Comment des think tanks progressistes ont tenté de combler le retard de la gauche dans la « guerre des idées » aux États-Unis : le Progressive Policy Institute et le Center for American Progress*
Bibliographic record
Abstract
Aux États-Unis, l’influence politique des think tanks conservateurs a été grandement étudiée par les chercheurs, qui ont accordé moins d’attention aux think tanks progressistes. Dans cet article, nous nous intéressons au Progressive Policy Institute et au Center for American Progress. Nous revenons sur leur contexte de création, nous décrivons les tactiques employées pour faire leur place dans le marché des idées et nous analysons l’influence qu’ils ont eue auprès d’administrations démocrates. Nous montrons que la création de ces centres de recherche répond à un contexte politique marqué par une prépondérance des idées conservatrices. Ces think tanks libéraux ont ainsi pour raison d’être, dans un premier temps, de redonner leur place aux idées libérales et, dans un second temps, de proposer une feuille de route au Parti démocrate afin de reprendre le pouvoir à la Maison-Blanche.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".