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Record W2315203496 · doi:10.3138/ecf.28.3.447

“Set the winter at defiance”: <i>Emily Montague</i>’s Weather Reports and Political Sensibility

2016· article· en· W2315203496 on OpenAlexvenueaboutno aff
Morgan Vanek

Bibliographic record

VenueEighteenth-Century Fiction · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSensibilityPoliticsCharacter (mathematics)AffectionHistoryLawSociologyPolitical sciencePsychologySocial psychology

Abstract

fetched live from OpenAlex

This article examines the political significance of the detailed descriptions of Canada’s very cold weather in Frances Brooke’s epistolary novel, The History of Emily Montague (1769). In 1769, public sphere debate about Canada was focused on the difficulty of displacing French Catholic loyalties among new British subjects. By using the same terms to describe the effects of the weather on her British protagonists and the effects of French Catholic influence on the new subjects these travellers hope to convert to British values, Brooke identifies French Catholic “coldness of character” as a serious threat to the British project to cultivate affection in these colonists. By the novel’s end, however, Brooke’s protagonists also model a willingness to enjoy the weather’s influence that aligns assimilating to British values with improvements in sensibility, rather than conflict. I conclude that tracking this change in Brooke’s characters’ writing about the weather casts new light on Emily Montague’s contribution to an important mid-century debate about how Britain would imagine and manage the increasingly diverse environments of its empire.

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 categoriesScience and technology studies, 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: Empirical
Teacher disagreement score0.321
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.208
Teacher spread0.192 · 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
Published2016
Admission routes2
Has abstractyes

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