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Record W3006165518

Sentimental Canada: Literary analysis of The History of Emily Montague

2017· dissertation· en· W3006165518 on OpenAlexaboutno aff
Aneta Jerglová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHistory of literatureHistoryLiteratureArt historyArt
DOInot available

Abstract

fetched live from OpenAlex

THESIS ABSTRACT This thesis focuses primarily on The History of Emily Montague, a novel written in 1769 by Frances Brooke. The novel is remarkable for covering a vast spectrum of eighteenth-century debates. In formal terms, it is an epistolary as well as a sentimental novel, both of which were widely popular during the eighteenth century. As it is written in letters by several persons, an example of the polyvocal epistolary novel, it provides a broad range of perspectives whereby it achieves exceptional insight into the social, cultural and even political concerns of the era. The thesis will focus on issues of form and on thematic issues: which range from the sentimental construction of ideal femininity and marriage, aesthetic conceptions of the visual appreciation of landscape and depictions of cultural otherness as parts of socio-cultural and literary debates of the eighteenth century. The thesis is consequently divided into three parts. The first part introduces the background of the author and of the novel concentrating on the specificities of its epistolary form. A short introduction into the history and development of this particular literary device will be provided, but the main thrust will be on its functions in the novel, advantages and disadvantages. The second part will observe The History of...

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)0.001
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.077
Threshold uncertainty score0.506

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0200.009
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.006
GPT teacher head0.220
Teacher spread0.214 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)Same topicCanadian Identity and HistoryFrench-language works237,207