Traduire jusqu’au point de non-pouvoir : approche de l’engagement blanchotien
Bibliographic record
Abstract
In the early 60’s, Blanchot participated with a group of European intellectuals in the process of conceptualizing an international journal based on translation. In our intent to inquire into Blanchot’s approach of « engagement » in the course of the project, the present study will examine differences between Blanchot and Levinas in regards to the notion of « non-pouvoir », which directs the task of the translator towards the point of fascination or inspiration in Blanchot’s terms. The point of no-power opens possibilities to various modes of translations, questioning the limits of the subject-translator by challenging the proper form of the Original. Notre intention ici est d’aborder, à partir de la conceptualisation d’une revue que M. Blanchot a créé avec d’autres intellectuels européens au début des années soixante, une réflexion sur l’engagement blanchotien, et de centrer notre analyse sur la différence de la notion de « non-pouvoir » entre Blanchot et Levinas, le point de fascination, ou d’« inspiration » pour reprendre les termes de Blanchot. Le concept de traduction sera l’occasion pour nous d’interroger la capacité du sujet-traducteur à remettre en cause l’idée du sens propre d’un texte.
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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.061 |
| Scholarly communication | 0.023 | 0.020 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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".