Promises to Keep: Diplomatic Assurances Against Torture in US Terrorism Transfers
Bibliographic record
Abstract
“Diplomatic assurances” are promises not to torture. They are sought when transferring a detainee from the custody of one government to another. Not surprisingly, they are sought from governments that typically torture.\nThis report surveys the law and practice of assurances in the US and, comparatively, in Canada and Europe. It is the culmination of a long-term engagement by Columbia’s Human Rights Clinic and its faculty to research and support advocacy on diplomatic assurances. That process has involved advocacy with Swedish NGOs, support for research by Human Rights Watch, FOIA requests with the ACLU and collaborative efforts with UN mechanisms.\nOver the past decade, human rights groups, in particular, have produced impressive documentation. But no single source presents the evolving evidence and jurisprudence of diplomatic assurances. This report seeks to fill that gap. We do not take a position on whether assurances can work. Rather, we seek to identify elements that are necessary in order to make assurances plausible. We focus on what is known about preventing torture and how that can be incorporated into the process.
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.
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 | 0.015 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".