Bibliographic record
Abstract
Why Can't I Be You traite des mecanismes d'identification et de nonidentification Cl l'autre qui surviennent en amour et qui se traduisent par differents phenomenes de meconnaissance dans la relation entre Alexandra, une femme minuscule et feminine, douce comme un oiseau , et William, un homme lourd, studieux et constipe, ayant les mains comme des jambons et les cuisses comme des [Lancs de breuf . Leur mauvaise lecture respective de l'autre atteint son parowysme lorsqu'Alexandra tue le lapin que William lui a apporte comme animal de compagnie, temoignage de son affection, geste qu'Alexandra rejette, cedant plutot aux fantasmes de ce Cl quoi ressemblerait l'amour entre ses mains fortes, la poussant contre le mur de telle fa(on, entrechoquant bruyamment la vaisselle, le rebord en saillie du buffet contre sa colonne vertebrale, les coutures dechirees, les ecchymoses de ses mamelons... William prefere la courtiser Cl travers Eschyle, Sophocle et Plotin... l'eolouir avec des mots, la distraire avec des mots .
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.040 | 0.022 |
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".