Paysages de l’écrivain. Les villes biographiées (Fourvel, Pajak, Germain)
Bibliographic record
Abstract
Cet article traite de la ville dans la biographie à la lumière de trois cas de figure reliés à des écrivains. Dans le premier cas, l’analyse d’Henri Calet, Montevideo et moi (2006) de Christophe Fourvel envisage le pèlerinage de l’écrivain sur les lieux arpentés par le biographié. Dans le second cas, il s’agit, à partir de L’immense solitude (1999) de Frédéric Pajak, d’analyser le lieu en tant que scène surdéterminant l’existence des écrivains qui furent amenés à y jouer un rôle. Le troisième cas, sans doute celui qui se rapproche le plus de la biographie d’une ville, est celui de La Pleurante des rues de Prague (1992) de Sylvie Germain, où la cité paraît secréter un certain type d’histoires, une certaine mémoire qui émane du lieu sans toutefois s’y réduire.This article focuses on the city in biography in light of three biographical works dealing with writers. In the first example, an analysis of Christophe Fourvel’s Henri Calet, Montevideo et moi (2006) considers the biographers pilgrimages to places frequented by the subject of his biography. The second example is Frédéric Pajak’s L’immense solitude (1999), in which places are analyzed as stages upon which writers made to play a part, therefore overdetermining their existence. The final example, which comes the closest to being a biography of a city, is Sylvie Germain’s La Pleurante des rues de Prague (1992), where the inner city seems to exude a certain type of story, to emanate a certain memory that cannot, however, be reduced to it.
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 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".