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Record W1608204014 · doi:10.3138/jcs.44.1.91

Nineteenth-Century English-Canadian Anthologies and the Making of a National Literature

2010· article· en· W1608204014 on OpenAlexvenueaboutno aff
Robert Lecker

Bibliographic record

VenueJournal of Canadian Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsAllegiancePoliticsNationalismHistoryCanadian literatureRepresentation (politics)SociologyMeaning (existential)AestheticsLiteratureLawPolitical sciencePhilosophyArtEpistemology

Abstract

fetched live from OpenAlex

The term “Canadian literature” was popularized by early Canadian anthologists who viewed their collections as evidence of the country’s coming of age. These editors were driven by a mix of evangelical nationalism, political allegiance, literary alliances, and the desire to profit from shifting perceptions of the country and its literature as Canada moved towards the twentieth century. The representation of Canada that emerges in these formative collections is intimately linked to the conditions surrounding their production, which impacted the anthologies as much as the editor’s religious, political, or aesthetic values. These conditions influenced the representation of nation and affected the ways in which readers came to understand the meaning of “country” as a textually constructed ideal. This essay examines seven anthologies of English-Canadian literature published in the nineteenth century in an attempt to determine the kind of values they promoted, the tensions their editors faced, and the extent to which they established canonical norms that would be inherited by their twentieth-century successors.

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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.656
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.277
Teacher spread0.258 · 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

Citations4
Published2010
Admission routes2
Has abstractyes

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