Improving Civilian Protection during War through Conflict-Specific Behavioural Regulation of Combatants
Why this work is in the frame
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Bibliographic record
Abstract
This thesis advances the claim that there is a gap between the regulation of behaviour for the protection of individuals in peace and the regulations needed to protect civilians from combatant violence during war. Social psychology and criminology theories can help to develop the necessary conflict-specific behavioural regulations. This is because social psychology and criminology theories can explain how combatant deviance is adversely affected by psychological processes that reframe combatants’ conceptions of right and wrong and, in so doing, fundamentally alter the way in which combatants view the IHL rules intended to protect civilians. This thesis uses legal doctrinal methodology to establish the current status of IHL application to armed groups and existing IHL protections for civilians, which are based largely on peacetime protections for individuals (e.g., prohibitions on assault, murder, rape, etc.). It demonstrates the need and utility of turning to academic disciplines beyond law, specifically social psychology and criminology, to understand combatant violence toward civilians. Through the use of case studies focusing on the Sierra Leone civil war and the numerous ongoing conflicts in the Democratic Republic of Congo, this thesis identifies two common combatant behaviours that contribute to the perpetration of IHL violations against civilians, but are currently unregulated by IHL: (1) combatant use of demeaning, degrading, or dehumanizing language toward civilians and (2) combatant use of nicknames, particularly violent or heroic nicknames. The thesis proposes two new IHL regulations to address these behaviours and to inhibit the ability of these behaviours to contribute to violence toward civilians during armed conflict. Ultimately, the thesis demonstrates how combatant psychology can be used to develop the substantive content of IHL for the protection of civilians.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it