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Record W2110249958 · doi:10.7202/007955ar

Du simple au multiple : le cinéma comme série de séries

2004· article· fr· W2110249958 on OpenAlexaffvenue
André Gaudreault

Bibliographic record

VenueCinémas Revue d études cinématographiques · 2004
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

L’idée de série est au coeur de la problématique de la prise de vues cinématographiques, puisque les « vues animées » sont constituées d’une série de photogrammes (obtenus grâce au procédé du tournage) et que les films sont constitués d’une série de plans (obtenus grâce à la procédure du montage). C’est même par un constant passage dialectique, de l’un au multiple puis du multiple à l’un, que la cinématographie aurait réussi à se développer comme dispositif. Cet article cherche les racines de ce phénomène jusque dans la constitution de la photographie et de la chronophotographie. On y explique comment le passage de la photographie à la chronophotographie est un saut d’ordre quantitatif (production de photographies en plus grand nombre), alors que le passage de cette dernière à la cinématographie relèverait plutôt d’un saut d’ordre qualitatif (plusieurs images fixes qui donnent naissance à une seule image animée). En cinématographie, le dispositif mis en branle permettrait ainsi d’accéder à un seuil d’un autre degré, à un autre ordre de représentation.

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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0080.010
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0270.002

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 head0.035
GPT teacher head0.235
Teacher spread0.199 · 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
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

Citations3
Published2004
Admission routes2
Has abstractyes

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