed that within each series of five rallies, starting with identical services, all participants were able to significantly improve their tactical proficiency gradually, but players without ID scored 4.3±0.5 from the first ball on, and while athletes with ID only 3.3±0.7 after five balls. The results of this study indicate that ID is associated with decreased tactical proficiency in table tennis.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".