Intersectionality and sex and gender-based analyses as promising approaches in addressing intimate partner violence treatment programs among LGBT couples: A scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although Intimate Partner Violence (IPV) is an important health and social issue, less is known about IPV among sexual orientation and gender-minoritized (SOGI) populations such as Lesbian, Gay, Bisexual and Transgender (LGBT) couples. IPV among same-sex (e.g. lesbian, gay, bisexual) and gender-minoritized (e.g. transgender) couples requires a reframing of this issue from a heteronormative and cisnormative lens in order to better understand and effectively address approaches to prevent this kind of abuse and to improve treatment programs. The purpose of this scoping review is to explore why including an intersectional lens in Sex and Gender-Based Analysis is needed to improve effectiveness of IPV treatment programs, analyzing what works and why among SOGI populations impacted by IPV in current IPV programs. Specifically, this scoping review systematically searched three academic databases to identify peer-reviewed publications examining: (a) existing treatment programs for SOGI-minoritized populations who are impacted by IPV, and (b) suggestions for future policies and services for SOGI-minoritized populations. Of the 1172 potential articles, 75 met the inclusion criteria, but none described IPV programs specific to SOGI-populations. The findings of this scoping review reflect the need for developing IPV programs that are informed by evidence-based practice in health and social services for SOGI populations, and will offer new approaches for current BIPs programs to move forward prevention and intervention.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it