Unsettling international law and peace-making: An encounter with queer theory
Bibliographic record
Abstract
Abstract This article examines the usefulness of an encounter with queer theory to contribute to the peaceful resolution of armed conflicts, to question the traditional frontiers of international law, and to lay the groundwork for envisaging different forms of peace and peace-making. In a field where, arguably, little genuine progress has been made to resolve armed conflicts and to address underlying forms of violence, queer theory can reinforce a pluralistic understanding of law and suggest much-needed unsettling and creative approaches. The article focuses on queer theory’s specific critique of the construction and normalization of hierarchies, categories, and identities, which almost always – whether explicitly or implicitly – lie at the heart of armed conflicts and frame peace negotiations, without ever being truly reconsidered. Moreover, queer theory allows appreciating both peace and law beyond predetermined categorizations and as aspirational endeavours that are constantly evolving. Through a dialogue between two figures, which imagines what Peace and qt* might want to tell each other, this article also attempts to queer the standard academic format and to question the dominant forms of expression and knowledge-production in academia.
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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 | 0.021 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.146 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".