Is Turkey coming to terms with its past? Politics of memory and majoritarian conservatism
Bibliographic record
Abstract
There is unprecedented domestic and international interest in Turkey's political past, accompanied by a societal demand for truth and justice in addressing past human rights violations. This article poses the question: Is Turkey coming to terms with its past? Drawing upon the literature on nationalism, identity, and collective memory, I argue that the Turkish state has recently taken steps to acknowledge and redress some of the past human rights violations. However, these limited and strategic acts of acknowledgment fall short of initiating a more comprehensive process of addressing past wrongs. The emergence of the Justice and Development Party as a dominant political force brings along the possibility that the discarded Kemalist memory framework will be replaced by what I callmajoritarian conservatism, a new government-sanctioned shared memory that promotes uncritical and conservative-nationalist interpretations of the past that have popular appeal, while enforcing silence on critical historiographies that challenge this hegemonic memory and identity project. Nonetheless, majoritarian conservatism will probably fail to assert state control over memory and history, even under a dominant government, as unofficial memory initiatives unsettle the hegemonic appropriation of the past.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".