Gender and Same-Sex Intimate Partner Violence: A Systematic Literature Review
Bibliographic record
Abstract
The infl uence of gender on intimate partner violence (IPV) has been predominantly studied in opposite sex relationships.This article presents the results of a systematic literature review in which the aim was to understand how gender may aff ect not only the violence in same-sex IPV but also, and mostly, each element of the couple and third-party responses.The search was conducted in four electronic databases: B-on, PubMed, Sage and PsycINFO.From the analysis of seven articles selected, four major domains were identifi ed in which gender aff ects these relationships: normalizing violence; diffi culty in recognizing violence; diffi culty in seeking help; and social isolation.It was concluded that gender, or gender role expectations, cannot be ignored while studying this phenomenon.More than infl uencing violence per se, gender shapes the way each element of the couple perceives their experiences and third-party perceptions (e.g., family, friends, justice system, and victims support services professionals), preventing an adequate social response to this form of violence.
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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.018 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".