Review of <i>Queer in Translation: Sexual Politics under Neoliberal Islam</i> by Evren Savcı (Duke University Press)
Bibliographic record
Abstract
Evren Savcı’s Queer in Translation presents an alternative, both in methodology and analysis, to the Orientalist analytical frameworks typical of Western scholars studying queer politics in Middle Eastern regions. Specifically, Savcı analyzes the rise of Turkey’s Adalet ve Kalınma Partisi (AKP; in English, the Justice and Development Party) to show how the AKP’s increased securitization and oppression of marginalized communities—including, but not limited to, Turkey’s LGBTQ community—is the result of the marriage of Islam and neoliberalism. Savci produces compelling case studies that reveal how Turkey’s weaponization of religion, morality, and capitalism serve to secure the nation against dissenting citizens. From the discourse surrounding the complicated murder of a gay Kurdish man, to unlikely solidarities between religious hijabi women and LGBTQ activists, and the public commons that became Gezi Park, Savci’s critical translation methods reveal how the language to construct and resist securitization in Turkey are far more nuanced than simple attribution to solely Islamist extremism or Western neoliberal influence.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".