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Record W2884794045 · doi:10.3138/cjfs.26.2.2017-0006

“It’s Over”: Reflexivity in Don McKellar’s <i>Last Night</i>

2017· article· fr· W2884794045 on OpenAlexaffvenueabout
Allan Weiss, Nicole Black

Bibliographic record

VenueCanadian Journal of Film Studies · 2017
Typearticle
Languagefr
FieldArts and Humanities
TopicContemporary Literature and Criticism
Canadian institutionsYork University
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Résumé : Le film Last Night (Minuit) du cinéaste canadien Don McKellar est une œuvre de science fiction apocalyptique dont la création répond à un afflux de films-catastrophes hollywoodiens à grand déploiement comme Independence Day (Le jour de l’indépendance). McKellar n’explique jamais le pourquoi ou le comment de la disparition du monde ; il s’intéresse plutôt à la façon dont les gens font face à la situation dans le quotidien, à leur propre manière, en se livrant à leurs rituels personnels dans l’appréhension d’un anéantissement imminent. En se concentrant sur l’individuel et le contingent, et en rejetant toute forme de grand récit apocalyptique, le film propose une apocalypse postmoderne. L’une des principales techniques postmodernes qui y sont employées est la réflexivité ; les références au caractère du film à titre de film sont omniprésentes dans Last Night, bien que les allusions soient relativement subtiles. Une étude attentive de la distribution, du dialogue et de l’imagerie du film révèle que ce avec quoi les personnages sont forcés de composer n’est pas une apocalypse naturelle, surnaturelle ou d’origine humaine, mais une apocalypse textuelle. En d’autres termes, l’unique issue certaine et définissable qui menace les personnages est celle de la fin du film lui-même.

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)0.003
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 score0.025
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.018
Scholarly communication0.0120.006
Open science0.0010.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0070.001

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 head0.080
GPT teacher head0.323
Teacher spread0.243 · 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
Published2017
Admission routes3
Has abstractyes

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