Bibliographic record
Abstract
rofesseure, Andersen profite en effet d'un congé sabbatique pour écrire De mémoire de femme (1982).Livre-matrice, il inaugure une œuvre à forte tendance autobiographique et éclairée par le féminisme.En un sens, Andersen est essentiellement l'auteure d'un seul grand livre, qui est sa vie.Inspiré, dense, finement maîtrisé, De mémoire de femme reste encore aujourd'hui, après une quinzaine d'ouvrages de fiction, la plus belle réussite de l'auteure.Le nom du personnage central, Anne Grimm, est un emprunt aux célèbres frères et conteurs allemands.Il camoufle habilement l'identité de l'écrivaine et donne le ton de l'ouvrage, entre fiction (c'est affaire de composition) et autobiographie.Il inscrit aussi d'emblée le personnage dans une quête identitaire, qui va se donner à lire sur le plan géographique (l'émigration vers le Canada) et sur le plan personnel d'une libération féminine, qui à la fin prendra aussi la forme d'une revendication féministe.Le titre du livre, au-delà de la visée individuelle, est chargé de tout un poids collectif.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 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".