Sophie BOULAY (2015), Usurpation de l’identité citoyenne dans l’espace public. Astroturfing, communication et démocratie
Bibliographic record
Abstract
L’astroturf est un gazon synthétique que l’on trouve dans les stades sportifs. Il ne jaunit jamais, ne nécessite aucune tonte, n’a pas besoin d’être arrosé et ne se change pas en boue lorsqu’il pleut. En somme, il n’a aucun défaut du vrai gazon et possède des qualités que celui-ci n’a pas. En d’autres termes, c’est un faux gazon meilleur que le vrai. Le terme d’astroturfing est devenu dans la littérature la façon de qualifier les stratégies de communication se donnant toutes les apparences du...
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".