Development of Boccia Throw Test Instrument for Athletes with Cerebral Palsy
Bibliographic record
Abstract
Background: Boccia is an accuracy game for athletes with cerebral palsy. In a Boccia game, the players throw a red- or blue-colored leather ball towards a white-colored target ball called the jack. Points are awarded to the colored balls with the closest distance to the jack. Aims: This development research aims to design a Boccia throw test instrument for novice athletes with cerebral palsy and test the instrument's validity and reliability. Methods: We use research and development with a 6-step instrument development method by Gall, Gall, and Borg. The subject of this research was 20 novice Boccia athletes who completed six trials to test the validity and reliability of the test instrument. Analysis was conducted through corrected item-total correlation and Cronbach’s Alpha using SPSS. Results: This research has produced a boccia throwing test instrument for cerebral palsy athletes with a throwing target in the form of a circle diameter of 25 cm, which is placed 5 meters from the ball throwing area. This instrument has proven its validity and reliability based on the validity value on the corrected item-total correlation > 0.05 and the reliability value on Cronbach's alpha > 0.80. Conclusion: The resulting test instrument is valid and reliable to assess the Boccia throwing accuracy skill in novice players.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".