Introduction: As if from nowhere… artists’ thoughts about research-creation
Bibliographic record
Abstract
Cette section inaugurale de Pratiques met en valeur, du point de vue de la pratique et de la recherche-création, la réflexion des artistes quant à leurs processus de travail et leurs oeuvres. S’il est clair que les artistes travaillant dans les universités font face à des défis particuliers, liés aux demandes croissantes de la part des institutions universitaires d’articuler leurs cadres méthodologiques et l’application de ceux-ci dans leur travail, ils jouissent également de la possibilité d’approcher, de partager et de présenter d’innombrables manières le fruit de leurs investigations créatives réalisées dans le contexte de la recherche-création. Les contributeurs à cette section – Marlene MacCallum, David Morrish, Christof Migone, Donna Szoke, Barbara Meneley et Risa Horowitz – s’expriment ici sur leurs recherches et sur les approches méthodologiques qu’ils privilégient. Ils révèlent et articulent l’éventail de leurs démarches, ainsi que les diverses façons dont ils conçoivent les méthodes, les pratiques et les modes de dissémination, de documentation et d’exposition dont disposent les artistes pour la recherche-création.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.027 | 0.018 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.018 |
| Insufficient payload (model declined to judge) | 0.020 | 0.008 |
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".