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Record W2416128801 · doi:10.1057/9780230354647_11

The Returning Reader: Canadian Serial Fiction and Mazo de la Roche’s Jalna Novels

2012· book-chapter· en· W2416128801 on OpenAlexaboutno aff
Candida Rifkind

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2012
Typebook-chapter
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsMiddlebrowHighbrowHistoryPhenomenonTasteSloganPopular cultureLiteratureModernityContext (archaeology)ArtMedia studiesAestheticsSociologyPolitical sciencePsychologyLawPhilosophy

Abstract

fetched live from OpenAlex

There is still much work to be done on the dynamics of middlebrow fiction in English-Canadian literature, especially that from the early twentieth century. The majority of studies focus on either popular or modernist fiction, pointing out the often-blurred line between these two positions in the English-Canadian field of cultural production. Landmark studies of women writers include Carole Gerson’s work, Clarence Karr’s Authors and Audiences: Popular Fiction in the Early Twentieth Century (2000) and Glenn Willmott’s Unreal Country: Modernity in the Canadian Novel in English (2002). 1 Such discussions of highbrow aspirations and popular achievements in the Canadian fiction market tend to neglect the mediating term, ‘the middlebrow’. Examination of the use of this term in a Canadian context provokes debate about distinctions of taste, the dynamics of gender, real and imagined audiences, popular and critical reception, ephemeral celebrity and canonical endurance. I propose that one starting point for an investigation of the middlebrow as a distinct phenomenon in Canadian literature is serial fiction from the first half of the twentieth century, more specifically from the modern period that spans 1920–1960. Recent British and American studies of the middlebrow open up a conceptual terrain for the study of Canadian serial fiction from this period that understands it as part of an international phenomenon with its own peculiar national inflections. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.093
Threshold uncertainty score0.451

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0320.012
Scholarly communication0.0110.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.001

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 head0.014
GPT teacher head0.212
Teacher spread0.198 · 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
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
Published2012
Admission routes1
Has abstractyes

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