Bibliographic record
Abstract
Cet article examine comment Google est susceptible d’affecter la mémoire. Pour ce faire, plusieurs détours sont nécessaires : après un rappel de quelques notions élémentaires sur la mémoire, nous examinerons rapidement certaines techniques de mémoire pour mieux caractériser l’écriture comme instrument de mémoire. Les supports de l’écriture retiendront ensuite notre intérêt, avec une attention particulière pour le codex qui, avec sa géométrie particulière, a dominé l’essentiel des deux derniers millénaires. Enfin, nous montrerons comment le codex donne lieu à deux formes d’analyse : la société des textes et la sociologie des textes. Tandis que la numérisation touche aux deux, Google retravaille en profondeur la société des textes, et c’est sur cette base que nous montrerons comment ce dispositif restructure profondément notre mémoire, comment il crée un trompe-l’oeil mémoriel.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.013 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".