Bibliographic record
Abstract
The first-round results of the 2002 French presidential election came as a shock to both French voters and people around the world. The French presidential election is a two-round system: it takes an absolute majority of the vote to be elected in the first round and, whenever no candidate is elected in the first round, a second round opposes the top two candidates of the first round two weeks later. In the months preceding the election, polls asked about not only voter intentions for the first round but also voter intentions for the second round, offering a choice between Jacques Chirac, the incumbent president, RPR (Rally for the Republic, right) and Lionel Jospin, incumbent prime minister, PS (Socialist Party), the obvious candidates for the second round. What happened on the first-round election day was not forecast by the polls: contrary to predictions, Jean-Marie Le Pen, FN (National Front, an extreme right-wing party), finished second with 16.9 percent of the vote and moved on to the second round. The newspaper Le Monde (2003) stated, “France is hurt, and many French people are humiliated.”
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 | 0.024 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".