Identifying the victims of the Indian Ocean tsunami: The role of the private sector
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
Until the 2004 Indian Ocean tsunami, identifying victims of a mass catastrophe was done largely by police and forensic scientists who tried to match pre-death and post-death data from paper files. The tsunami brought computer databases into the world of forensic identification and led to major involvement from four private-sector companies from Canada, France, Denmark and Norway. Between them, the firms created a system to improve the handling of missing persons’ calls; an automated fingerprint identification system; a system to generate possible matches between pre and post-death data; and a state-of-the-art morgue in Phuket, Thailand. In the past, there has been private-sector involvement in mass death incidents — for example, most funerals are conducted by private firms — but the tsunami marked a major shift to a public-private partnership in an area that has generally been limited to police and forensic scientists.
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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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