The Gender Jurisprudence of the Special Court for Sierra Leone: Progress in the Revolutionary United Front Judgments
Bibliographic record
Abstract
emblematic of the brutal, decade-long armed conflict in Sierra Leone. 3 The RUF became known for, among other acts, gender-based crimes such as widespread rape, sexual slavery, and forced marriage. 4Therefore, it was not surprising when the SCSL's Prosecutor secured an indictment charging three members of the RUF with the following: one count of rape as a crime against humanity (count 6); one count of sexual slavery as a crime against humanity (count 7); one count of the crime against humanity of other inhumane acts (under which the act of forced marriage was considered) (count 8); and one count of outrages upon personal dignity as a violation of Article 3 Common to the Geneva Conventions and of Additional Protocol II (count 9). 5 After a lengthy trial, 6 the SCSL convicted the accused on all four counts due to their participation in a joint criminal enterprise. 7 As a result, the RUF trial judgment brought the first-ever convictions in an international or internationalized tribunal for the crimes against humanity of sexual slavery and forced marriage (as an inhumane act), which the Appeals Chamber confirmed. 83.The conflict began in March 1991 with the launch of an attack by the RUF.It officially ended in January 2002, when the President of Sierra Leone declared a final cessation of hostilities.RUF TJ, supra note 1, 12, 44.4. See, e.g.
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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 | 0.028 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.025 |
| Scholarly communication | 0.020 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.017 | 0.016 |
| 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".