Preventing an Agunah Crisis in the Wake of the World Trade Center Disaster by Establishing Death through Various Forms of Evidence
Bibliographic record
Abstract
According to Jewish law, specific evidence confirming the death of a man is needed before his widow is able to remarry. In situations such as the attacks on the World Trade Center, where many victims could not be identified on the basis of their remains alone, evidence traditionally tendered to establish death was largely unavailable. This meant that a relaxation of some of the more stringent requirements for proof of death was required, and that some additional, novel categories of evidence had to be considered in establishing death. DNA fingerprinting and dental records are among the evidence that rabbis now consider to have some probative value in establishing death. In addition, telephone calls made and e-mails sent by the victims just prior to the attacks could be used as proof of presence within the towers. When considered in conjunction with assessments of the probability of escape from a given location within the towers, this evidence is given greater weight. The combination of traditional identification signs, processes and principles of proving death and the more recently acceptable methods has the effect of decreasing the waiting period before which a Jewish woman can conclude that her husband has perished, and can thus effectively bring some closure to a tragic circumstance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".