Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Résumé : La présente étude, menée dans le cadre du « Programme 13-Novembre » consacré à la mémoire des attentats de novembre 2015 en France, porte sur un corpus de près de 1 000 témoignages recueillis en 2016 auprès de personnes diversement impactées par ces événements (rescapés, intervenants professionnels, proches de victimes, habitants des quartiers touchés, habitants d’autres villes de France, etc.). Pour mettre au jour les marqueurs linguistiques les plus spécifiques de certains sous-corpus, ces témoignages ont été analysés à l’aide d’un logiciel d’analyse de données textuelles. L’objectif est d’en apprendre davantage sur la manière dont s’élabore la mémoire collective, en faisant la part des facteurs sociaux susceptibles de déterminer la fabrication des souvenirs individuels.
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.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it