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Record W6965241461 · doi:10.3138/9781487512125

The Order of Canada: Genesis of an Honours System, Second Edition

2023· article· en· W6965241461 on OpenAlexaboutno aff

Bibliographic record

VenueProject Muse (Johns Hopkins University) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsTributeHonourOrder (exchange)Product (mathematics)Service (business)

Abstract

fetched live from OpenAlex

In 1966, a project to create a national honour for Canadians was begun. The order recognizes individuals for their outstanding achievements, dedication, and service to the country. It is a product of national identity, politics, and history, and includes such individuals as Atom Egoyan, Joseph Boyden, and Louise Arbour. The second edition of The Order of Canada continues the celebration of the order. Christopher McCreery sheds new light on the development of Canadian honours in the early 1930s, the imposed prohibition on honours from 1946 to 1967, and new details on those who have been removed or resigned from the Order. Extensively illustrated, The Order of Canada pays tribute to the individuals who felt the need for a system of recognition for Canadians. Indeed, the order’s history is as fascinating as the more than four thousand Canadians who have received it

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)0.003
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: none
Teacher disagreement score0.138
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0190.013
Scholarly communication0.0130.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.012
GPT teacher head0.199
Teacher spread0.187 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

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