MétaCan
Menu
Back to cohort
Record W2233481095

Earle Birney’s Poetry: A Study

2012· article· en· W2233481095 on OpenAlexaboutno aff
Kumar Talanki Jeevan

Bibliographic record

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryModernism (music)LiteratureCosmopolitanismGlobeMetaphysicsArtHistoryArt historyPhilosophyPoliticsLawPsychology
DOInot available

Abstract

fetched live from OpenAlex

In the history of Canadian poetry, one may see three distinct phases, namely, Confederation to the World War I, the 1920s to the World War II, and the late twentieth century to the early twenty-first century. The Canadian poets who appeared during the first phase were largely influenced by the English Romantics and the early Victorians, and looked for themes in their own natural landscape. The poets of the second phase, with the emergence of modernism, created an outlet for the new poetry and reflected their fascination with the sea and with the impersonal violence of nature. But it is only in the third phase, Canadian poetry has undergone radical change with the contribution of poets like Earle Birney and others. These poets exhibited a new social awareness and came out with experimental poetry characterized by cosmopolitanism, metaphysical strains, symbolism, and so on. An attempt is made in the present paper to examine Earle Birney’s three poems - 'David,' 'November Walk,' and 'The Bear on the Delhi Road.' They are extracted from three of his representative anthologies David and Other Poems (1942), Near False Creek Mouth (1964), and Fall and Fury (1978) which show Birney’s encyclopedic knowledge on Canadian subjects and also virtually every part of the globe.

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)0.004
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 score0.737
Threshold uncertainty score0.529

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0230.016
Scholarly communication0.0070.004
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicShort Stories in Global LiteratureFrench-language works237,207