Application of the Theory of Gender and Power to Relationships and Experiences among Middle Eastern and/or Arab Canadians
Bibliographic record
Abstract
Background. The study explored associations between factors derived from the application of the Theory of Gender and Power (TGP) as they relate to HIV-risk behaviour among Middle Eastern/Arab-Canadians. This area deserves increased attention, as the proportion of HIV incident cases among Canadian women—due to heterosexual transmission—is increasing. \n \nMethods. A web-based survey was administered to Middle Eastern/Arab-Canadians who were aged 18-35 years, of Middle Eastern and/or Arab descent, living in Canada, heterosexual, and in a relationship. Multivariate regression analyses were used to assess factors associated with condom-use risk and lifetime number of sexual partners. Analyses were stratified by gender. \n \nResults. The study sample consisted of 157 participants, with more female participants (65.38%), and a mean age of 22.71 years. Females were more likely to have an older partner and more likely to be virgins, compared to males. Only a third (27.45%) of sexually active participants in this sample reported using condoms every time they have sex and participants reported a mean of 4.31 lifetime sexual partners. Factors associated with both condom-use risk and lifetime number of sexual partners varied greatly between genders. Among females, having low self efficacy towards practicing safer sex was predictive of condom-use risk. Among males, not being worried about getting HIV was predictive of condom-use risk. Thinking they knew how to use condoms was predictive of having more sexual partners among females, while being low acculturated from Middle Eastern culture was predictive of more partners among males. \n \nConclusions. Factors associated with HIV risk varied greatly between genders among this sample and may contribute to power imbalances within relationships. The application of the TGP to this sample was moderately successful in predicting number of sexual partners among females and condom-use risk among males. However, it was not as successful in predicting condom-use risk among females and number of sexual partners among males. Many factors associated with HIV risk have been identified in this study, and should be used to create interventions designed to increase equality within Middle Eastern/Arab-Canadian relationships. However, many issues are discussed that still need to be addressed in future research.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".