Social scripts of violence among adolescent girls and young women in Zambia: Exploring how gender norms and social expectations are activated in the aftermath of violence
Bibliographic record
Abstract
Adolescent girls and young women ages 15-24 experience high rates of gender-based violence (GBV), underpinned by gender and social norms that shape their transitions to adulthood. For interventions that seek to leverage and build on existing infrastructure for health service provision, it is important to understand how gender norms operate in the background and how they shape service engagement or non-engagement. In formative work for our project, Screen & Support, outside of Lusaka, Zambia, we engaged in community conversations with adolescent girls and young women to understand common types and experiences of violence, perceptions of what causes violence, and pathways to post-violence service access. This manuscript explores emerging findings surrounding social and gender norms. We engaged n = 12 adolescent girls and young women ages 15-24, including survivors of GBV, young women living with HIV, and young married women in separate conversations conducted in a mix of Nyanja, Bemba, and English. Arts-based activities accompanied guided focus group discussions. Translated transcripts were coded and thematically analysed by two authors using Dedoose software. Key themes emerged around two major themes-understanding the norms underpinning violence, and observing how these norms were activated in the aftermath of violence. Sub-themes focused on power differentials supporting violence, social expectations and community-enacted sanctions, and understanding dominant norms and assumptions. Considering what unfolded in the aftermath of violence, young women participants considered key reference groups upholding norms, explored the contexts where norms may be contested or become more complicated, and described how accepting silence was a common means of closure. We discuss the implications of these findings for programme design, delivery, and evaluation, as well as the potential, and roadmap, for shifting norms that negative affect adolescent girls and young women.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".