Geographic distribution of conversion therapy prevalence in Canada. Findings from a national cross-sectional survey, 2020
Bibliographic record
Abstract
Background: Conversion therapy practices (CTPs) are discredited efforts that target lesbian, gay, bisexual, trans, queer, Two-Spirit, or other (LGBTQ2S+) people and seek to change, deny, or discourage their sexual orientation, gender identity, and/or gender expression. This study aims to investigate the prevalence of CTPs across Canadian provinces and territories and identify whether CTP bans reduce the prevalence of CTPs. Methods: We collected 119 CTPs from 31 adults (18+) in Canada who have direct experience with CTPs, know people who have gone to CTPs, or know of conversion therapy practitioners using a 2020 anonymous online survey. Mapping analysis was conducted using ArcGIS Online. CTP prevalence was compared between provinces/territories with and without bans using chi-square tests. Results: Three provinces and eleven municipalities had CTP bans. The prevalence of CTPs in provinces/territories with bans was 2.34 per 1,000,000 population (95% CI 1.65, 3.31). The prevalence of CTPs in provinces/territories without bans was 4.13 per 1,000,000 population (95% CI 3.32, 5.14). Accounting for the underlying population, provinces/territories with the highest prevalence of CTPs per 1,000,000 population were New Brunswick (6.69), Nova Scotia (6.50), and Saskatchewan (6.37). Conclusions: Findings suggest only 55% of Canadians were protected under CTP bans. The prevalence of CTPs in provinces/territories without bans was 1.76 times greater than provinces/territories with bans. CTPs are occurring in most provinces/territories, with higher prevalence in the west and the Atlantic. These findings and continued efforts to monitor CTP prevalence can help inform policymakers and legislators as society is increasingly acknowledging CTPs as a threat to the health and well-being of LGBTQ2S+ people.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".