Nancy Armoury Combs, Fact-Finding without Facts: The Uncertain Evidentiary Foundations of International Criminal Convictions, Cambridge, Cambridge University Press, 2010
Bibliographic record
Abstract
Les discussions a l'egard de la legitimite de la justice penale internationale portent generalement sur ses fondements theoriques. Les premiers efforts de justice penale internationale, maintes fois critiques quant a leur apparence vindicative, ont eu cependant le « luxe » de pouvoir faire abstraction ou presque de toute preuve testimoniale. A Nuremberg, l'imposante quantite de preuve documentaire laissee par le regime nazi fut jugee suffisante, en depit des nombreuses critiques pour condamner les responsables de certaines des atrocites commises par le III Reich. Apres presque quatre decennies d'accalmie, la renaissance post-guerre froide de la justice penale internationale a du effectuer un virage quant a son mode d'etablissement des faits. Les conflits auxquels elle fait desormais face ne se caracterisent plus par une structure claire du pouvoir et les responsables de crimes de masse ne laissent a peu pres plus de traces documentaires de leurs delits. Des lors, la preuve testimoniale est devenue l'element central des proces penaux internationaux. Cette situation n'est pas sans entrainer plusieurs problematiques; d'aucun soulignent l'inexactitude des temoignages des victimes d'actes violents, notamment. C'est sur ce sujet peu publicise que Nancy Armoury Combs, professeure de droit penal international a la William and Mary Law School, fonde son ouvrage.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".