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Record W4309923233 · doi:10.4324/9781003142683-5

From the Dawn of Modernism to the “Bursting Dam of the Sixties”

2022· book-chapter· en· W4309923233 on OpenAlexaboutno aff
Maria Löschnigg

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicArt, Politics, and Modernism
Canadian institutionsnot available
Fundersnot available
KeywordsModernism (music)HistoryBurstingArt historyArtPsychologyNeuroscience

Abstract

fetched live from OpenAlex

This chapter traces the development of the Canadian short story from the 1920s to the 1950s and shows how, in the course of this period, the modernist short story established itself in Canada. After a brief general introduction to major trends, the first focus will be on Raymond Knister and Morley Callaghan as major catalysts for the emergence of the modernist Canadian short story. The prairie story will be in the centre of the following section, which will zoom in on Sinclair Ross’s work. In this section, I shall also compare Ross’s well-known story “The Lamp at Noon” with Sharon Butala’s “Gabriel” in order to shed light on shifts from the stereotypical format of the Depression narrative to more holistic depictions of the prairies in the 1990s. Another section is devoted to Ethel Wilson, Joyce Marshall and Sheila Watson, with the aim to highlight the distinct achievements of female authors in this formative phase of short fiction in Canada. The chapter will close with a glimpse at decisive changes in the cultural infrastructure of the 1940s and ’50s, including new publication forums and the crucial role of mentors such as Robert Weaver. In his function as organiser of cultural programmes for the Canadian Broadcasting Corporation from 1948 to 1985, in particular, he became a key figure in the consolidation of the genre in Canada.

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: Other · Consensus signal: Other
Teacher disagreement score0.965
Threshold uncertainty score0.663

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 studies0.0170.019
Scholarly communication0.0080.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.083
GPT teacher head0.239
Teacher spread0.156 · 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
Published2022
Admission routes1
Has abstractyes

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