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Record W2475261035 · doi:10.7202/1036195ar

La tolérance des juges à la fraude fiscale : un inconscient d’institution

2016· article· fr· W2475261035 on OpenAlexvenueno aff
Alexis Spire, Katia Weidenfeld

Bibliographic record

VenueCriminologie · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Cette contribution vise à montrer que la régulation de la fraude fiscale par l’institution judiciaire traduit une tolérance, en partie inconsciente, des acteurs qui en sont chargés. Pour en analyser les mécanismes, on s’intéresse aux discours et aux pratiques des procureurs et des magistrats chargés d’assurer le suivi pénal des dossiers que leur transmet l’administration fiscale. Tous se disent convaincus de la nécessité de lutter contre cette forme de délinquance en col blanc, mais s’abstiennent d’utiliser tous les moyens dont ils disposent pour que la pénalisation de la fraude fiscale débouche sur des sanctions effectives. Il en découle une indulgence qui contraste avec la posture d’intransigeance adoptée par l’institution judiciaire dans d’autres domaines. Pour comprendre les ressorts de cette impunité fiscale, nous proposons une approche qui tient compte de la singularité de ce délit et du profil social de ceux qui le commettent, en considérant à la fois les contraintes institutionnelles qui s’imposent aux magistrats et les représentations qui les rendent acceptables.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.012
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.614
GPT teacher head0.502
Teacher spread0.112 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations10
Published2016
Admission routes1
Has abstractyes

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