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Record W4384830813 · doi:10.31664/zu.2022.111.08

Constructing Visibility: Esther Born’s Photography beyond the Archives

2023· article· en· W4384830813 on OpenAlexaboutno aff
Derrick R. Cartwright

Bibliographic record

VenueŽivot umjetnosti · 2023
Typearticle
Languageen
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsnot available
Fundersnot available
KeywordsWrightPortraitArchitectureArt historyFlourishingPhotographyHistoryVisual artsArtPsychology

Abstract

fetched live from OpenAlex

Esther Baum Born was an American photographer who worked in both the United States and Mexico. Beginning in the 1920s, she exhibited her work regularly in New York galleries and saw her photographs published in a broad spectrum of architectural journals. Born’s book, The New Architecture in Mexico (1937), stands as an undisputed monument to her creative insights and a respected source for cutting-edge ideas about modern building. Less well known to the scholarly community are the sensitive portraits that Born took of her own artistic milieu: Frida Kahlo, Diego Rivera, and Frank Lloyd Wright, to name only a few, appeared before her camera. The author argues that these images represent an area for future research. In any event, Born’s creative flourishing was largely eclipsed once she joined the highly successful architectural practice of her husband, Ernest Born. She gave up photography entirely in the 1940s to support his work. The legacy of both Borns remains fairly well-known to students of Bay Area architecture, who have admired their contributions to public transportation (designing train stations), urban renewal (developing master planning documents), and book design (such as the Plan of St. Gall, co-authored with art historian, Walter Horn). Much of the couple’s joint career is documented in established archives throughout the United States and Canada, although it needs to be said that Ernest Born is typically given top billing for the work. Esther Born’s early efforts as a photographer sit in these archives, too. A full assessment of her legacy as a photographer waits to be written. This paper attempts to give greater visibility to her ambitions as well as to the lasting consequence of her work’s placement within the many archival situations where it can be found today.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.224
Teacher spread0.209 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2023
Admission routes1
Has abstractyes

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