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Record W3124844187 · doi:10.7202/1072852ar

Philanthropy and Propaganda: The Bust of George III in Montréal

2020· article· fr· W3124844187 on OpenAlexaffvenueabout
Joan Coutu

Bibliographic record

VenueRACAR Revue d art canadienne · 2020
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsSocial Sciences and Humanities Research CouncilUniversity of Victoria
Fundersnot available
KeywordsArtHumanitiesBustGeorge (robot)Art historyEngineering

Abstract

fetched live from OpenAlex

En 1765, deux ans seulement après l’instauration du régime civil britannique, un incendie rasait presque entièrement le quartier des affaires ainsi qu’une grande partie de la ville de Montréal. Quand on apprit la nouvelle à Londres, un certain Jonas Hanway, commerçant et philanthrope, organisa une souscription pour venir en aide à la ville sinistrée. Il envoya à Montréal deux voitures de pompiers, la somme de 8,415 livres sterling et un buste de Georges III. Le buste sculpté par Joseph Wilton, « Sculptor to the King », fut érigé sur la Place d’Armes en souvenir de la générosité britannique. Cet article explique pourquoi Hanway, un homme qui n’aurait jamais visité le Canada, ni aucune autre colonie britannique, ressentait le besoin de souligner la générosité britannique en érigeant un monument au roi. Cette étude examine, en outre, les relations entre Hanway et le groupe de marchands anglais établis à Montréal et ennemis jurés du lieutenant-général, James Murray. Reste à savoir si le buste fut envoyé à Montréal pour l’unique bénéfice des Canadiens comme Hanway le laissait entendre ou bien si la sculpture ne devait pas plutôt servir à rassurer les marchands de Montréal quant à leurs droits sous le lieutenant-gouverneur?

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.551

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.010
Scholarly communication0.0050.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.000

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 head0.167
Teacher spread0.151 · 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
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
Published2020
Admission routes3
Has abstractyes

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