Breaking Through the Legal Binary: Media Labelling of Dominic Ongwen as a Victim–Perpetrator
Bibliographic record
Abstract
Individuals formerly involved in armed groups are positioned in the victim–perpetrator binary by legal systems and societies. Media participates in this process and influences the relationship between law and society by reproducing or challenging legal and social designations. We assess the relationship between the International Criminal Court's (ICC) prosecution of Dominic Ongwen, a former child soldier in Uganda's Lord's Resistance Army (LRA), and media representations of Ongwen. We conduct a content analysis of 779 Ugandan, African, and international newspapers’ English-language articles published between January 2005 and October 2022. We find that media coverage focuses on Ongwen's adult roles in the group, including as an LRA leader, largely reproducing the ICC's portrayal of the accused. A minority of articles acknowledge a more complex status and increase in frequency once Ongwen's ICC trial is underway. An important faction challenges the ICC's narrative, with non-Africa-based media presenting a more complex depiction of Ongwen.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".