Neuroscience and Non-Lethal Violence in Genocide: Exploring Scope and Constraints
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Beyond findings in psychiatry and psychology, in the last two decades, the novel field of neuroscience has expanded our purview of brain injury, pain, and trauma—basically, non-lethal forms of violence. Peeking into the brain using state-of-the-art neuroimaging enables us to discern anomalies such as brain lesions, cysts, enlarged sulci, and regions of hypoperfusion (reduced blood flow), among other things, thereby allowing us to infer connections between brain anomalies and behavior. These findings, this paper posits, are highly relevant to genocide scholarship. Scholars have suggested that “mental harm” in Article II(b) of the Genocide Convention be extended to include neuroscientific findings; the most common in the literature being Post-traumatic Stress Disorder (PTSD), Traumatic Brain Injury (TBI), and Chronic Traumatic Encephalopathy (CTE). Including these in determining short- and long-term, visible and non-visible effects of exposure to mass atrocity and genocide would allow for a more accurate assessment of non-lethal violence on survivors and their families. Moreover, sufferers would be in a stronger position to employ restorative justice comprising legal, medical, and pecuniary means. Despite the excitement over these revelations, a question to ponder are the challenges individuals and institutions would face before they incorporate non-lethal violence derived from neuroscientific findings into genocide scholarship. This paper explores practical, technical, ideological, and legal arguments: (1) neurohype, (2) limitations of neuroimaging, (3) ideological battles, (4) gatekeeping the definition of genocide.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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