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Record W4382279062 · doi:10.1515/9780773552708

Quebec

2017· book· en· W4382279062 on OpenAlexaboutno aff
Clarence Epstein

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2017
Typebook
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

The 2017 painting Quebec by Adam Miller represents over four hundred years of Quebec history. Featuring recognizable Quebec and Canadian politicians, ordinary characters, and allegorical figures, this unusual work visualizes many of the debates surrounding the 150th anniversary of Canadian Confederation as well as the 375th anniversary Montreal's founding. Bringing together a collection of commentaries on the painting and its artist, this volume contemplates the Quebec and Canadian experience and the bonds that link art and history. Included within are a reproduction of the painting, assorted detail shots, a key to the figures represented, and preparatory drawings used for the final work. Furthermore, essays by art historians François-Marc Gagnon, Donald Kuspit, and Alexandre Turgeon reflect on the painting and its style, as well as on its representation of history in relation to questions of politics, art, and collective memory. The book also contains an interview with Adam Miller conducted by Clarence Epstein, which reveals the sources of inspiration for the piece and the artist's creative process. A preface by the patron who commissioned the painting, Salvatore Guerrera, rounds out the contributions. Adam Miller is a painter known for his polished neo-classical figurative style that dramatizes historical subject matter and themes of social justice. He lives in New York.

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 score0.297
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2970.033

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 head0.254
Teacher spread0.230 · 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
Published2017
Admission routes1
Has abstractyes

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