Development and Validation of the Attitude Towards Transgression Scale (ATTS)
Bibliographic record
Abstract
Transgression in sport can be defined as overstepping boundaries or limits—or in other words, breaking the rules. Whether exhibited as antisocial behaviour towards teammates or opponents, aggression, or cheating, transgression in sport is widespread and a difficult problem to solve. The aim of this thesis was to contribute to the body of research seeking to understand transgression in sport by developing an effective method of measuring attitude towards rule-breaking among triathletes. The development of the attitude towards transgression scale (ATTS) began with a mixed-methods pilot study that enrolled experienced academics and triathlete participants. A methodical developmental protocol was followed, with the objective of ensuring the creation of a robust measure. For the second phase, a quantitative cross-sectional and correlational design study incorporating 126 experienced United Kingdom (UK)-based triathletes was conducted. The theory of planned behaviour (TPB) was adopted as the theoretical framework, and conceptually the ATTS corresponds to the ‘attitude towards the behaviour’ component of the TPB model. The study aimed to investigate and highlight potential correlations between intention (dependent variable) and attitude (the ATTS), personality, social desirability, athletic identity, and self-control, as well as subjective norm and past behaviour questions developed using the TPB item construction guidelines. For the final phase, a further 162 participants from the UK, United States (US), Canada, and Ireland were recruited. We employed the same quantitative cross-sectional and correlational design with the primary aim of re-examining the ATTS and its effectiveness. The findings suggested that one’s intention was significantly predicted by attitude (ATTS), subjective norm, and past behaviour. The results (to some degree) support the TPB as the theoretical framework. It is hoped that researchers can further test the ATTS to understand its effectiveness across wider sporting contexts.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| 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".