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Record W4409745981 · doi:10.1080/03086534.2025.2483833

Anthropology and Settler Nationalisms in the Art of Emily Carr, Irma Stern, and Margaret Preston

2025· article· en· W4409745981 on OpenAlexaffabout
Martin Crevier

Bibliographic record

VenueThe Journal of Imperial & Commonwealth History · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsCarrSternArt historyArtHistoryAnthropologySociologyAncient historyEcology

Abstract

fetched live from OpenAlex

South African Irma Stern (1894–1966), Canadian Emily Carr (1871–1945), and Australian Margaret Preston (1875–1963) all attained iconic status as artists in their respective countries. Early appraisers commended their incorporation of Indigenous and Black peoples in a national modernist canon through the use of post-impressionistic sensibilities. Despite notable similarities in biography, vision and oeuvre, these three artists have yet to be considered together in a comparative and connected mode. This article links their careers, ideas and concomitant emergence by focusing on their common and concurrent engagement with the science of Anthropology. All three absorbed and shared anthropologically-inflected conceptions of the ‘Other’. By distilling Anthropology’s discourses for popular audiences, they served as transmission belts between science and the public. They spread theories of racial typologies, of degeneration, of culture and of Indigenous disappearance. Modern art, via Anthropology, thus served as an interface through which Indigenous populations were appropriated and incorporated within nationalisms across Britain’s empire of settlement.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.020
GPT teacher head0.258
Teacher spread0.238 · 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 designNot applicable
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
Published2025
Admission routes2
Has abstractyes

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