Du dévoilement de certaines images mentales liées à la France dans les Conventions Nationales Acadiennes de 1881 à 1937 : une analyse rendue possible par Hyperbase
Bibliographic record
Abstract
Le présent article vise à rendre compte d’une recherche mythocritique effectuée à l’aide du logiciel de traitement de données Hyperbase sur une partie du vaste corpus des conventions nationales acadiennes, de 1881 à 1937, corpus double, à la fois discours politique et discours littéraire. Il s’agit de déterminer comment est représentée la France à l’intérieur des discours et pourquoi ces images sont-elles si présentes au sein des Conventions. Quel rôle jouent les références à la France à l’intérieur des grands discours nationalistes ? En quoi participent-elles de la construction de l’identité nationale acadienne ? Les hypothèses de travail ainsi que leurs vérifications ont été accomplies grâce aux possibilités du logiciel, en exploitant les fonctions documentaires et statistiques.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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".