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Record W154197953

Melvin Charney : Tracking Images = Melvin Charney : Un dictionnaire...

2000· book· fr· W154197953 on OpenAlexaboutno aff
Melvin Charney, Jean-François Chevrier, Manon Régimbald, Phyllis Lambert

Bibliographic record

VenueE-Artexte (Artexte) · 2000
Typebook
Languagefr
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectureExhibitionNewspaperArt historyContext (archaeology)Interpretation (philosophy)ArtCriticismUrbanismHistoryVisual artsLiteratureSociologyMedia studiesArchaeologyPhilosophyLinguistics
DOInot available

Abstract

fetched live from OpenAlex

This publication documents Charney’s work as Canada’s representative for the 7th Venice Biennale International Architecture Exhibition. Chevrier explains the practice of the artist who, since 1970 and in the context of an investigation of “monumentality in the media age,” has collected newspaper articles and photographs of urban architecture and experiences. The author situates the project as a junction of the history of the criticism of architecture and the critique of urbanism. Charney’s text describes his Dictionnaire comprised of 232 plates, which he has organized into nine categories (Events, The structure of events, The structure of structures, Meta-events, Fragmentation, Exclusion and effacement, Reclamation, Affirmation, Out on the edge) according to “what they expose about the interaction between people and the constructed world.” Regimbald discusses various site-specific works produced in parallel with this project since 1974, and suggests an interpretation of Charney’s art as a double process of destruction of the “aura” and the production of “traces.” Texts in English, French and Italian. Biographical notes. Bibliography 1 p.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.774
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0220.018

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 head0.016
GPT teacher head0.223
Teacher spread0.206 · 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; both teacher heads agree on what is shown here.

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
Published2000
Admission routes1
Has abstractyes

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