TOPLUMSAL CİNSİYETLENDİRİLMİŞ ŞİDDET, SÖMÜRÜ VE DİRENİŞ: İRANLI MÜLTECİ KADINLARIN YALOVADAKİ DENEYİMLERİ
Bibliographic record
Abstract
My dissertation focuses on the experiences of Iranian refugee women in Turkey who await resettlement in Canada, the USA, and various European Countries. Asylum seekers from countries such as Afghanistan, Iran and Iraq are assigned to satellite cities in Turkey until their resettlement. The lives of refugees waiting without any social or financial support are deeply shaped by satellite city regulation, and the satellite city emerges as an important category of analysis to understand the multifaceted experiences of refugees in Turkey. Based on ten months of ethnographic research with a feminist methodology in one of those satellite cities — namely Yalova — I ask, how do refugee women experience satellite city restrictions, labor exploitation, and gendered violence during their period of waiting in Turkey and, what kind of strategies do they use to resist these oppressive conditions? With a focus on Iranian women, my research demonstrates that their experience in Yalova entails multiple and multi-layered forms of gendered violence, ranging from encounters with legal system down to their everyday practices, all while being exposed to fierce exploitation in the informal labor market, compounded by the constant looming threat of deportation. However, by cultivating solidarity, they also create ways to navigate and negotiate the restrictions of the asylum regime and never give up claiming their lives. By locating women’s experiences at the center of the research, I aim to make refugee women’s experiences and the structures that reshape them visible and to map the relationship between heteropatriarchy, racism, and capitalism.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".