A Selective Annotated Bibliography of Resources on the Summary in French and English/Bibliographie selective annotee sur le resume de texte, en Frarncais et en Anglais
Bibliographic record
Abstract
This annotated bibliography lists selected resources in English and French on the topic of the summary.The authors have focussed primarily on frequently cited works in the field, on recent publications, and on publications likely to be of particular interest to the Technostyle readership.The bibliography lists only books and articles devoted specifically to the summarization process or to the summary in one of its many forms.The bibliographic references are organized thematically under five headings: pedagogical perspectives; empirical research; professional applications; abstracts; and automatic summarization.Both paper and web resources are included.Cette bibliographie annotee porte sur le resume et comprend des titres en franrais et en anglais.Les ouvrages retenus sont ceux qui sont les plus frequemment cites ou les plus recents, ou encore ceux qui presentent un interet pour les lecteurs et les lectrices de Technostyle.Elle n'inclut que des monographies et des articles portant exclusivement sur les differentes formes de resume ou sur l'activite resumante.Elle se subdivise en cinq themes, lesquels sont generalement abordes dans la documentation specialisee sur le resume: perspectives pedagogiques, procedes de reduction, applications professionnelles, resume analytique et resume automatique.Les references renvoient a des sources imprimees OU electroniques.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.032 | 0.042 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.104 | 0.032 |
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".