Bibliographic record
Abstract
Cet article présente les résultats de huit ans de travail sur le concept d’éditorialisation, réalisés dans le cadre du séminaire international « Écritures numériques et éditorialisation » que j’ai coorganisé avec Nicolas Sauret depuis 2008. Je propose de définir l’éditorialisation comme l’ensemble des dynamiques qui produisent l’espace numérique. Ces dynamiques peuvent être comprises comme les interactions d’actions individuelles et collectives avec un environnement numérique. À partir de cette définition je propose de décrire le fonctionnement des instances d’autorité dans l’espace numérique.
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 | 0.050 | 0.272 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.051 | 0.026 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.108 | 0.043 |
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".