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Record W7026784533

Anti-Americanism in Canada

2022· report· en· W7026784533 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Research (Auckland University of Technology) · 2022
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsState (computer science)Government (linguistics)Agency (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this paper is to examine Granatstein’s arguments (who suggested that the kind of anti-Americanism one finds in Canada is in fact unique) in light of the developments since 1996, when he was writing. It begins by exploring the nature of anti-Americanism in Canada to confirm Granatstein’s contention that Canadian anti-Americanism is unique. I then look at the state of contemporary anti-Americanism in Canada—in the late 1990s and early 2000s. I will argue that Granatstein was correct to suggest that the kind of unique anti-Americanism that had marked Canadian political culture for much of the nineteenth century and all but the last decade of the twentieth century had largely disappeared. However, he was overly optimistic about the decline of this phenomenon. I will show that anti-Americanism is alive and well in Canada, but it is a particular and quite limited strand of anti-Americanism.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.093
Threshold uncertainty score0.678

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0200.008
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.108
GPT teacher head0.358
Teacher spread0.250 · 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 designQualitative
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

Citations3
Published2022
Admission routes1
Has abstractyes

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