Free---- Rapelay English Patch 14 💎

| | Survivor-Led | Organization-Led | |--|--------------|------------------| | Control | Full | Shared (org edits) | | Risk | Harassment, doxxing | Dilution of message | | Best for | Peer networks, grassroots | Large-scale public health | | Example | #MeToo (unstructured) | Know Your IX (structured) |

Hybrid model: Org provides legal, comms, and mental health support; survivor retains editorial approval. FREE---- Rapelay English Patch 14

Issue: Campus sexual assault prevention
Goal: Increase bystander intervention reporting
Survivors: 3 students (diverse genders, races, assault types – all anonymous audio) As we look toward the next decade, technology

| Day | Action | |-----|--------| | 1–5 | Consent & safety planning with survivors; record audio with voice modulators | | 6–10 | Edit 60-sec clips; create transcripts; build landing page with resources | | 11–15 | Train student ambassadors; prep trigger warning protocols for each class | | 16–20 | Launch: Email to faculty, Instagram Reel series, QR codes in bathrooms | | 21–25 | Live panel (optional) with survivors (moderated, no open mic) | | 26–30 | Survey students; report findings; pay survivors; offer follow-up support | Instagram Reel series

As we look toward the next decade, technology is changing how survivor stories and awareness campaigns interact. Generative AI allows survivors to create avatars or voice-modulated versions of themselves. This allows individuals in dangerous situations (such as those in high-control religious groups or abusive relationships) to share their stories without risking physical safety.

Furthermore, de-identified data storytelling is emerging. This allows survivors to answer surveys about their experiences—like the exact tactics used by a fraudster or a rapist—which are then aggregated into an “anonymous survivor narrative.” It provides the texture of a story without the identity of the narrator.