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Record W2014338774 · doi:10.1080/0046760x.2013.844279

Political partisanship, bureaucratic pragmatism and Acadian nationalism: New Brunswick, Canada’s 1920 history textbook controversy

2014· article· en· W2014338774 on OpenAlexaffabout
Frances Helyar

Bibliographic record

VenueHistory of Education · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsLakehead University
Fundersnot available
KeywordsPatriotismNationalismPoliticsBureaucracyCitizenshipSociologySpanish Civil WarNewspaperGender studiesPolitical scienceLaw

Abstract

fetched live from OpenAlex

During a time of post-war sensitivity to Canadian nationalism and patriotism, public feeling was aroused in 1920 New Brunswick regarding a world history textbook with a new chapter about the First World War. The American author made no reference to Canada’s war efforts. The subsequent public discussion focused on issues of patriotism, citizenship, history education and schooling, but it eventually dissolved into longstanding conflicts over language and religion. This case study investigates how questions about history education were interpreted through the lens of the political partisanship of the newspaper editor, the bureaucratic rationality of the educational administrator, and the Acadian nationalism of the Roman Catholic Bishop. The controversy depicts a loosening but not breaking of postcolonial ties, and uncovers the political nature of public memory, along with the complex intertwining of religion and language rights within schooling, history education and citizenship in post-war Canada and New Brunswick.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.872

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0450.022
Scholarly communication0.0130.002
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.000

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 head0.057
GPT teacher head0.317
Teacher spread0.260 · 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.

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
Published2014
Admission routes2
Has abstractyes

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