Sexual violence stigma experiences among refugee adolescents and youth in Bidi Bidi refugee settlement, Uganda: Qualitative insights informed by the stigma power process framework
Bibliographic record
Abstract
There are over 100 million forcibly displaced persons who experience elevated risks for sexual violence. Sexual violence stigma can have immediate and long-lasting effects on social and health outcomes among survivors. There is a dearth of information on the experiences of sexual violence stigma among refugee adolescents and youth, particularly in low and middle-income contexts where most forcibly displaced persons are hosted. Our study focuses on understanding the lived experiences of sexual violence stigma among refugee adolescents and youth in Bidi Bidi Refugee Settlement, Uganda. This qualitative study involved twelve individual in-depth interviews and six focus groups in Bidi Bidi with refugee youth aged 16–24, refugee elder interviews (n = 8), and service provider interviews (n = 10). We explored experiences and impacts of sexual violence stigma, including accessing supportive resources. We conducted thematic analysis informed by the Stigma Power Process framework. This framework examines how social processes of stigma serve to keep people ‘in’, ‘down’, and ‘away’. Participant narratives highlighted negative cultural conceptions of sexual violence survivors and of women and girls, as well as daily indignities targeting survivors that reinforced their lower status. Shaming sexual violence survivors as ‘immoral’ operated to keep people ‘in’ the social order where it was expected that ‘moral’ persons would not experience sexual violence. Fear of such judgment, and wanting to stay ‘in’, produced barriers for survivors to access healthcare and legal support. Participants reported community-level blame and punishment kept them ‘down’, and community isolation and rejection kept them ‘away’. At the individual level, survivors were kept ‘down’ through internalizing shame, low self-esteem, self-isolation, and hiding. Findings signal the need to address the far-ranging impacts of sexual violence stigma on refugee youth health, wellbeing, and rights. Meaningfully engaging refugee youth and communities in reducing sexual violence stigma must concomitantly transform inequitable gender norms and power relations.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".