Being European, the nationalist way: Europe in the discourse of radical right parties
Bibliographic record
Abstract
European radical right parties (RRPs) have recently experienced strong electoral success and have strengthened their positions within the European Parliament. While their Eurosceptic positions are well documented in the literature, the fact that most RRPs refer not only to their nations but to Europe in general in order to ground their nationalist visions remains understudied. We investigate this issue by analyzing the discourses of MEPs from 24 radical right parties in the 8 th legislature of the European Parliament (2014–2019). Relying on a vast corpus (36,413 speeches) and using quantitative text analysis, this research sheds light on the various notions of Europe that are used by radical right MEPs. We find evidence of three visions of Europe: as a civilization; as an ethno-religious community; and as a liberal society. The use and preferences for these visions vary according to ideological positions, strategies and national contexts.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".