Bibliographic record
Abstract
<JATS1:p>Mazzoleni, Stewart, Horsfield, and their contributors analyze the two-way relationship of the mass media and the contemporary phenomenon of extreme right wing neo-populist political parties which emerged in the closing years of the 20th century across the world. The success of Jean-Marie Le Pen, leader of the neo-populist Front National, in the first French presidential ballot in April 2002 shows that these extremist parties have strong, if varying, electoral support. Drawn into reporting on the policies and antigovernment critiques of the new parties, the mass communication institutions, especially those engaged in news production, have been challenged by a variety of unconventional but effective political campaign strategies that caused many media professionals considerable challenge.</JATS1:p> <JATS1:p>Taking an approach informed by mass communication theory, this book analyzes eight case studies of the interaction of news media dynamics and neo-populism in Austria, Australia, France, Canada, India, Italy, the United States, and the Latin American region against the background of widespread disenchantment with traditional parties and the complacency and cynicism of popularly elected governments. Insights into media responses reveal how dependent on media coverage the neo-populist parties were and how, in many cases, the media were initially unequal to the confronting ideologies of the new parties. Although the news media exploited the new parties, new parties exploited the news media as well in quite shrewd and original ways. This is an important resource for scholars, students, and other researchers involved with political mass communications and right-wing political organizations.</JATS1:p>
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".