‘Am I a terrorist or an educator?’ Turkish asylum seekers narratives on education rights violations after a crackdown following the 2016 failed coup attempt in Turkey
Bibliographic record
Abstract
Democratisation in Turkey collapsed in the wake of the 2016 failed military coup and the crackdown that followed, with President Recep Tayyip Erdoğan launching a widespread rollback of academic and other liberties, systematically purging civic institutions of political opponents and critics that significantly harmed intellectuals, students, and educational rights. This paper analyses the narratives of Turkish citizens who were prosecuted, dismissed, abused, tortured, victimised, and imprisoned during the State of Emergency (OHAL) initiated after the failed coup attempt in July 2016. This narrative approach examines the transcripts of in-depth interviews about the experiences and critical life stories of 20 individuals now living in the United States, Canada, and Europe. Also included are field notes and documents that reveal the authorities’ violations of their educational human rights. These included the denial of education, unwarranted dismissal, elimination of academic freedom of thought, and harassment of academics and their children. Such violations have created a brain drain of educators fleeing the country. These deleterious changes in the Turkish education system have had severe social and political effects and have produced an education system that fails to meet the country’s needs, which, if not remediated, will ripple through the generations, dimming the nation’s future.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".