Promoting Open Access and Innovations: From Synergies to Le Centre de recherche interuniversitaire sur les humanités numériques
Bibliographic record
Abstract
This article discusses the relationship between digital humanities and disciplinary boundaries in the last decade, primarily in the context of the national project Synergies. It offers first an overview of Synergies as a concrete example of the way technological change impacts the very notion of disciplines by trying to create a platform that was interdisciplinary by nature, then discusses the creation of a new Digital Humanities centre in Québec—Le Centre de recherche interuniversitaire sur les humanités numériques – and the ways it was conceived as encompassing a range of disciplinary approach.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.012 | 0.050 |
| Scholarly communication | 0.029 | 0.023 |
| Open science | 0.003 | 0.036 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".