Defining the Civilian: The International Committee of the Red Cross’ Response to Crisis in Bosnia, 1992–1995
Bibliographic record
Abstract
This article explores how the International Committee of the Red Cross defined non-combatants during the Bosnian War (1992–1995) and how those definitions contributed to a counter-narrative that disrupts familiar conceptualizations of the war as exclusively ethnic. Through an examination of Red Cross press releases, I argue that the Red Cross defined identity primarily based on individual experiences with violence and/or transnational constructions of vulnerability in war based on age and gender. This is largely in contrast to Western politicians and journalists who repeated the language of ultranationalist leaders and relied on ethno-nationalist categories to describe non-combatants. By examining the discursive practices of the Red Cross, historians have an opportunity to further understand why some communities and individuals experienced violence, and participated in the war, in ways counter-intuitive to the nationalist discourse.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".