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Record W1533371911

Essays in Poetry, Mainly Australian : Vincent Buckley and the Question of the National Literature

2010· article· en· W1533371911 on OpenAlexaboutno aff
William Hatherell

Bibliographic record

VenueJournal of the Association for the Study of Australian Literature · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryAmbivalenceRomanceCriticismLiterary criticismContext (archaeology)LiteratureHistoryAustralian studiesAmerican literatureWorld literatureSociologyVictorian literatureCanadian literatureGender studiesArtPsychoanalysisPsychology
DOInot available

Abstract

fetched live from OpenAlex

Vincent Buckley's Essays in Poetry, Mainly Australian (1957) was Buckley's major contribution to the formation of an Australian literary canon, particularly one fit for study in the newly emerging academic discipline of Australian literature. This essay examines Essays in the context of both contemporary debates about Australian literature and culture, and the broader religio-cultural approach evident from Buckley's critical writing about Anglo-American literature and criticism as well as his Australian work. It argues that Buckley's ambivalent attitude to Australian literature, and the academic teaching of this literature, needs to be considered in the light of his anxieties about the status and role of romantic and post-romantic poetry in a modern world characterised by a lack of belief in transcendent values.

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)0.003
metaresearch head score (Gemma)0.010
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: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.008
Scholarly communication0.0060.004
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.309
Teacher spread0.295 · 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
Published2010
Admission routes1
Has abstractyes

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