Factors affecting the risk of gender-based violence among 2SLGBTQIA+ adolescents and youth: a scoping review of climate change-related vulnerabilities
Bibliographic record
Abstract
Gender-based violence (GBV) is a pervasive and growing issue that affects diverse populations worldwide. This study aimed to synthesize the factors affecting the risk of GBV among 2SLGBTQIA+ adolescents and youth. A scoping review was conducted using international databases (Web of Science, Scopus, Proquest, PubMed, Embase, EBSCOhost) since 2009. The studies were independently appraised by two reviewers guided by the PRISMA approach. Ninety-nine articles focusing on the 2SLGBTQIA+ community, GBV, and adolescents or youth were included for the review. The factors affecting the risk of GBV among 2SLGBTQIA+ adolescents and youth were categorized into (1) Wellbeing and mental health; (2) Disparities compared to cisgender youth; (3) Perpetration and victimization; (4) Different types of violence; and (5) Differences among 2SLGBTQIA+ subgroups. The studies further showed relevance to climate-related stressors such as displacement and resource scarcity, and how those can further amplify the vulnerabilities of 2SLGBTQIA+ youth to GBV. The findings revealed the necessity for multi-level strategies that account for the compounded risks faced by 2SLGBTQIA+ adolescents and youth, including those introduced by environmental crises. These five factors related to GBV among 2SLGBTQIA+ adolescents and youth should be considered by social work professionals when working with at-risk populations. Due to limited robust evidence (from countries outside the US) and the diverse contexts of the selected studies, future research is needed to minimize GBV among 2SLGBTQIA+ adolescents and youth, especially as climate change introduces new layers of vulnerability. Systematic review registration: 10.37766/inplasy2024.4.0008.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".