Ombres et lumières sur les élections européennes des 7 et 10 juin 1979 : ébauche d’une première analyse des résultats
Bibliographic record
Abstract
This article seeks to provide a first attempt at finding a way through the intricate jungle created by at least nine political Systems electing members for one Parliament. The analysis is divided into four steps. The first step considers the actors and the rules of the game and results in a clear conclusion : neither the rules (the electoral Systems) nor the actors (European political parties) allow for the expression of any kind of political will. The second step of the analysis deals with some generalizations about the so-called European trends of the election. The "nonvoters' party" appears as the clear winner. Moreover, this is the only common pattern observed in the nine countries. The third step is comprised of a country by country overview. Rather than referring to the European election, one should talk about at least elevent different elections each with a different set of issues. In terms of the issues, Denmark is the sole country where essentially European matters were in the forefront. In the other cases, the election of the MEP resembles an opinion poll designed especially to meet the needs of national leaders and parties. The article concludes by considering future developments. The real European elections will take place in 1984. What will happen from June 1979 until 1984 will be akin to rehersals for a play. The script seems well written and the dialogue is interesting. However, the actors (the parties) are untrained. The destiny of the performance will entirely depend on the actors.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".