« Je ne suis pas raciste, mais je suis réaliste »
Bibliographic record
Abstract
Résumé : Traditionnellement, les femmes étaient perçues comme accessoires dans les mouvements des droites extrêmes. Durant la pandémie, plusieurs influenceur·euses ont fait preuve d’opportunisme pour augmenter leur nombre d’abonné·es (Stewart et al., 2023). Dans cet article, la théorie du cadrage de l’action collective est mobilisée pour analyser le discours tenu sur Facebook par trois influenceuses anti-mesures sanitaires lors de la période d’instauration du passeport sanitaire. Les analyses mettent en évidence des discours réactionnaires et libertariens. Ces influenceuses nourrissent le ressentiment en tant que femmes militantes, identifiant « l’injustice » et encourageant l’action collective en fusionnant les cadres d’extrême droite et les mouvements « New Age ». Elles se positionnent comme des résistantes face à la dévaluation des besoins du peuple de la part des élites et du gouvernement et les accusent de les priver de liberté.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".