Bibliographic record
Abstract
Quand j’évalue un article soumis à Recherches théâtrales au Canada, je me pose toujours une série de questions, dont celles-ci : la contribution repousse-t-elle les limites des études théâtrales et des études de performance de façon nouvelle, intéressante ou provocante? Nous permet-elle de voir sous un jour nouveau des matériaux que nous connaissons déjà? Fait-elle la lumière sur un sujet que nous avons négligé? Nous présente-t-elle de nouvelles sources primaires? Propose-t-elle une méthodologie innovatrice, une nouvelle approche théorique? Bref, le texte offre-t-il à notre champ de recherche quelque chose de différent et cette différence est-elle pertinente? Je me réjouis de pouvoir dire que les six articles rassemblés dans ce numéro de RTAC repoussent les limites des recherches en théâtre et en performance, chacun à sa façon. Ce même travail se poursuit dans l’excellent Forum préparé sous la direction d’Adriana Disman, lequel explore quatre prestations qu’elle a retenues pour la série LINK & PIN en 2013-14.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.010 | 0.022 |
| Scholarly communication | 0.029 | 0.022 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.032 | 0.007 |
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".