Opportunities and challenges in preventing violence against adolescent girls through gender transformative, whole-family support programming in Northeast Nigeria
Bibliographic record
Abstract
BACKGROUND: Household violence is one of the most prevalent forms of gender-based violence faced by adolescent girls in humanitarian settings. A growing evidence base demonstrates the extent to which multiple forms of familial violence, including intimate partner violence, violence against children, and sibling violence overlap in the same households. However, existing evidence of family support programming that effectively reduces violence against girls by addressing intersecting forms of household violence are limited, particularly in the Global South. Through a qualitative implementation evaluation informed by a grounded theoretical approach, we explored the perceived impact of a gender transformative, whole-family support intervention aimed at building adolescent girls' protective assets against violence, among program participants in two communities of internally displaced people Maiduguri, Borno State, Northeast Nigeria. METHODS: We conducted six in-depth interviews and six focus group discussions with adult caregivers; six participatory activities and four paired interviews with adolescent girls and boys; and 12 key informant interviews with program staff. Criterion sampling was used to recruit 21 male caregivers, 21 female caregivers, 23 adolescent boys, and 21 adolescent girls; purposive sampling was used to recruit 12 program staff to participate in qualitative research activities. We audio recorded, translated, and transcribed all interviews. In a collaborative coding process, a multi-stakeholder team used applied thematic analysis in Dedoose to identify emergent themes in the data. RESULTS: Participants reported a decreased tolerance for and perpetration of violence against girls at the household level, and endorsed their right to protection from violence at the community level. However, alongside these self-reported changes in attitude and behavior, aspects of normative, patriarchal norms governing the treatment of adolescent girls were maintained by participants. CONCLUSIONS: This study builds the evidence base for gender transformative, whole-family support programming and its impact on preventing violence against adolescent girls in humanitarian emergencies. Situating our findings in a feminist analysis of violence, this study calls attention to the complexity of gender norms change programming amongst families in conflict-affected settings, and highlights the need for programming which holistically addresses the relational, community, and structural drivers of violence against girls in emergencies.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".