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Record W6986475888

Pop Photographica: Photographâs Objects in Everyday Life 1842â1969

2003· article· en· W6986475888 on OpenAlexvenueaboutno aff

Bibliographic record

VenueArchivaria · 2003
Typearticle
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsnot available
Fundersnot available
KeywordsPhotographyEveryday lifeObject (grammar)Frame (networking)
DOInot available

Abstract

fetched live from OpenAlex

The most eye-catching piece in Pop Photographica: Photograph's Objects in Everyday Life 1842-1969 is a photograph of a young couple on their wedding day, framed with snazzy gold paper and trimmed with bright paper decoupage.What makes this object stand out is that the photograph is not in a picture frame or in an album: it rests inside a glass bottle.The exhibit "Pop Photographica," curated by Daile Kaplan, has brought this and other unusual photographic objects together at the Art Gallery of Ontario."Everyday" photographs, those taken by non-professionals often only for intimate purposes and destinations such as the family album, seem to be attracting renewed attention in the eyes of some academics, artists, and hobbyists.1 Frequently, this type of photography is called "vernacular photography," recognizing that it is a genre of photography likely never intended for public display or academic analysis -almost like a language or dialect shared among a smaller community of speakers.Kaplan, a former photographer, is also an author, auctioneer, curator, and Vice President and Director of Photographs at Swann Galleries auction house in New York.A self-described champion of vernacular photography, Kaplan has coined the term "pop photographica" as a catch-all phrase she uses to describe "the convergence of photography and popular culture." 2

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)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.043
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.003
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0330.004

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 head0.028
GPT teacher head0.232
Teacher spread0.204 · 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
Published2003
Admission routes2
Has abstractyes

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