Dragomans and “Turkish Literature”: The Making of a Field of Inquiry
Bibliographic record
Abstract
Abstract Theories of cultural and linguistic mediation have tended to posit intermediaries as conduits through which one culture/language either enters another unproblematically, or gets “distorted” due to intermediaries’ incompetence or self-interest. Both these perspectives presuppose stable, well-bounded, and coherent cultures/languages as what intermediaries purportedly mediate. Instead, this paper proposes an understanding of cultural and linguistic mediation as a process that constitutes its objects, that is, as an essential dimension of all acts of cultural and linguistic boundary-making. It focuses on dragomans (diplomatic interpreters) who operated at the interface between the Ottoman government and foreign diplomats to the Porte throughout the early modern period. The paper suggests how dragomans’ practices of knowledge production were profoundly collaborative, involving a range of Ottoman and Venetian interlocutors. Such practices thus belie any facile distinction between “local” and “foreign,” but rather challenge us to consider the emergence of “Oriental” studies as a dialogical project that necessitated ongoing recalibrations of prior knowledge through a multiplicity of perspective, where diplomatic institutions and epistemologies played a key role.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.010 | 0.047 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| 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".