Bibliographic record
Abstract
Alors que la compassion et l’empathie sont promues dans nos sociétés comme des slogans, cet article entend montrer comment la compassion a été critiquée et perçue comme un faux-semblant, en particulier par Virginia Woolf et Hannah Arendt, au lendemain de la Première puis de la Seconde Guerre mondiale. À quelles conditions une authentique compassion, qui naît de la confidence reçue, peut-elle être effective ? La relation de confiance qui s’établit entre deux personnes, et qui permet la confidence, suffit-elle ? Nous montrerons comment la compassion qui résulte de la lecture permet une compassion authentique parce qu’elle sollicite l’imagination : alors que dans la vie réelle, les positions de chacun restent inchangées, quelle que soit la compassion éprouvée devant le spectacle de la souffrance, la lecture permet un déplacement de la subjectivité. Parce que je lis la souffrance de qui l’a racontée pour l’avoir vécue, j’éprouve une compassion plus authentique que lorsque j’en suis témoin. La compassion imaginaire est alors une authentique expérience, qui met en évidence l’importance de la vulnérabilité et de la confiance.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 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".