Waiting for justice amidst the remnants: urban development, displacement and resistance in Diyarbakir
Bibliographic record
Abstract
This paper looks into the lives of displaced people and their material bonds with the past while waiting for justice during exceptional times in Diyarbakir, Turkey’s Kurdistan. Diyarbakir is known for its central location in the Kurdish conflict in Turkey for many decades. In August 2015, the old city of Diyarbakir called Sur joined other resisting cities and districts in the Kurdish region of Turkey, where Kurdish militants built barricades all around their controlled neighbourhoods against the state’s violent attacks and declared autonomy. Months after the beginning of the resistance, the Turkish state managed to take back control of Sur after heavy clashes between Turkish security forces and Kurdish militants. All the resisting neighbourhoods of Sur were razed to the ground, and close to 24,000 residents were displaced. Since then, a massive urban transformation project for Sur has been in the making. The everyday survival of the displaced people from Sur depends on the ways they negotiate with the state in a long process of waiting. Bringing together different accounts of waiting, I intend to shed light on temporal dimensions of forced displacement embedded in the remnants of the past and shaped by present history of subjugation and state violence.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".