The media and neo-populism : a contemporary comparative analysis
Bibliographic record
Abstract
Tables and Figures Acknowledgments Foreword The Media and the Growth of Neo-Populism in Contemporary Democracies by Gianpietro Mazzoleni Striking a Responsive Chord: Mass Media and Right Wing Populism in Austria by Fritz Plasser and Peter A. Ulram The Media and Neo-populism in France by Guy Birenbaum and Marina Villa The Northern League and the Italian Media System by Roberto Biorcio The Bharatiya Janata Party, Ayodhya, and the Rise of Populist Politics in India by John McGuire and Geoffrey Reeves One Nation and the Australian Media by Bruce Horsfield and Julianne Stewart More Bad News: News Values and the Uneasy Relationship between the Reform Party and the Media in Canada by Richard W. Jenkins Ross Perot's Outsider Challenge: New and Old Media in American Presidential Campaigns by Jonathan Laurence Media Populism: Neo-populism in Latin America by Silvio Waisbord Conclusion: Power to the Media Managers by Julianne Stewart, Gianpietro Mazzoleni, and Bruce Horsfield Index About the Editors and Contributors
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.038 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 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".