Circulation of Orhan Pamuk’s <i>Benim Adım Kırmızı</i> [<i>My Name is Red</i>] in contemporary Chinese-Indonesian literature
Bibliographic record
Abstract
This article is an exploration of contemporary Turkish and Chinese-Indonesian literatures with regards to a mid to late 18th Century literary niche: the it-narrative. Thinking ( noesis ) back and forth between centuries and different literary genres makes ( poiesis ) the conversation possible, which addresses the socio-literary imagination of the last four centuries. The authors re-examine the genre of it-narrative outside 18th Century studies and reassess the encounter of Turkish author Orhan Pamuk and Chinese-Indonesian author Alberta Natasia Adji within the socio-cultural and historico-political context of modern Turkey and Indonesia. The question is how Pamuk’s use of prosopopoeia in his 1998 novel Benim Adım Kırmızı ( My Name is Red ) influences Adji’s decision to use the 18th Century it-narratives in her 2019 short story I am Her Bracelet . Image by H005 from Wikimedia Commons: ‘Plates for sale on the Grand Bazaar (Kapalı Çarşı) in Istanbul’, CC BY-SA 3.0
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".