MétaCan
Menu
Back to cohort
Record W4386544701 · doi:10.20378/irb-50144

Expropriating the dead in Turkey : how the Armenian quarter of İzmir became Kültürpark

2021· preprint· en· W4386544701 on OpenAlexaboutno aff
Ellinor Morack

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)ArmenianAncient historyHistoryGeographyArchaeology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.038
GPT teacher head0.250
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicArchaeological Research and ProtectionFrench-language works237,207