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Record W4291000919 · doi:10.1017/9781108682367

A Concise History of Canada

2022· book· en· W4291000919 on OpenAlexaffabout
Margaret Conrad

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsIndigenousCONQUESTHistoryImmigrationPopularityState (computer science)NarrativeReading (process)GenealogyPolitical scienceEthnologyLawAncient historyLiteratureArtArchaeology

Abstract

fetched live from OpenAlex

Margaret Conrad's history of Canada explains what makes up this diverse, complex, and often contested nation-state. Beginning in Canada's deep past with the arrival of its Indigenous peoples, she traces its history through the conquest by Europeans, the American Revolutionary War, and Confederation in the nineteenth century to its prosperous present. This impressive second edition has expanded by 20 percent, including revised chapters and an insightful analysis of the fraught relationship between Justin Trudeau and Donald Trump. As a social historian, Conrad emphasizes the relationships between Indigenous peoples and settlers, French and English, Catholic and Protestant, men and women, rich and poor. It is this grounded approach that drives the narrative and makes for compelling reading. Despite its successes and its popularity as a destination for immigrants from across the world, Canada remains a cautious and contested country. This thorough yet concise new edition explains why.

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 score0.064
Threshold uncertainty score0.466

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0130.002
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0620.013

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 head0.014
GPT teacher head0.167
Teacher spread0.153 · 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

Citations7
Published2022
Admission routes2
Has abstractyes

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