Bibliographic record
Abstract
Alors que la campagne présidentielle américaine est lancée dans sa phase finale, Sens Public, en collaboration avec ilovepolitics.info, présente une série de critiques hebdomadaires des quelques grands ouvrages américains qui apparaissent essentiels pour comprendre les aspects déterminants de la course à la Maison Blanche. Jusqu’à l’élection du 4 novembre 2008, chaque semaine, un article analysant un livre qui a connu un grand succès aux États-Unis, ou que les commentateurs politiques américains ont largement mentionné à l’appui de leurs propres analyses, se trouve disséqué et replacé dans un contexte plus large. Chacun d’eux porte sur des sujets qui se perdent trop souvent dans le vacarme médiatique que créent les campagnes. Ces critiques espèrent mettre davantage en perspective ces enjeux majeurs, essentiels pour comprendre le devenir de l’Amérique contemporaine.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".