“It definitely changed me”: Exploring sexual and gender diverse people's experiences with intimate partner violence in Ontario, Canada
Bibliographic record
Abstract
INTRODUCTION: Intimate partner violence (IPV) involves an individual committing acts intended to harm or intimidate a current or former romantic partner. The COVID-19 pandemic and subsequent stay-at-home orders often trapped victims with perpetrators and intensified IPV. Although sexual and gender diverse people disproportionately experience IPV compared to cisgender, heterosexual people, their experiences are not well documented in the Canadian context. This study aimed to explore the experiences of Two-Spirit, lesbian, gay, bisexual, transgender, queer, intersex, asexual, and other sexual and gender diverse (2S/LGBTQIA+) people with IPV in Ontario and how the COVID-19 pandemic affected their IPV experiences. METHODS: We conducted in-depth, semi-structured interviews with self-identified 2S/LGBTQIA+ people who experienced IPV on/after March 15, 2020. We audio-recorded and transcribed all interviews and coded the transcripts for content and themes using inductive and deductive techniques. RESULTS: Our 20 participants experienced physical, psychological, sexual, and financial abuse. Technology-facilitated violence extended abuse geographically and temporally. IPV experiences were associated with negative mental health outcomes that were intensified by the COVID-19 pandemic. Participants struggled to see themselves as legitimate victims of IPV. Although participants regretted being victims of violence, many saw their abusive relationship(s) as a learning experience to inform future relationships. DISCUSSION: Our findings suggest that 2S/LGBTQIA+ people may experience unique forms of identity abuse and may have difficulty recognizing their IPV experiences as abuse. Ensuring that comprehensive sexual health education is trauma-informed, anti-oppressive, and includes information about healthy relationship dynamics, 2S/LGBTQIA+ relationships, and IPV is critical.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.027 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".