Alan Renwick, Jean-Benoit Pilet, Faces on the Ballot. The Personalization of Electoral Systems in Europe , Oxford, Oxford University Press, 2016, 338 p.
Bibliographic record
Abstract
L’article vise à analyser les processus de cadrage de l’incertitude et de l’expertise légitime durant la controverse sur le gaz de schiste en France et au Québec (Canada). Il s’agit d’étudier la controverse entre 2010 et 2015 et de comprendre quels sont les mécanismes mis en œuvre pour tenter de réduire l’incertitude, quel type d’incertitude est ciblé, par quels outils, par quels acteurs et avec quels effets sur la trajectoire politique de la controverse. L’analyse développe un cadre théorique innovant faisant appel à l’analyse des politiques publiques, la sociologie de l’expertise et la sociologie de la participation publique. La comparaison de l’action publique en France et au Québec met en relief des attitudes contrastées face à un contexte similaire d’incertitude. Alors qu’en France, l’incertitude est confinée à la technique de fracturation hydraulique, au Québec, elle s’étend à de multiples domaines scientifiques. L’article défend ainsi que l’incertitude est socialement produite, politiquement cadrée et scientifiquement informée.
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 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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".