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Record W4288385266 · doi:10.3138/chr.2021-0010

What Events in Canadian History Are Most Significant? A Survey of History Teachers

2022· article· en· W4288385266 on OpenAlexvenueaboutno aff
Lindsay Gibson, Catherine Duquette, Jacqueline P. Leighton

Bibliographic record

VenueCanadian Historical Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsQuantitative historyStatistical significanceSignificance testingHistoryIntellectual historySocial sciencePsychologySociologyPolitical historyPolitical scienceLawMedicineEconomic history

Abstract

fetched live from OpenAlex

Historical significance is one of the most fundamental and inescapable aspects of history and history education. History teachers make countless decisions about the historical significance of events in their daily practice, but little research has focused on the criteria that history teachers use to decide which events in Canadian history are historically significant, the events in Canadian history teachers rate as most historically significant, and the demographic factors that influence their historical significance ratings. This article focuses on the results of a survey in which English- and French-speaking teachers currently teaching Canadian history in a Canadian K–12 school, Collège d’enseignement general et professionnel (in Quebec), or college or university (n = 270) rated the historical significance of one hundred events in Canadian history, selected three factors that most influenced their ratings, and answered various demographic questions. The results suggest that teachers utilize historical and educational criteria to assess the historical significance of events, that their historical significance ratings were temporally and theoretically diverse, and that demographic factors have more influence on their historical significance ratings than the intellectual criteria they identified.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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: Review · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.191
GPT teacher head0.347
Teacher spread0.156 · 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
GenreReview

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

Citations5
Published2022
Admission routes2
Has abstractyes

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