Bibliographic record
Abstract
Résumé Au cours des dernières années, la question de la dynamique culturelle est revenue à l’avant-plan des préoccupations. Les travaux qui en traitent se caractérisent souvent par une approche essentiellement théorique. Il nous semble plus fructueux d’examiner ces questions à partir de cas réels. Dans cette perspective, nous retracerons la « biographie » de Halloween, une fête tiraillée entre un récit d’origine, qui affirme sa persistance millénaire, et une histoire récente, faite de transformations successives. Nous suivrons sa trajectoire depuis son apparition aux Temps modernes dans les îles anglo-irlandaises jusqu’à ses avatars contemporains, en passant par son implantation aux États-Unis et au Canada à la fin du xix e siècle. Cette analyse mettra en évidence qu’une des conditions de la persistance de cette célébration est justement la grande plasticité des usages qui lui sont associés.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".