The Narrative Shelter for Young People with Childhood Experiences of Intimate Partner Violence: A Concept for Creating Opportunities for Storytelling, Storylistening, and Resilience
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objectives: Childhood experiences of intimate partner violence (CEIPV) remain a significant public health issue affecting millions of young people (YP) globally. Although CEIPV has been researched for decades, YP’s voices are often left unheard, their stories relegated to mere research data. Their CEIPV are usually told through adult proxy accounts rather than by YP themselves. Additionally, research shows that YP have limited opportunities to influence domestic violence policies and practices. This theoretical paper proposes a new YP engagement model for CEIPV research and practice. Methods: The model is based on a review of relevant literature, including lessons from the women’s shelter movement, child rights, narrative practice, trauma and violence-informed approaches, and selected case studies. Results: The Narrative Shelter Model integrates storytelling and storylistening to create a safe space for YP with CEIPV to exercise their voice and choice, and share their stories in a non-retraumatizing way. Moreover, the model invites the storylistener(s) to connect with YP’s stories to influence decision-making. Conclusion: The Narrative Shelter Model elicits a path towards creating safe and inclusive spaces for YP with CEIPV to share their stories and be heard as agents of social change. It aims not only to promote their voices but also to empower them to become young advocates and peer supporters in responding to IPV, thereby strengthening their resilience and recovery. The use of this model within domestic violence agencies can continue to position YP as experts in their own lives and pivotal agents in shaping knowledge and effective interventions.
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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 | 0.000 | 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 | 0.000 | 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 it