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Record W2891768200 · doi:10.7202/1050636ar

‘No Sense of Reality’

2018· article· en· W2891768200 on OpenAlexvenueaboutno aff
Kirk Niergarth

Bibliographic record

VenueOntario History · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsWitnessTolerationCommunismGovernment (linguistics)George (robot)LawPolitical scienceSociologyEconomic historyHistoryArt historyPhilosophy

Abstract

fetched live from OpenAlex

In 1936 George Drew, future Premier of Ontario, was greatly concerned that a false and very dangerous impression of the Russian experiment in government was being spread in Ontario. So he traveled to Russia in 1937 where he confirmed his preconceived ideas with first-hand observation. For him, toleration of domestic communism could lead either to the horrors of Stalin’s USSR or to the fascism of Hitler or Mussolini. Canada’s best option, he felt, was to follow Britain in ending partisan politics and establishing a “National Government.” Thus, in the 1930s, he worked, unsuccessfully, to create coalition governments in Toronto and Ottawa. This article concludes that the lens through which Drew viewed the USSR can be reversed to gain insight into the Canadian political culture of which he was a part. The right-wing solutions that Drew advocated were conveyed to the public through international comparison and analogy based on Drew’s eye-witness account of his European tour.

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)0.011
metaresearch head score (Gemma)0.016
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 score0.842
Threshold uncertainty score0.314

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0170.099
Scholarly communication0.0160.020
Open science0.0030.008
Research integrity0.0050.012
Insufficient payload (model declined to judge)0.0070.002

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 head0.027
GPT teacher head0.231
Teacher spread0.203 · 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
Published2018
Admission routes2
Has abstractyes

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