Bibliographic record
Abstract
"L'élaboration de ma théorie a été appuyée sur un immense travail de terrain, l’analyse systématique de la chose imprimée produite en langue française au cours d*une année que j*avais choisie avec quelques bonnes raisons contingentes: l*année 1889. Pourquoi? Mil huit cent quatre-vingt-neuf est simplement une «riche» année et c’est une année-charnière: c’est tout à la fois l’année du centenaire de la Révolution, l’année de l’Exposition universelle, de la Tour Eiffel, l’année de la résistible ascension et de la chute du Brav’ général Boulanger, l’année du Drame de Meyerling et de bien d’autres événements prégnants. J’yallais toutefois à l’aveuglette; je n’étais aucunement un dix-neuviémiste et j’avais tout à apprendre." CONSULTEZ LA RÉÉDITION NUMÉRIQUE INTÉGRALE EN LIGNE ET EN LIBRE ACCÈS DE «1889 : UN ÉTAT DU DISCOURS SOCIAL» DE MARC ANGENOT http://www.medias19.org/index.php?id=11003
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".