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Record W2017667722 · doi:10.7202/030515ar

“Non-Resident Me”: John Bartlet and the Canadian Historical Profession

2006· article· en· W2017667722 on OpenAlexvenueaboutno aff
Rohit T. Aggarwala

Bibliographic record

VenueJournal of the Canadian Historical Association · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsNationalismHistoriographyLegitimacyPoliticsHistoryLawPolitical scienceSociology

Abstract

fetched live from OpenAlex

John Bartlet Brebner (1895-1957) was a significant Canadian historian, but his work has been marginalised and discredited in the historiography. A Maritime historian, he continued to study Nova Scotia after leaving the University of Toronto for Columbia University, and this and his work on early explorers and British history led to his espousal of a continental approach that emphasised Canadian-American exchange and a shared British legal and political heritage. A deep liberal, he felt under suspicion because he did not promote either of the two nationalist schools of Canadian history and because he lived in the United States; this feeling moved him to naturalise as an American in 1941 and give up Canadian history. He later regretted this action, as his experiences as a liberal American in the post-war era gave him concerns about the liberal quality of American nationalism. After Brebner's death, his reputation was tarnished by the posthumous publication of an obsolete manuscript and the concerted attack of nationalist historians who, led by Donald G. Creighton, sought to deny legitimacy to even the most nuanced use of the "continental approach."

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)0.005
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score0.640

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0420.016
Scholarly communication0.0080.004
Open science0.0020.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Historical AssociationSame topicCanadian Identity and HistoryFrench-language works237,207