Bibliographic record
Abstract
Écrivaine américaine associée au New Journalism, Joan Didion s’est intéressée au rêve californien. Dans un essai intitulé Where I Was From, elle questionne l’emprise de certains « mythes » sur la pensée politique des Californiens. Plutôt que de restreindre son champ d’investigation au domaine public, Joan Didion étudie également l’histoire de sa famille. Cette démarche, qui se situe entre le journalisme et le récit autobiographique, s’appuie sur une documentation qui relève aussi bien de l’histoire de la Californie (récits historiques, rapports gouvernementaux, faits divers, textes littéraires, tableaux) que de sa propre vie (archives familiales, souvenirs de jeunesse). Ce travail de recherche et de réminiscence, qui vise à démystifier la Californie, se conclut par un travail de deuil, qui marque la fin des illusions. Entre journalisme littéraire et récit de deuil, Where I Was From questionne le « récit de société » dans un parcours singulier que cet article s’emploie à retracer.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".