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Record W4242203637 · doi:10.32920/ryerson.14654295

Discourse, difference, and dehumanization: justifying the Canadian Japanese internment, 1940-1949

2021· preprint· en· W4242203637 on OpenAlexaffabout
Alexandra Marcinkowski

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsCarleton UniversityToronto Metropolitan UniversityCentre for Social Innovation
Fundersnot available
KeywordsNarrativeWhite (mutation)ParliamentHouse of CommonsGender studiesNewspaperEthnic groupPower (physics)GlobePolitical scienceIdentity (music)Critical discourse analysisNegotiationSociologyReferentMedia studiesHistoryLawPoliticsPsychologyLiteratureAestheticsIdeology

Abstract

fetched live from OpenAlex

This thesis argues Canadian Members of Parliament used the December 7, 1941 attack on Pearl Harbour as an opportunity to enforce a dominant “us versus them” narrative in order to justify the internment of approximately 22,000 Canadians of Japanese ancestry. National and local newspapers reinforced this narrative through uncritical and biased reporting which negatively framed the Japanese against a more idealized and white “Canadian” identity. Critical discourse analysis was applied on several debates in the House of Commons and news articles in the Daily Colonist and the Globe and Mail between 1940 and 1949, to examine the articulation of social relations – in this case, race and ethnicity – with the goal of uncovering the power relations embedded within the discourse. The findings reveal a clear “us versus them” narrative, whereby Canadians of Japanese ancestry were constructed as “yellow,” “bad,” and “unwanted,” as opposed to white Canadians who were “good” and “loyal.”

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)0.006
metaresearch head score (Gemma)0.008
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.828

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0440.054
Scholarly communication0.0090.003
Open science0.0010.005
Research integrity0.0020.004
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 head0.030
GPT teacher head0.278
Teacher spread0.248 · 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
Published2021
Admission routes2
Has abstractyes

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