Crossing sexual barriers: Predictors of sexual guilt and sexual anxiety among young Canadian and American Muslim adults
Bibliographic record
Abstract
The current study tested two exploratory path models predicting sexual guilt and sexual anxiety in young Muslims adults living in Canada and the United States. Using path analysis, I examined the joint influence of background (religiosity, perceived parental sexual attitudes, and gender) and attitudinal (sexual attitudes, gender role attitudes, and sexual double standard) factors on sexual guilt and sexual anxiety. Surveys were completed by 403 Canadian and American young heterosexual Muslim adults (ages 17–35). Most participants (79.4%) were women, approximately one-third of the participants were born outside Canada or the United States, and half identified as students. Most participants identified as either South Asian (43.1%) or Arab (25.1%) and the majority had either an undergraduate (32.3%) or graduate (37.2%) degree. In the final two path models, religiosity both directly and indirectly predicted sexual guilt and anxiety while sexual attitudes, belief in the sexual double standard, and gender role attitudes partially mediated this relationship. Gender role attitudes were strongly related to participants’ support for the sexual double standard, while gender was not a predictor of sexual guilt or anxiety. Perceived parental attitudes had no predictive value, possibly being redundant with religiosity. The path models revealed complex and interesting relationships between the variables which have various implications for young Muslim adults as well as the practitioners who work with them.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".