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Record W2989843484 · doi:10.32316/hse-rhe.v31i2.4663

Historical Pageantry and Progressive Pedagogy at Canada’s 1927 Diamond Jubilee Celebration

2019· article· en· W2989843484 on OpenAlexaffvenueabout
James Miles

Bibliographic record

VenueHistorical Studies in Education / Revue d histoire de l éducation · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNarrativeIndigenousIdentity (music)HistoryGovernment (linguistics)Political scienceGender studiesMedia studiesSociologyArtLiteratureAesthetics

Abstract

fetched live from OpenAlex

Historians have argued that Canada’s Diamond Jubilee of Confederation in 1927 represents one of the federal government’s most sustained and successful attempts at nation building in the interwar period. In this mass outpouring of patriotic celebration, schools in particular played an important role in producing commemorative events, but also in constructing an engaging and accessible historical narrative for public consumption. At the heart of these events was the staging of hundreds of historical pageants, including many performances produced by teachers and students. This article examines how progressive pedagogies, such as active and play-based learning, came to be aligned with nation-building initiatives in widely produced historical pageants. Furthermore, it examines two published historical pageant scripts performed in Ontario’s schools to reveal the dominant themes of the historical narratives being promoted in relation to Indigenous-settler relations, gender, and national identity.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.386

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0290.020
Scholarly communication0.0060.001
Open science0.0010.003
Research integrity0.0010.002
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 head0.038
GPT teacher head0.310
Teacher spread0.272 · 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

Citations1
Published2019
Admission routes3
Has abstractyes

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