Development and Validation of the Attitude toward Sexual Aggression against Women (ASAW) Scale
Bibliographic record
Abstract
There is consensus in the social psychological literature that attitudes (i.e., positive or negative evaluations of a psychological object) can be important determinants of behaviour. To facilitate more rigorous research on the relationship between attitudes and sexually aggressive behaviour, the purpose of this thesis was to develop and validate a measure of attitudes toward sexual aggression, namely, the Attitude toward Sexual Aggression against Women (ASAW) scale. To develop the ASAW, a large pool of potential items designed to assess favourable or unfavourable evaluations of a wide range of sexually aggressive behaviours was administered to three independent samples of men from the community. Items were selected based on psychometric and structural analyses, with the primary objective of selecting non-redundant items with the highest response variance (to reduce floor effects). The resulting 13-item scale demonstrated excellent internal consistency and factor analyses suggested it is unidimensional. To test the validity of the ASAW's scores, I conducted two separate studies. The first study provided preliminary evidence of discriminant and incremental validity. Factor analyses indicated that ASAW items were distinct from the items of three commonly used measures of offence-supportive cognition, and that the ASAW explained unique variance in sexually aggressive behaviour after accounting for these other measures. The second study consisted of an experimental test of construct validity based on following reasoning: if scores on the ASAW are sensitive to a well-established attitude-change manipulation (i.e., persuasive communication; Stiff & Mongeau, 2016), this would suggest that the ASAW is measuring attitudes toward the target of the manipulation. Results of the randomized experiment were mixed, suggesting that scores on the ASAW tended to be sensitive to the attitude-change manipulation, but not significantly more so than a measure of a related but distinct construct (i.e., rape myth acceptance). Taken together, these studies provide preliminary evidence for the ASAW's validity, including structural, discriminant, incremental, and construct validity. If additional tests provide more conclusive evidence of construct validity, then the ASAW should be used in future research to examine the role that attitudes may play in the perpetration of sexual aggression against women.
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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".