Expropriating the dead in Turkey : how the Armenian quarter of İzmir became Kültürpark
Bibliographic record
Abstract
The İzmir fire of 1922, as well as the subsequent re-building of the fire area according to a new master plan, have been studied quite extensively, but so far, nobody has looked into the politics of expropriation and compensation surrounding them.This article studies the expropriation of the İzmir fire area in the late 1920s and the subsequent urban renewal project of the 1930s by contextualizing it within the history of the dispossession of Armenians and Orthodox Greeks in the late Ottoman Empire and early republican Turkey.As I show, some property owners in the fire area were able to negotiate much better terms for their expropriation than others.Those who had been killed or expelled in 1922 and whose physical property had been destroyed in the fire were also expropriated, but never compensated.Their physical dispossession was thus repeated in the legal realm.Based on a variety of archival sources from Turkish and Western archives, this article shows that Armenian compensation claims were pocketed by the İzmir municipality and other state agencies.This, however, aroused the interest of the treasury, which in 1941 claimed those compensation sums that should have been paid for plots in the the former Armenian quarter now covered by kültürpark.I argue that the treasury did so because the abandoned property law of 1922 had officially made the treasury the universal custodian of "absent" property owners.
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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 | 0.008 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".