MétaCan
Menu
Back to cohort
Record W1599924783 · doi:10.7202/1015183ar

Quand les documentaristes de l’ONF « fictionnalisent » les potentialités télévisuelles

2013· article· fr· W1599924783 on OpenAlexaffvenueabout
Gwenn Scheppler

Bibliographic record

VenueCinémas Revue d études cinématographiques · 2013
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

En 1953, l’ONF inaugure ses deux premières séries documentaires spécialement conçues pour la télévision de Radio-Canada :Sur le vif/On the SpotetRegards sur le Canada/Window on Canada. Ces deux séries hebdomadaires, qui vont garder l’antenne jusqu’en 1956 pour la première et 1955 pour la seconde, vont connaître un accueil mitigé de la part du public, en particulierRegards sur le Canada. Chacune de ces séries est différente dans son principe, même si les artisans de l’une sont souvent ceux de l’autre (notamment Bernard Devlin). Alors queSur le viffonctionne à la manière d’un reportage divertissant simulant le direct télévisuel,Regards sur le Canadafonctionne plutôt à la manière d’un ciné-club éducatif, où un présentateur-conférencier fait jouer d’anciens films qu’il commente ensuite avec des invités sur un plateau de télévision. Le dispositif de ces deux séries est donc significatif, d’un point de vue historique tout autant qu’esthétique : ils marquent, chacun à sa façon, une transition entre le cinéma et la télévision, une phase d’adaptation et d’expérimentation que l’auteur documente et analyse.

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: Empirical · Consensus signal: none
Teacher disagreement score0.194
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0100.011
Scholarly communication0.0120.006
Open science0.0010.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0320.005

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 head0.235
GPT teacher head0.307
Teacher spread0.072 · 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
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueCinémas Revue d études cinématographiquesSame topicCultural Insights and Digital ImpactsFrench-language works237,207