Examining intersections between violence against women and violence against children: perspectives of adolescents and adults in displaced Colombian communities
Bibliographic record
Abstract
BACKGROUND: Research examining the interrelated drivers of household violence against women and violence against children is nascent, particularly in humanitarian settings. Gaps remain in understanding how relocation, displacement and ongoing insecurity affect families and may exacerbate household violence. METHODS: = 73) in two districts in Colombia from May to August of 2017. Participants were displaced and/or residing in neighborhoods characterized by high levels of insecurity from armed groups. RESULTS: Using inductive thematic analysis and situating the analysis within a feminist socioecological framework, we found several shared drivers of household violence. Intersections among drivers at all socioecological levels occurred among societal gender norms, substance use, attempts to regulate women's and children's behavior with violence, and daily stressors associated with numerous community problems. A central theme of relocation was of family compositions that were in continual flux and of family members confronted by economic insecurity and increased access to substances. CONCLUSIONS: Findings suggest interventions that systemically consider families' struggles with relocation and violence with multifaceted attention to socioecological intersections.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".