« Détails, gros plan, micro-analyse » : Carlo Ginzburg lit Siegfried Kracauer
Bibliographic record
Abstract
L'article consacr en 2006 par Carlo Ginzburg Siegfried Kracauer, l'occasion de la publication en franais de L'Histoire. Des avant-dernires choses, s'achve sur un acte de reconnaissance, aux deux sens du terme, vibrant d'une motion qui, pour tre distance , n'en est pas moins l : J'ai lu Kracauer et, en particulier History. The Last Things before the Last, trs tard, beaucoup trop tard. Pourtant, quand je l'ai lu, j'ai prouv un sentiment trange. Mme les pages les plus inattendues, comme celles, tout fait remarquables, qu'il consacre la micro-histoire, me parlaient dans une langue familire. Tout se passait comme si un cho anticip, et partiel certes, des conversations que Kracauer n'avait
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".