Mercy for money: Torture’s link to profit in Sri Lanka, a retrospective review
Bibliographic record
Abstract
BACKGROUND: The purpose of this retrospective study is to describe the pattern of bribe taking in exchange for release from torture, during and after the decades-long war in Sri Lanka. METHODS: We reviewed the charts of 98 refugee claimants from Sri Lanka referred to the Canadian Centre for Victims of Torture for medical assessments prior to their refugee hearings in Toronto between 1989 and 2013. We tallied the number of incidents in which claimants described paying cash or jewelry to end torture, and collected other associated data such as demographics, organizations of the perpetrators, locations, and, if available, amounts paid. We included torture perpetrated by both governmental and nongovernmental militant groups. Collected data was coded and evaluated. FINDINGS: We found that 78 of the 95 subjects (82.1%) whose reported ordeals met the United Nations Convention Against Torture/International Criminal Court definitions of torture described paying to end torture at least once. 43 subjects paid to end torture more than once. Multiple groups (governmental and non-governmental) practiced torture and extorted money by doing so. A middleman was described in 32 percent of the incidents. Payment amounts as reported were high compared to average Sri Lankan annual incomes. The practice of torture and related monetary extortion was still reported after the end of the war, inclusive of 2013. INTERPRETATION: Torture in Sri Lanka is unlikely to end while profit motives remain unchallenged. As well as health injuries, victims of torture and their families suffer significant economic injuries while their assailants are enriched. The frequent link between torture and impunity means multiple populations the world over are vulnerable to this abuse.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".