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Record W765501899 · doi:10.29173/css217

History by the Minute: A Representative National History or a Common Sense of the Majority?

2008· article· en· W765501899 on OpenAlexvenueaboutno aff
Michael K. Barbour, Mark Evans

Bibliographic record

VenueCanadian Social Studies · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCommon senseScrutinySocial studiesNational historyMulticulturalismNational curriculumCurriculumSociologyCultural pluralismNational heritageCultural heritageSocial scienceHistoryLawPolitical sciencePedagogyAnthropology

Abstract

fetched live from OpenAlex

A number of times over the past century, there have been struggles in the United States over what is and is not included in the history curriculum. These struggles have primarily been over who is represented in the teaching of history. In Canada, however, this debate has not been as prevalent. For example, Historicas Heritage Minutes is a national project that is designed to present Canadians with a common sense of national history and in the eight years since it was first introduced it has not received similar scrutiny. In this article, we use an emergent coding scheme to examine this project to investigate exactly whose history is being told and whether or not it is representative of Canadian society. We feel that while the Heritage Minutes are sometimes over representative of the dominant cultural traits in Canadian society, they do present a multicultural view of 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)0.008
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.330

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0070.019
Scholarly communication0.0080.011
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.358
GPT teacher head0.407
Teacher spread0.049 · 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 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

Citations2
Published2008
Admission routes2
Has abstractyes

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