Les Hawai’i saisies par la géo-graphie: l’espace utopique de Mark Twain
Bibliographic record
Abstract
À travers Mark Twain et les Hawai’i, ce texte propose d’analyser les relations entre images littéraires et géographicité. La littérature pourrait bien constituer une puissante machine à fabriquer de la différenciation spatiale, en tant qu’elle convertit l’étendue terrestre en signes, en lieux qui accèdent à la signification par l’imaginaire, lequel peut prendre la forme de l’écriture. Celle-ci ordonne le monde et donne en retour prise pour le transformer. Si Mark Twain a prolongé ainsi certaines images fabriquées par les découvreurs, il en a fourni aussi de nouvelles qui sont venues compliquer le palimpseste mettant en désir les Hawai’i dans l’imaginaire américain. À travers le monde subjectif de l’écrivain et les figures de l’altérité qu’il met en scène, l’utopie hawaiienne peut être lue comme un espace dont l’idéalisation rend possible le développement d’une catharsis.
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 | 0.011 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".