Bibliographic record
Abstract
In this volume the McGill University Research Group on Transmission, Translation, and Transformation in Medieval Cultures and their collaborators initiate a new reflection on the dynamics involved in receiving texts and ideas from the antiquity or from other contemporary cultures. For all their historic specificity, the western European, Arab/Islamic and Jewish civilizations of the Middle Ages were nonetheless co-participants in a complex web of cultural transmission that operated via translation and inevitably involved the transformation of what had been received. This threefold process is what defines medieval intellectual history. Every act of transmission presumes the existence of some ‘efficient cause’ – a translation, a commentary, a book, a library etc. Such vehicles of transmission, however, are not passive containers in which cultural products are transported. On the contrary: the vehicles themselves select, shape, and transform the material transmitted, making ancient or alien cultural products usable and attractive in another milieu. The case studies contained in this volume attempt to bring these larger processes into the foreground. They lay the groundwork for a new intellectual history of medieval civilizations in all their variety, based on the core premise that these shared not only a cultural heritage from antiquity but, more importantly, a broadly comparable ‘operating system’ for engaging with that heritage. Each was a culture of transmission, claiming ownership over the prestigious knowledge inherited from the past. Each depended on translation. Finally, each transformed what it appropriated.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.120 | 0.054 |
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".