Manuscript Sources and Medial Transfer in the Research of Early Modern Disputations: From Administration to Exchange of Knowledge
Bibliographic record
Abstract
The scholarship of early modern disputations has concentrated on printed theses, since they are one of the most common types of prints in the era. Although preserved minutes transcribing what was said while these theses were discussed are rare, this article argues that it is worth giving due consideration to such manuscript sources when it comes to researching this very topic. Endeavouring to investigate Catholic and Protestant examples from Central Europe between 1580 and 1660, I explore four areas where handwritten documents, such as university records and student notebooks, have the potential to nuance our understanding of different traditions pertaining to disputation. In comparison to the printed disputations typical for Protestant Europe, manuscripts with Catholic and Jesuit provenance reveal a different function of scholarly debates, which were less focused on the individual performance of the respondent and served more as a method of recapitulation in everyday education. Protestant examples, on the other hand, demonstrate that disputations played a distinguished role in the exchange of scientific knowledge and expertise. During the process of professors and students conveying information from their homeland to university centres and back, disputations changed medium from print to manuscript, and vice versa.
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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 | 0.043 | 0.109 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.013 | 0.019 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".