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Record W1592504197 · doi:10.29173/cons8052

‘We at least had our Ancient Trees’: The Development of Myth and Identity in Nineteenth Century American Painting

2010· article· en· W1592504197 on OpenAlexvenueno aff
Justin J. Morris

Bibliographic record

VenueConstellations · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPridePaintingIdentity (music)MythologyArticulation (sociology)FellNational identityHistoryArt historyArtSociologyAestheticsLawPolitical scienceClassicsGeographyPoliticsCartography

Abstract

fetched live from OpenAlex

Modern history has looked on the United States of America as a country with a very distinct and proud national heritage and identity, though this was not always so. When founded in 1776, America was a nation that had not yet developed the identity and customs that would soon come to define the country nationally and internationally. The articulation of this distinct identity fell to the artist class and, in particular, first and second generation American painters. Painters such as Thomas Eakins, Thomas Cole, and the Hudson River School of artists pulled from their natural surroundings to create art that would foster pride in the values of peace, liberty, and freedom. Without these early painters, the United States would not have the strong identity that is so well known 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 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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.024
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.024
GPT teacher head0.251
Teacher spread0.227 · 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 designQualitative
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
Published2010
Admission routes1
Has abstractyes

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