Sophie BOULAY (2015), Usurpation de l’identité citoyenne dans l’espace public. Astroturfing, communication et démocratie. Québec, Presses de l’Université du Québec
Bibliographic record
Abstract
L’astroturf est un gazon synthetique que l’on trouve dans les stades sportifs. Il ne jaunit jamais, ne necessite aucune tonte, n’a pas besoin d’etre arrose et ne se change pas en boue lorsqu’il pleut. En somme, il n’a aucun defaut du vrai gazon et possede des qualites 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 litterature la facon de qualifier les strategies de communication se donnant toutes les apparences du...
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".