Panel électoral français 2002 Vague 1
Bibliographic record
Abstract
A l'occasion des élections présidentielle et législatives de 2002, le Centre de recherches politiques de Sciences Po (CEVIPOF), le Centre d'informatisation des données socio-politiques (CIDSP) et le Centre d'études sur l'opinion publique (CECOP) ont uni leurs efforts, avec l'aide du Ministère de l'intérieur, de la Fondation nationale des sciences politiques (FNSP) et de l'université de Montréal, pour mettre en place une grande enquête électorale au dispositif unique et inédit en France. Le calendrier électoral de 2002 était particulièrement propice à une enquête en plusieurs vagues et par panel puisque quatre tours de scrutins ont eu lieu à l'occasion de deux élections décisives à quelques semaines d'intervalle. Ainsi, le Panel électoral français (PEF) s'est déroulé en trois vagues et 1417 électeurs constituent le panel. Non seulement cette enquête présente les avantages du panel, mais elle permet également une comparaison avec les précédentes enquêtes menées par le CEVIPOF après les élections présidentielles de 1988 et de 1995 et les élections législatives de 1978 et 1997. For the 2002 presidential and legislative elections,the Center of political researches of Sciences Po (CEVIPOF), the Center for the Computerisation of Socio-Political Data (CIDSP) and the Public Opinion Research Centre (CECOP) joined forces, with the help of the Ministry of the Interior, the Fondation Nationale des Sciences Politiques (FNSP) and the University of Montreal, to establish a large-scale electoral survey using an approach that was unique and entirely new in France. The 2002 electoral agenda was particularly conducive to a multi-wave, panel-based survey, since four rounds of voting took place in two decisive elections with only a few weeks between them. So the French Electoral Panel (PEF) was conducted in three waves with a panel made up of 1417 voters. The advantage of this survey lay not only in the use of the panel, but also in the fact that it allowed comparison with the previous surveys conducted by CEVIPOF after the presidential elections of 1988 and 1995, and the legislative elections of 1978 and 1997.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.085 | 0.020 |
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".