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Record W2092504690 · doi:10.4000/ahrf.11200

Tronchet et la réorganisation constituante des institutions judiciaires

2007· article· fr· W2092504690 on OpenAlexaff
Philippe Tessier

Bibliographic record

VenueAnnales historiques de la Révolution française · 2007
Typearticle
Languagefr
FieldArts and Humanities
TopicEuropean Political History Analysis
Canadian institutionsInstitut d'Histoire de l'Amérique Française
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

François Denis Tronchet, connu pour sa participation au procès du roi et sa contribution à la rédaction du Code civil de 1804, joua un rôle important, pendant la Constituante, dans la réorganisation des institutions judiciaires d’Ancien Régime, et, notamment, dans la réforme de la procédure criminelle. Bien que très tôt qualifié de « Nestor de l’aristocratie », il apparaît à la fois comme attaché à certaines traditions et ardent promoteur de la réforme, aussi peut-il être qualifié d’homme de la transaction. En fait, Tronchet utilise l’expérience qu’il a acquise dans sa pratique du métier d’avocat pour élaborer des solutions pragmatiques, concrètes et humaines. Ces solutions de compromis sont souvent inspirées par un idéal de modération, de défense de l’équilibre et du refus de la « barbarie », ce concept repoussoir qui désigne à la fois l’Ancien Régime et certaines pratiques étrangères ; cet ensemble d’idées est étroitement associé au modèle de l’avocat, qu’il glorifie, tout en rejetant le corporatisme judiciaire.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.024
Scholarly communication0.0070.005
Open science0.0010.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0090.002

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.

Opus teacher head0.033
GPT teacher head0.284
Teacher spread0.251 · 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 designNot applicable
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

Citations1
Published2007
Admission routes1
Has abstractyes

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