Bibliographic record
Abstract
I was born in 1920 in Turkey in a village near Mardin. My father's family included 400–500 young men. We came here [to Syria] in 1925. The French were in Syria. They offered us shelter and were very good to us. We were tyrannized by the Turks who were against all Islamic teachings. The Turks were not true Muslims. They wanted us to assimilate. They wanted to force all the people in the villages to wear hats [this is a reference to Mustafa Kemal's efforts to get Western dress adopted by all Turks]. We fled after the revolution led by Shaykh Said in 1920. The Kurds revolted against the Turks. They demanded a self-governed Kurdish state in Turkey. When Shaykh Said was hung by the Turks, many Kurds fled Turkey and came to Syria. I remember we all travelled in big groups, seven or eight families and all of their sheep and cattle which they sold on the way at Ras al-‘Ain. We all walked to Dayr al-Zor and then to Al-Sham [Damascus]. We had relatives here who received us and helped us to settle. This quarter had only Kurds who spoke Kurdish. What is funny was that when my father left Turkey, he had no idea there were other people than Kurds in the world. He was quite shocked when he got to Dayr al-Zor and heard people talking other languages. He used to say that he almost turned back there to return to Turkey. When we had been in Syria for six or five years we were granted citizenship [by the French mandate authority]. […]
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".