Toward an Ontology of Trans-Imperial Ottoman Chancery Genres
Bibliographic record
Abstract
Toward an Ontology of Trans-Imperial Ottoman Chancery Genres E. Natalie Rothman (bio), Kirsta Stapelfeldt (bio), Erdem Idil (bio), Vanessa McCarthy (bio), and Qaasim Karim (bio) KEYWORDS digital ontology, genre, early modern, translation, bilingual registers Our project aims to shed light on the trans-imperial nature of Mediterranean diplomatic chancery production by considering the multiple entanglements between Ottoman and Venetian genres, textual artifacts, practices, and practitioners in early modern Istanbul. It is part of The Dragoman Renaissance Research Platform, which facilitates research into the personal and professional trajectories and textual and visual practices of dragomans (diplomatic translator-interpreters) employed by the Venetian bailate (permanent residency) in the Ottoman capital and beyond. The platform offers a range of data sets related to dragomans' activities that can be dynamically edited, analyzed, and augmented, modeling collaboration and resource sharing among scholars and students from a range of disciplinary perspectives interested in processes of cultural mediation in the early modern Mediterranean. The project harnesses the power of a multilingual, multi-disciplinary, and multi-generational collaborative team and the unique institutional context of the University of Toronto Scarborough. An ongoing collaboration between two principal investigators, E. Natalie Rothman (a historian) and Kirsta Stapelfeldt (a digital librarian) has allowed us to combine long-term infrastructural commitments and expertise from the Digital Scholarship Unit of the University of Toronto Scarborough Library with specialized contributions from numerous postgraduate, graduate, and undergraduate research assistants. Over the years, students have brought to the project unique linguistic competencies [End Page 77] (e.g., early modern Ottoman Turkish and Italian paleographies, Serbo-Croatian) and varied digital skillsets (scripting, mapping, data analytics). With long-term institutional support for the project's scoping, hosting, maintenance, and software update, we have been able to dedicate available "soft" funding (most recently: from the University of Toronto's work-study program and the Jackman Humanities Institute's Scholars-in-Residence program, as well as a multi-year Insight Grant from the Canadian Social Sciences and Humanities Research Council) to defray research assistantships and—pre-pandemic—research travel costs. The relative stability afforded by a strong institutional backing has also allowed us to forge a variety of collaborative sub-projects with subject-area experts (Ottomanists, translation studies scholars, historians of archives and knowledge production, data scientists, and open-source software developers) beyond the University of Toronto. The new phase of the project aims to create an ontology—an explicit, formal specification—of the relationships among Venetian and Ottoman terms for chancery genres, government positions, administrative units, and honorific titles, as found in a particular archival fond known as Carte turche ("Turkish Charters"). This fond, part of the Bailo a Costantinopoli series, is today housed in the Venetian State Archives, but was created and continuously elaborated in the Venetian bailate in Istanbul from 1589 to 1785. It consists of a series of some forty bound registers containing roughly two thousand copies of sultanic orders and other records issued by the imperial divan that are matched with facing Italian translations produced and often signed by specific bailate dragomans.1 The initial phase of the project entailed transcription, transliteration, and metadata creation for each record in this vast corpus. The current phase aims to use data analytics to better understand both the relationships between individual Ottoman and Italian records and specific textual practices throughout the corpus: for example, the shifting relationship between Ottoman and Venetian terms for chancery genres, government positions, administrative units, and honorific titles. Our current workflow involves atomizing information concepts—documents, archival artifacts containing them, images that represent these artifacts, persons, and agencies represented in the documents or responsible for their production, and terms used to describe all of the above, including genre terms, honorific titles, and administrative positions. Defining these information concepts as separate and unique, yet interrelated in plural and shifting configurations underpins the process of creating linked data. Unlike information [End Page 78] architectures of the past, which codified conclusions in pre-defined relational databases, this method of structuring information allows for ongoing aggregation and mutable understandings of the subjects being described and their potentially indeterminate and multiple relationships. By following linked data principles, our intent is to account for variation in how specific terms...
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".