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Record W4399841361 · doi:10.1515/9781772127492

The Riel Problem

2024· book· en· W4399841361 on OpenAlexaboutno aff
Albert Braz

Bibliographic record

VenueUniversity of Alberta Press eBooks · 2024
Typebook
Languageen
FieldEngineering
TopicOptimization and Packing Problems
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Tracing Louis Riel’s metamorphosis from traitor to hero, Braz argues that, through his writing, Riel resists his portrayal as both a Canadian patriot and a pan-Indigenous leader. After being hanged for high treason in 1885, the Métis politician, poet, and mystic has emerged as a quintessential Canadian champion. The Riel Problem maps this representational shift by examining a series of cultural and scholarly commemorations of Riel since 1967, from a large-scale opera about his life, through the publication of his extant writings, to statues erected in his honour. Braz also probes how aspects of Riel’s life and writing can be problematic for many contemporary Métis artists, scholars, and civic leaders. Analyzing representations of Riel in light of his own writings, the author exposes both the constructedness of the Canadian nation-state and the magnitude of the current historical revisionism when dealing with Riel.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.014
Scholarly communication0.0080.008
Open science0.0020.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0250.009

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 head0.010
GPT teacher head0.165
Teacher spread0.156 · 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 designSimulation or modeling
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

Citations1
Published2024
Admission routes1
Has abstractyes

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