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Record W4406579460 · doi:10.1177/17506352241312086

Framing victims and perpetrators: Local and international reporting on the International Criminal Court case against Dominic Ongwen

2025· article· en· W4406579460 on OpenAlexaff
Jessica Trisko Darden, Izabela Steflja, Amanda Wintersieck

Bibliographic record

VenueMedia War & Conflict · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsFraming (construction)Criminal courtPolitical scienceCriminologyLawSociologyInternational lawHistory

Abstract

fetched live from OpenAlex

Building on research on victims and perpetrators of political violence and their depiction in the media, this article highlights the conceptual and practical challenge of specifying the process by which individuals acquire a morally ambiguous or ‘complex’ status in conflict. The authors conduct a content analysis of English-language print reporting on Dominic Ongwen’s International Criminal Court case and ambiguous status as a child soldier and victim–perpetrator. They identify important variation in how different news media frame the processes through which an individual becomes a victim–perpetrator and how these depictions relate to understandings of agency as well as transitional justice and post-conflict societal transformations. The article presents a framework for understanding how individuals are seen as ‘turning’ from one category of conflict-affected individual to another category as depicted in the news media.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.006
Science and technology studies0.0050.006
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.044
GPT teacher head0.338
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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