Event centrality and conflict-related sexual violence: A new application of the Centrality of Event Scale (CES)
Bibliographic record
Abstract
Berntsen and Rubin’s Centrality of Event Scale (CES) has been used in many different studies. This interdisciplinary and exploratory article is the first to apply the scale and to analyse event centrality in the context of conflict-related sexual violence (CRSV). It draws on a research sample of 449 victims-/survivors of CRSV in Bosnia and Herzegovina (BiH), Colombia and Uganda. Existing research on event centrality has mainly focused on the concept’s relationship with post-traumatic stress disorder and/or post-traumatic growth. This article, in contrast, does something new, by examining associations between high event centrality, resilience, well-being and experienced consequences of CRSV, as well as ethnicity and leadership. Its analyses strongly accentuate crucial contextual dimensions of event centrality, in turn highlighting that the concept has wider implications for policy and interventions aimed at supporting those who have suffered CRSV. Ultimately, the article juxtaposes event centrality with a ‘survivor-centred approach’ to CRSV, using the former to argue for a reframing of the latter. This reframing means giving greater attention to the social ecologies (environments) that shape legacies of sexual violence in conflict.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".