Moving Images: WITNESS and Human Rights Advocacy (<i>Innovations Case Narrative</i>: WITNESS)
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
Back in 1988 I was part of Amnesty International's "Human Rights Now!" Tour, which was to celebrate the 40th anniversary of the Universal Declaration of Human Rights. We managed to persuade Bruce Springsteen, Tracy Chapman, Youssou N'Dour, and Sting to join us, and we toured over nineteen countries. During that time I met hundreds of survivors of human rights abuses and listened to their stories of suffering and frustration. These were people who had been brutally tortured, forced to flee their homes and countries, who watched their loved ones murdered, and suffered overwhelming forces of oppression. What all of these personal accounts had in common was that the perpetrators went unpunished for their crimes. These human rights abuses were being successfully denied, ignored, and forgotten, despite many written reports. But, it was clear that in those cases where photographic film or video evidence existed, it was almost impossible for the oppressors to get away with it.
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.
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 | 0.005 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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