“The Problem from Hell”: Examining the Role of Peace and Conflict Studies for Genocide Intervention and Prevention
Bibliographic record
Abstract
Genocide is one of the most challenging problems of our age. In her book, “A Problem from Hell:” America and the Age of Genocide, Samantha Power (2002) argues that the United States, while in a position to intervene in genocide, has lacked the will to do so, and therefore it is incumbent on the U.S. citizenry to pressure their government to act. This article reviews how the topic of genocide raises questions along the fault lines of the field of Peace and Conflict Studies (PACS). In this article, a framework is provided to examine genocide and responses to it. This includes a review of a multiplicity of factors that (a) facilitate genocide, (b) constrain action in the face of it, and (c) facilitate intervention. In this analysis, further consideration is given to the location of the actor either within the region of the conflict or external to it. Our goal is to situate the study of genocide in the PACS field and promote to the articulation of possibilities for intervention by individuals, organizations, and policymakers.
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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 | 0.089 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.010 | 0.044 |
| Scholarly communication | 0.016 | 0.027 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".