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Record W2550155018 · doi:10.1093/ajlh/njw013

The Making of European Law: Exploring the Life and Work of Michel Gaudet

2016· article· en· W2550155018 on OpenAlexaff
Morten Rasmussen

Bibliographic record

VenueAmerican Journal of Legal History · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicFrench Historical and Cultural Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIdeologyLawPoliticsSociologyOrder (exchange)European Union lawLegal professionEuropean unionLegal cultureLegal realismPolitical science

Abstract

fetched live from OpenAlex

This article studies the emergence of European law by exploring the life and career of Michel Gaudet, a French jurist who, behind the scene and out of the political spotlight, played a central role in fostering the European legal order in the 1950s and 1960s. As director at the legal service of the European Communities executives, Gaudet significantly contributed to the legal revolution that quasi-constitutionalized the European Treaties in the mid-1960s. Yet, he remains one of the least known figures of the early history of the European integration. Relying on his rich personal archives and on interviews with members of his family, this article investigates his personal and professional life experiences, with the aim of understanding how these experiences shaped his ideas, and influenced his thinking and actions in the legal field. This allows us to better understand the background and ideological outlook of one of the most influential figures behind the making of the European legal order, and consequently the intellectual roots of this legal transformation of Europe. It also affords us a unique glimpse into the social and intellectual world of the first generation of civil servants who shaped the new European institutions in the 1950s and 1960s.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.050
GPT teacher head0.200
Teacher spread0.150 · 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.

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

Citations7
Published2016
Admission routes1
Has abstractyes

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