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Record W4405640038 · doi:10.14324/herj.22.1.02

Researching history education in Canada: plus ça change?

2024· article· en· W4405640038 on OpenAlexaffabout
James Miles

Bibliographic record

VenueHistory Education Research Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

This article explores history education research in Canada by analysing three important studies conducted prior to 1970. The article considers how history education has shifted across these reports and what questions and problems remain stubbornly consistent and contemporary in history classrooms, despite regular interventions, reforms, papers, studies and curricular initiatives. The three research projects discussed in this article provide glimpses into how research on history education in Canada has been conducted, and what assumptions, questions and beliefs have driven it. In comparing these three studies, the article identifies important continuities and changes for Canadian history education researchers over time. In thinking across these three studies, the article also identifies and reflects on what paradigms of educational thought are present in each case, and how the socio-cultural-political context they were conducted in shaped the research. The article argues that each of these three studies reflects key debates in educational theory, including questions about progressive education and the civic and citizenship function of history education in society. The article also raises questions and issues for researchers interested in conducting national studies of history education in other national contexts with similarly decentralised education systems. Finally, the article addresses what might be learnt by current history education researchers doing similar work today.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.669
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.427
GPT teacher head0.508
Teacher spread0.081 · 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 teacher head, not a consensus.

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

Citations1
Published2024
Admission routes2
Has abstractyes

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