Speaking of Women? Exploring Violence against Women through Political Discourses: A Case Study of Headscarf Debates in Turkey
Bibliographic record
Abstract
This paper explores the production of violence against women through political discourses in Turkey. Since the foundation of the Republic (1923), women’s bodies have been on the agenda as the markers of secular Turkish modernity. With the rise of political Islam as of the 1970s, the image of the headscarved woman has challenged the construction of “modern Republican woman” and the association of women’s bodies with secularism. Especially after the 1980s with the introduction of bans, “the headscarf issue” has intensified and become the embodiment of the clash between political Islam and the official secularist ideology. By drawing on the sexualizing aspects of the headscarf and its significance in the construction of female honour, I will demonstrate how women’s bodies are turned into readily available topics for consumption in politics. I argue that headscarf debates have factored into patriarchal discourses, which inflict violence on women on both discursive and material levels. By analysing a few cases on media reflections and art projects on the “headscarf debate”, I aim to show how women’s bodies become vulnerable to violence through political discourses.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".