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Soul of a Nation

2022· book-chapter· en· W4391120952 on OpenAlexaboutno aff
Randall Balmer

Bibliographic record

VenueUniversity of North Carolina Press eBooks · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousGeorge (robot)CricketFrontierPolitical scienceSoulIce hockeyCriminologyHistoryMedia studiesGeographySociologyLawArt history

Abstract

fetched live from OpenAlex

Ice hockey, which evolved from lacrosse, has become Canada’s game. A dentist in Montréal, George Beers, argued at the time of Canada’s confederation in 1867 that Canada needed its own game; cricket, he argued was too British. Instead, Canada needed a rough-and-tumble game that reflected the wild Canadian landscape. He argued that lacrosse was that game, played initially by First Nations people but adopted by Canadians. Beers, a Presbyterian who believed that everything should be done “decently and in order,” codified rules for lacrosse and established boundaries for the field, thereby “domesticating” the Indigenous game. Although great controversy still surrounds the precise origins of ice hockey, it developed from lacrosse and continues to reflect the rugged, frontier-justice Canadian society.

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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.251
Threshold uncertainty score0.499

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.011
Scholarly communication0.0060.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.003

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 head0.047
GPT teacher head0.235
Teacher spread0.188 · 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
Published2022
Admission routes1
Has abstractyes

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