MétaCan
Menu
Back to cohort

I Sing

2025· book-chapter· en· W4415457243 on OpenAlexaboutno aff
Michel Legrand, Stéphane Lerouge

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLiterary Analysis and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)LyricsSisterGloomSet (abstract data type)

Abstract

fetched live from OpenAlex

Abstract In 1964, at the start of his rise as a film composer, Legrand decides he would like to try singing. He used to sing as a child with his sister Christiane, who went on to become a famous soprano. He writes the music for the songs, and the lyrics are penned by Eddy Marnay, an “enigmatic character” who “never sleeps, merely dozes.” Legrand admits that singing, for him, is a source of glorious, self-indulgent pleasure; he particularly loves scat. His first vocal album is a commercial failure, but his record company encourages him to try again. In 1965, Jacques Brel asks Legrand to sing the opening set of his concert in Montreal. Legrand agrees, and Brel teaches him about the art of performance: body language, lighting, and so on. On the night of the concert, Legrand is gripped by stage fright but makes it through. In 1971, he is asked to write music for a film adapted from a Françoise Sagan novel: at a dinner party in her apartment, he plays the theme he has written to Sagan, who is immediately inspired to write lyrics for it: their only 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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.784
Threshold uncertainty score0.953

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0480.000

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 head0.034
GPT teacher head0.198
Teacher spread0.165 · 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 designNot applicable
Domainnot available
GenreOther

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

Explore more

Same topicLiterary Analysis and Cultural StudiesFrench-language works237,207