Bibliographic record
Abstract
Nelly Arcan et Kathy Acker, deux auteures ayant marqué leur milieu littéraire — celui québécois contemporain pour l’une, celui punk américain des années 80 pour l’autre — partagent entre autres thématiques similaires, une réflexion sur l’identité, et plus spécifiquement sur l’identité de genre, telle qu’elle est créée par le langage. Si chacune se constate pareillement faite par le discours, leur oeuvre n’en est pas moins, de l’une à l’autre, singulière. Ce texte s’interroge sur la construction d’une identité fluide, variable, toujours réinterprétée, telle qu’elle peut se lire dans les romans de Kathy Acker, en la comparant à l’identité figée dans les mots et leur cohérence écrasante des récits de Nelly Arcan. Comment penser le rapport à l’identité chez chacune, telle que mise en scène dans des personnages à la fois vidés et saturés par le langage ?
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".