MétaCan
Menu
← Back to cohort

Knister, (John) Raymond (1899–1932)

2018· book-chapter· en· W4234474655 on OpenAlexaffabout
Kait Pinder

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsMcGill University
Fundersnot available
KeywordsPoetrySupporterWifeLiteratureNationalismModernism (music)History of literatureHistoryCriticismPerformance artLiterary magazineArt historyArtLiterary criticismLiterary scienceLawGenealogyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Raymond Knister was one of Canada’s earliest modernist writers. Although Knister is best known as an imagist poet, he wrote and published work in a wide range of genres, including poetry, novels, short stories, book reviews, literary criticism, and one play. Born and raised in the farmlands of southern Ontario, Knister was called the ‘farmer who was poet too’ by fellow Canadian poet Dorothy Livesay. Knister’s writing career, which began in the 1920s, coincided with an age of Canadian nationalism, and despite the fact that Knister found it easier to publish in the USA. than in Canada, he was a great supporter of developing Canadian literature. Like other writers of this time, such as Morley Callaghan and A. J. M. Smith, Knister insisted upon the development of a unique national literature that would remain connected with international literary movements, like modernism, but would be neither an imitation of other literatures or produced for the ephemeral tastes of the market. Knister’s writing career was cut short when he drowned on 29 August 1932, while on holiday with his wife at Lake St Clair in Ontario.

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.591
Threshold uncertainty score0.812

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0380.010

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 head0.023
GPT teacher head0.236
Teacher spread0.213 · 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
Published2018
Admission routes2
Has abstractyes

Explore more

Same topicCanadian Identity and History→French-language works237,207→