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Record W4234555024 · doi:10.32920/ryerson.14665008

The colour of time: Stephen Shore’s American Surfaces 1972-2014

2021· preprint· en· W4234555024 on OpenAlexaff
Lisa Muzzin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsToronto Metropolitan University
FundersMinistry of Minority Affairs
KeywordsExhibitionPhotographyVisual artsArtNegativeVisual art of the United StatesMateriality (auditing)ShoreArt historyAestheticsPerformance artGeology

Abstract

fetched live from OpenAlex

In 1972 American photographer Stephen Shore (b. 1947) started the series of chromogenic colour photographs titled American Surfaces (1972-73). In the decades following the initial production of this work and its 1974 acquisition by the Metropolitan Museum of Art in New York, the material qualities and aesthetics of colour photography underwent dramatic changes. This thesis explores the relationship between developments in colour imaging technology and shifts in artistic production from the making of American Surfaces to the present, and explores the increased recognition now given to colour photography as art. In 2016, American Surfaces can be found in a variety of forms including: two publications, numerous recently created digital chromogenic colour exhibition prints, and the original 1972-73 prints at The Met. Focusing on the materiality of this culturally and historically significant body of colour photographic work, this thesis examines three different iterations of American Surfaces from initial production in 1972 to 2014 and their impact on the interpretation of the series.

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)0.002
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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.009
Scholarly communication0.0050.003
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.260
Teacher spread0.235 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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