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Record W4395071477 · doi:10.3917/fp.045.0197

Rodéo

2024· article· fr· W4395071477 on OpenAlexaff
Lola Quivoron, Antonia Buresi, Vannina Micheli-Rechtman

Bibliographic record

VenueFigures de la psychanalyse · 2024
Typearticle
Languagefr
FieldDecision Sciences
TopicDiverse academic research themes
Canadian institutionsEspace pour la vie
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

Cet entretien avec la réalisatrice Lola Quivoron et l’actrice et co-scénariste Antonia Buresi s’inscrit dans mon projet de faire dialoguer des personnalités du monde de la culture et de l’art avec des psychanalystes, afin de montrer la créativité et la modernité de la psychanalyse, toujours à l’écoute des mouvements contemporains. Lola Quivoron a réalisé Rodéo , son premier long métrage, avec l’actrice et co-scénariste Antonia Buresi. Il est sorti en salle en 2022, puis en dvd et sur les plates-formes en 2023. Il a concouru dans la sélection « Un certain regard » au Festival de Cannes en 2022. Ce film aborde les thèmes du cross-bitume, des banlieues, mais aussi du masculin, du féminin et du genre : « Julia vit de petites combines et voue une passion dévorante, presque animale, à la pratique de la moto. Un jour d’été, elle fait la rencontre d’une bande de motards adeptes du cross-bitume et infiltre ce milieu clandestin, constitué majoritairement de jeunes hommes. Avant qu’un accident ne fragilise sa position au sein de la bande… » Les questions soulevées par ce film sont abordées avec beaucoup de modernité et de créativité et cet entretien met en lumière la finesse des personnages et du processus de réalisation et d’écriture.

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)0.003
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.612
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0080.004
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.6120.345

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 head0.124
GPT teacher head0.500
Teacher spread0.376 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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