A Model of Perfectionism, Moral Disengagement, Altruism, and Antisocial and Prosocial Behaviors in Wheelchair Athletes
Bibliographic record
Abstract
Two forms of perfectionism were examined in the present study to see whether they predicted prosocial and antisocial behaviors in sport through moral disengagement and altruism in a sample of 327 wheelchair basketball and rugby athletes (M = 33.57 years, SD = 10.51; 83% male). Using structural equation modeling, the following significant direct and indirect effects were found. First, perfectionistic strivings positively predicted perceived prosocial behaviors and altruism. Second, perfectionistic concerns negatively predicted altruism and prosocial behaviors and positively predicted moral disengagement. Third, antisocial behaviors were positively predicted by moral disengagement and altruism. Furthermore, perfectionistic concerns indirectly predicted antisocial behaviors positively through moral disengagement and negatively through altruism. Finally, perfectionistic strivings positively predicted antisocial behaviors through altruism. Results provided partial support for the role of perfectionism in predicting prosocial and antisocial behaviors through moral disengagement among athletes with a disability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".