Knowledge is a commons - Pour des savoirs en commun
Bibliographic record
Abstract
L’Association Canadienne de Littérature Comparée/Canadian Comparative Literature Association (ACLC/CCLA) célébrait en 2019 son cinquantième anniversaire. Le colloque annuel de l’association, qui s’est tenu dans le cadre du Congrès des sciences humaines du Canada du 2 au 5 juin 2019 à l’Université de la Colombie-Britannique (UBC) à Vancouver, a été l’occasion de faire le point sur la place du comparatisme au sein de nos institutions. Pour ce faire, nous avons organisé une table ronde bilingue conjointe réunissant des membres de la communauté comparatiste et de la communauté des humanités numériques qui réfléchissent et mettent en œuvre des pratiques éditoriales collaboratives. Il nous importait ainsi que nos discussions se traduisent par une intervention concrète, pensée et écrite de façon collaborative et qui puisse “manifester” ce que la littérature comparée permet de mettre en œuvre. Le manifeste qui apparaît dans ces pages, “Knowledge is a commons - Pour des savoirs en commun”, présente le résultat de notre réflexion collective avec l’ambition d’offrir un point de départ pour davantage de travail collaboratif.
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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 | 0.020 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.031 | 0.059 |
| Scholarly communication | 0.030 | 0.016 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 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".