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Record W4399555913 · doi:10.1080/02722011.2024.2313919

“Join This Great Movement for the Release of Humanity from Oppression and Deceit”: Social Credit and Conspiratorial Thinking, 1945-1958

2024· article· en· W4399555913 on OpenAlexaffabout
Kevin Anderson

Bibliographic record

VenueThe American Review of Canadian Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOppressionHumanityJoin (topology)Movement (music)Political scienceSociologyInternet privacyLawComputer sciencePhilosophyAesthetics

Abstract

fetched live from OpenAlex

Social Credit was a constant presence in Canadian politics at the federal level from the mid-1930s until the late 1970s. Yet, the federal Social Credit Party has often been dismissed as the “lunatic fringe.” This article will contextualize the federal Social Credit Party as part of the political right in the early Cold War. By analyzing the statements of several Social Credit MPs, as well as text from the Canadian Social Crediter, this article seeks to better understand the nature of conspiratorial thinking within Social Credit and how it was interwoven into broader, more “mainstream,” postwar concerns, such as international Communism, the perceived decline of Britishness and Christianity, and the growing welfare state. The federal Social Credit Party pushed against the permeable barriers between “fringe” and “mainstream” by pairing conspiratorial thought with widespread concerns and operating within the center of political respectability in Canada.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.107
Threshold uncertainty score0.774

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0150.047
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.341
Teacher spread0.298 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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