Paris dans l’optique : cadre photographique et cadre littéraire chez Philippe Delerm
Bibliographic record
Abstract
« Ajoutez deux lettres à Paris : c’est le paradis » (Renard 202) : tel est l’engouement qui motive le projet de tant d’ouvrages qui prétendent à capturer la capitale française. Des photographies de Doisneau aux textes canoniques de la littérature de Zola ou d’Hugo, il faut à tout prix documenter la Ville-Lumière afin de saisir cet espace protéiforme. Les amoureux de l’Hôtel de Ville de Philippe Delerm et Paris l’instant, ouvrage photo-littéraire réalisé conjointement avec sa femme Martine Delerm, s’inscrivent dans la continuité de cette tradition qui saisit le lieu, d’une manière ou d’une autre. Bien que très différents, ces deux projets explicitent un questionnement quasi-millénaire : Qu’est-ce que Paris ?
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 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".