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Record W2606343177 · doi:10.22501/jar.17834

Mapping a Modern Diegesis: Terre des Hommes and Robert Altman's Quintet

2013· article· en· W2606343177 on OpenAlexaboutno aff
Paul Landon

Bibliographic record

VenueJournal for Artistic Research · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsnot available
Fundersnot available
KeywordsSpectacleMeaning (existential)ArchitectureImpromptuRepresentation (politics)White (mutation)Space (punctuation)Art historySet (abstract data type)ArtAestheticsVisual artsHistoryComputer sciencePhilosophyEpistemologyLinguisticsPoliticsPolitical science

Abstract

fetched live from OpenAlex

This project maps the locations in the old Expo 67 site in Montréal used in the film Quintet (Robert Altman, 1979). It reflects upon how the representation of the international, modern architecture and design of the Expo pavilions could shift from signifying promise and potential for social betterment to becoming indexes of technological catastrophe and social decay. It also looks at how the architecture of Expo 67, both as a site of technological spectacle and as an impromptu film set, has disappeared. The interface for the project reflects the process of looking for something that has been forgotten. Like the characters of the film Quintet, lost in a nuclear winter landscape, the reader wanders through expanses of white space to find remnants of the expo site and of the film's set, to find artefacts and fragments of meaning. keywords:

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)0.001
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 score0.534
Threshold uncertainty score0.938

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.007
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.192
GPT teacher head0.390
Teacher spread0.198 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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