Determining Validity and Reliability of Doping Behavior Measurement Instrument in Young Athletes Society
Bibliographic record
Abstract
The purpose of this study is to determine validity and reliability of doping behavior questionnaire. In order to do so, 20-item doping behavior level measurement questionnaire used in a similar study by Claude Goulet et al in Quebec, Canada, was made ready for distribution after being translated, assessed in terms of writing, modification of errors as well as updating on prohibited materials and removing some of the prohibited materials titles considering the specific cultural issues of the country. In this study, 373 young athletes of Pakdasht Township (197 girls and 176 boys) participated. In order to answer each question, 5 answers were considered based on Likert 5-valuation scale (from zero score with “No, I do not use” expression up to score five with “Yes, I usually use” expression) were considered which should have been answered. Cronbach’s Alpha coefficient method is used to determine the questionnaire internal stability, while confirmatory factor analysis (CFA) was applied to validate structure. The fitting indicators were used to test fitting of the model, including: 1. Wellness indicators, including AGFI, GFI, NFI and badness indicators, including X 2 /df and RMSEA, were used.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".