Preliminary Validation of an Arabic Version of the Sport Motivation Scale (SMS-28)
Bibliographic record
Abstract
This study aims to validate the Arabic version of the Sport Motivation Scale (SMS-28). SMS-28 is the English version of the French-Canadian scale l’Echelle de Motivation Dans Les Sport, which is based on the self-determination theory. The scale can reliably and validly measure the different forms of motivation toward sport. It consists of different subscales of intrinsic motivation (IM-to know, IM-to accomplish, IM-to experience), extrinsic motivation (identified regulation, introjected regulation, external regulation) and amotivation. The Arabic version of the scale was translated using the transcultural translation procedure. The final script of the translated scale was distributed to a sample of participants, which consists of a group of 208 students at the Faculty of Physical Education at the University of Jordan. The students were randomly selected and completed the scale voluntarily. Analytical analysis including factor analysis, Cronbach Alpha and Pearson correlation analysis were conducted. Results of the factor analysis reflected the validity of the scale, Cronbach Alpha showed adequate levels of internal consistency, while correlation values between the subscales were acceptable and reflected the motivation continuum suggested by the self-determination theory. Thus, an Arabic version of the sport motivation scale has emerged. Future studies using the Arabic version of the scale are encouraged.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".