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Organisation et financement des concerts dispensés par les musiciens et formations allemands en France sous l’Occupation 1940-1944

2025· dissertation· W7152501116 on OpenAlexaboutno aff
Jean-Christophe Esnault

Bibliographic record

Venuenot available
Typedissertation
Language
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFirst world warFantasyQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

La victoire allemande en France, l’Armistice et l’Occupation qui s’installe créent l’occasion pour les vainqueurs de montrer la supériorité de la culture allemande sur la française ; la musique savante et les grands musiciens de langue allemande vont être l’un des outils de cette démonstration. De plus, la bonne réceptivité des premiers concerts ouverts au public parisien en décembre 1940 encourage l’occupant à la mise en place, dans le cadre d’une propagande culturelle, de nombreuses manifestations musicales à Paris et en province.Dans le contente de ce travail, se poseront deux questions essentielles. Nous nous demanderons tout d’abord comment s’organisent ces manifestations, qui décide de faire venir les musiciens en France, de leur rémunération, des frais de voyages, quels sont les différents organismes organisateurs de ces manifestations et qui prend en charge le financement. Puis nous nous interrogerons sur la rentabilité des concerts. Quelle est-elle : financière, politique ? Se pose ici la question de ce que l’occupant cherchait à atteindre. Car, outre ce besoin d’affirmer la suprématie de la musique allemande, les efforts déployés par le Reich, sous couvert de divertissement, ont-ils été suffisant pour séduire le peuple français, l’asservir pour mieux l’entrainer sur la voie de la Collaboration ?

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.510

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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.

Opus teacher head0.028
GPT teacher head0.270
Teacher spread0.242 · 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
Published2025
Admission routes1
Has abstractyes

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