Discrimination and Health: Measurement and Impacts on Ontario’s Transgender Communities
Bibliographic record
Abstract
Discrimination may contribute to poorer health outcomes experienced by non-dominant social groups. While discrimination and health research has flourished over the past two decades, little attention has been paid to the assessment of multiple forms of discrimination, nor to the health effects of discrimination for transgender persons in Canada. Therefore, this thesis examines the impacts of discrimination on health behaviours among transgender persons in Ontario and develops a new instrument set for evaluating self-reported discrimination irrespective of attribution, the Intersectional Discrimination Index (InDI). The first four manuscripts draw on data from the Trans PULSE Project, a respondent-driven sampling survey of transgender Ontarians aged 16+ conducted in 2009-2010 (n=433). Analyses were weighted using RDS-II methods, and odds ratios or prevalence ratios were estimated from logistic regression models to identify the impacts of discrimination, social exclusion, and gender transition. The first manuscript investigates correlates of both past-year HIV-related sexual risk and sexual inactivity among transfeminine (male-to-female spectrum) persons. Genital surgery for gender transition was independently associated with lower odds of both outcomes. Discrimination was not associated with sexual risk overall, but sensitivity analyses found that correlates differed by type of sexual risk behaviour. The second manuscript examines HIV-related sexual risk among transmasculine (female-to-male spectrum) persons who are gay, bisexual, or have sex with men. Known correlates of sexual risk among cisgender gay and bisexual men were similarly predictive of risk in this population, including sexual abuse, stimulant use, and depressive symptoms. The third and fourth manuscripts focus on heavy episodic drinking (HED) and illicit drug use, respectively, among all transgender Ontarians. HED, cocaine use, and amphetamine use were more common among transgender Ontarians than expected based on the age-standardized reference population. HED was associated with transmasculine gender and sex work, but not with discrimination. Illicit drug use was associated with anti-transgender violence, homelessness or underhousing, and sex work. The final manuscript describes the development and validation of the InDI, which includes three components measuring anticipated, day-to-day, and major discrimination. The bi-national validity and reliability study found consistent evidence of construct validity and test-retest reliability. Finally, implications and future research directions are discussed.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".