Gender and Sexual Orientation in Canadian Intimate Partner Violence Research: A Focused Mapping Review and Synthesis
Bibliographic record
Abstract
Intimate partner violence (IPV) is a widespread social and health problem disproportionately burdening women and, we are learning, gender and sexual minority (GSM) people, who are under-represented in research. The measurement and reporting of gender and sexual orientation in health and social science research are also inadequate. We conducted a focused mapping review and synthesis to examine the inclusion of GSM people, and the reporting of gender identity and sexual orientation, in Canadian IPV research. Using database searches, hand-searches (November 2022), and citation chaining (April/May 2023), we identified eligible articles that (1) were published in English or French in peer-reviewed journals from 2020 to 2022, (2) reported research involving at least some Canadian IPV survivors and/or perpetrators, and (3) had at least one Canada-affiliated author. The 150 included articles contribute significantly to the IPV literature but have shortcomings. Most articles inadequately reported gender identity and sexual orientation; among articles reporting, most only included cisgender heterosexual participants. Some articles conflated sex and gender, used outdated terminology, or used language that invisibilized GSM people. While research focused on heterosexual women (and men) is needed, exclusionary research practices can further marginalize GSM people. Given such research practices can impede the development of equity-oriented policies for these groups, we provide recommendations for researchers to improve inclusion and reporting. Gatekeepers such as ethics review board members and funders should strive to uphold these standards, including developing their own research and reporting policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.048 | 0.138 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.057 | 0.073 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".