Commentary:Introduction of Fresh Evidence by the Prosecution During Cross-Examination in the Special Court for Sierra Leone
Bibliographic record
Abstract
This commentary addresses a number of important evidentiary issues that arose during cross-examination of Charles Taylor, the former President of Liberia, who who stood trial and was convicted of crimes against humanity and war crimes committed during Sierra Leone’s brutal civil war before the UN-backed Special Court for Sierra Leone (SCSL). At the core of cross-examination was the Prosecution’s strategy to challenge Taylor’s self-portrayal as a peacemaker and to demonstrate a pattern of conduct of the accused in Liberia similar to the one pursued by war-mongering leaders of various rebel groups in Sierra Leone. The Prosecution also attempted to demonstrate close links between the accused and the leadership of the notorious Revolutionary United Front (RUF), which he allegedly used to commit crimes in order to gain access to Sierra Leone’s boundless mineral resources, including diamond deposits. A large part of the Prosecution’s strategy was to impeach the credibility of the accused through the introduction of documentary evidence that unravelled inconsistencies in his prior testimony. This, however, proved on many occasions to be impossible, as the judges treated these documents with great caution, pointing out that this material had not been admitted into evidence during the Prosecution case (“fresh evidence”). This commentary examines, in light of the SCSL jurisprudence and practices, a number of vexed evidentiary issues that accompany the introduction of fresh evidence by the prosecution after the closure of its case-in-chief.
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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 | 0.023 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.015 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.011 | 0.004 |
| Research integrity | 0.106 | 0.097 |
| Insufficient payload (model declined to judge) | 0.005 | 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".