New technologies and enforced disappearances: opportunities and challenges for the protection of human rights
Bibliographic record
Abstract
New technologies and enforced disappearances have been part of thematic study included in the annual report of the Working Group on Enforced and Involuntary Disappearances (WGEID) published in August 2023. Enforced disappearances present flagrant human rights violation where the families of disappeared person are not familiar with the fate and whereabouts of their disappeared relatives. The use of new technologies in cases of enforced disappearances may enhance the human rights protection, facilitate the search for disappeared persons and obtain evidence. However, new technologies can be used to prevent further investigations and obtain evidence especially in cases where torture is committed by state actors and cases of enforced disappearances in transnational context. This paper will analyze the positive and negative effects from the use of new technologies in enforced disappearances and will emphasize the importance to conduct an effective investigation and to acknowledge the right to truth in these cases.
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.037 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".