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Record W2753764120

How Nicolas Sarkozy Shrank Jean-Marie Le Pen’s Electorate

2007· article· fr· W2753764120 on OpenAlexaboutno aff
Nonna Mayer

Bibliographic record

VenueRevue française de science politique · 2007
Typearticle
Languagefr
FieldSocial Sciences
TopicCommunism, Protests, Social Movements
Canadian institutionsnot available
Fundersnot available
KeywordsAuthoritarianismPresidential systemQuarter (Canadian coin)PoliticsEthnocentrismPresidential campaignPolitical scienceEconomic historyPresidential electionArtPolitical economySociologyHistoryLawDemocracy
DOInot available

Abstract

fetched live from OpenAlex

Between the first round of the 2002 and the 2007 French presidential election, Jean-Marie Le Pen lost 6 percentage points and a million voters. The French Electoral Panel (2007) shows that these voters still stand out by their rightist tropism, their ethnocentric-authoritarian attitudes. But over a quarter of the 2002 Le Pen voters turned to Nicolas Sarkozy in 2007, because he appeared to have a presidential stature and far more chances to be elected. The FN lost more support among the self employed and office and sales clerks than among blue collars which form today almost half his constituency. Its decline shows that the progression of extreme right parties is not inescapable, and that the supply side of politics is decisive.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.099
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0090.004
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.005

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.

Opus teacher head0.026
GPT teacher head0.309
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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