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Record W2935895264 · doi:10.1093/whq/whz007

<i>Citizens of Convenience: The Imperial Origins of American Nationhood on the U.S.-Canadian Border</i>. Early American Histories. By Lawrence B. A. Hatter

2019· article· en· W2935895264 on OpenAlexaboutno aff
Lucretia Grindle

Bibliographic record

VenueWestern Historical Quarterly · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipEmpireTreatyPower (physics)LawArgument (complex analysis)HistoryPolitical scienceEconomic historyPolitics

Abstract

fetched live from OpenAlex

Using the lens of the Montreal fur trade, Lawrence B.A. Hatter’s Citizens of Convenience examines the nature of the Canadian-American border from the Paris Treaty of 1783 through the War of 1812. Central to his argument is the idea that the evolution of the northern border, from a fluid zone of essentially free trade to the defined and hardened line of enforcement enunciated in the Treaty of Ghent in 1814–15, was essential to the formation of America’s identity, which Hatter defines as imperial. Acknowledging that “contemporary Americans might feel squeamish about calling the United States an empire,” Hatter reminds us that, “the Founders felt no such discomfort” (p. 9). This reminder is important, both because it is one of the strengths of Hatter’s work that he continually reasserts the realities and points of view of the eighteenth and early nineteenth centuries and because America’s conception of itself was formed, defined, and enacted along its borders, especially the northern border it now shared with its erstwhile ruling power, Great Britain. Here, the central concepts of any imperial, and indeed national, project played out—the control of territory, the control of movement of people and thus the definition of citizenship, and the regulation of trade.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.764
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.232
Teacher spread0.225 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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