Making Scholarship Public: Collaboration and Interdisciplinarity in Early Modern Studies
Bibliographic record
Abstract
How can collaborative, interdisciplinary research on early modern Europe expand the reach of the humanities beyond the academy? In what ways could such a “public turn” enhance the effectiveness of humanities research and teaching? This essay recounts how a number of large, interdisciplinary projects in which the author has been centrally involved grew from scattered intuitions toward collective clarity; how they gathered people from different disciplines around shared questions and changed the ways participants saw their own work; how they enabled students and postdocs to grow as original thinkers by taking part in collaborative research; and how large-scale research that asks big questions might be able to build bridges between the academy and the multiple publics in Canada and beyond in ways that enhance both the university and society. Comment la recherche collaborative et interdisciplinaire en études des débuts de la modernité peuvent atteindre un public au-delà du monde universitaire ? Dans quelle mesure cet accès public pourrait améliorer l’efficacité de la recherche et de l’enseignement en sciences humaines ? Cet article retrace comment un certain nombre de grands projets interdisciplinaires dans lesquels l’auteur a été impliqué, se sont développés à partir d’intuitions indépendantes vers une vision collective. On y retrace aussi comment ont été rassemblés des chercheurs de différentes disciplines autour de questions communes et comment cela a amené les chercheurs à considérer leur travail différemment, comment ces projets ont permis à des étudiants et des post-doctorants de devenir des chercheurs innovants en participant à des collaborations de recherche, et comment des projets de recherche d’ampleur posant de grandes questions peuvent créer des ponts entre le milieu universitaire et plusieurs publics canadiens et étrangers de façon à faire avancer à la fois l’université et la société.
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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 | 0.048 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.038 | 0.109 |
| Scholarly communication | 0.038 | 0.041 |
| Open science | 0.003 | 0.034 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".