Masculinities and Queer Perspectives in Transitional Justice
Bibliographic record
Abstract
This book addresses the theory and practice of transitional justice through the lens of masculinities and queer perspectives. What and where are the intersections between masculinities and queer theories and frameworks for better understanding lived experiences of violence, justice, and transitions? How can masculinities and queer perspectives enhance and "complexify" our understandings of the intersections between gender, sexualities, armed conflict and (post-)conflict transitions? Incorporating masculinities and queer perspectives in transitional justice in tandem, and alongside one another, this book contributes empirically, conceptually, and methodologically to an exploration of gender in processes of dealing with violent pasts. More specifically, and by taking on the task of combining, bringing into conversation, and utilizing both masculinities and queer perspectives, the book aims to facilitate and contribute toward more inclusive, holistic, and intersectional approaches of gender in dealing with the past. This book will appeal to scholars and students working in the areas of transitional justice, peace and conflict research, international relations, gender studies, and socio-legal studies. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution (CC-BY) 4.0 license.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.023 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".