Gender-Based Violence and 2SLGBTQI+ Groups
Bibliographic record
Abstract
Gender-based violence (GBV) is a pervasive public health issue that affects all Canadians, including Indigenous peoples (First Nations, Inuit, Métis); however, it is well-understood that GBV disproportionately affects certain social groups. An estimated one million Canadians aged 15 and older identify with a sexual orientation other than heterosexual, and approximately 1 in 300 people identify as transgender or non-binary. In Canada, violence rooted in biphobia, homophobia, transphobia, and queerphobia results in disproportionately high levels of GBV experienced by Two-Spirit, lesbian, gay, bisexual, transgender, queer (or questioning), intersex, and other individuals who identify outside of cisgender, heterosexual norms (2SLGBTQI+ people). The health impacts of GBV experienced by people who identify outside of gender and sexuality norms are profound, spanning mental and physical dimensions across the life course. This article employs an anti-oppression queer framework to provide a comprehensive overview of current knowledge and understandings of GBV in Canada concerning 2SLGBTQI+ people, emphasizing (1) the disproportionate risk of GBV faced by 2SLGBTQI+ communities within the context of Canadian social politics; (2) key links between the experiences of GBV among 2SLGBTQI+ people in Canada and associated health disparities; (3) current orientations to GBV policy, practice, and research, with an emphasis on contemporary, inclusive paradigms that shape equity-oriented health and social services; and (4) future directions aimed at eradicating GBV and addressing health inequities among 2SLGBTQI+ people in Canada. While much work remains to be done, the expansion of 2SLGBTQI+ inclusion in GBV prevention within the past five years points to a promising future.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".