Bibliographic record
Abstract
Le mot de l'éditeurChers lecteurs, chères lectrices, S'endimancherLe dimanche, quelque part au début du siècle, la femme ne sortait pas sans une coiffe.À la messe et selon la saison, c'est un défilé digne des plus grands designers que l'on pouvait voir, où les femmes se pavanaient avec leurs nouvelles mantilles ou capelines fabriquées d'étoffes ou d'ornements originaux.Un spectacle en soi.La mode est alors synonyme d'élégance et de rang social.L'avènement du prêt-à-porter ou de l'élégance bon marché transforme la tradition vestimentaire et l'économie domestique.Cette transformation plus libérée et moins conventionnelle fait jaser.L'étoffe s'allège et les vêtements laissent de plus en plus entrevoir la silhouette jadis cachée.Les temps changent.Quoique toujours aussi important au niveau de l'identité, la mode est devenue depuis un moyen d'expression axé sur le confort et l'élégance avec en moins les convenances.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.197 | 0.104 |
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".