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Record W2414165096 · doi:10.3138/jcs.49.2.87

Hiding in Plain Sight: A New Narrative for Canadian Literary History

2015· article· en· W2414165096 on OpenAlexvenueaboutno aff
Alison Calder

Bibliographic record

VenueJournal of Canadian Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativePoliticsWhite (mutation)HistoryColonialismSociologyValue (mathematics)History of literatureCanadian literatureLiteratureAestheticsLawArtArchaeologyPolitical science

Abstract

fetched live from OpenAlex

This essay imagines a new genealogy for Canadian Prairie writing, arguing that the development of a limited Prairie literary canon has led to two related critical perceptions: first, that early Prairie writing is of little value; and second, that there is little engagement with questions of colonial contact and intercultural relations between settler and Aboriginal cultures in early Prairie writing. While canonical Prairie texts generally depict the Prairie as agricultural space from which Aboriginal inhabitants have already been removed, lesser-known texts often engage with, and frequently re-enact the process of, that removal. Both kinds of texts depict the Prairie as White space, but the canonical ones present that construction as a fait accompli, whereas the lesser-known ones repeatedly depict its processes. This essay provides short readings of three lesser-known novels published before 1950 to show authors engaging in regional and national conversations about the future of the nation in ways that expand our understanding of the political work done by these novels and by the current Prairie canon itself.

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)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.740
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.000
Science and technology studies0.0010.000
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 head0.117
GPT teacher head0.303
Teacher spread0.186 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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