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Robert Duncan’s Big Poetry: Re-visioning the Common

2020· article· en· W3127927867 on OpenAlexaff
Miriam Nichols

Bibliographic record

VenueSillages critiques · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicPoetry Analysis and Criticism
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsArticulation (sociology)Scope (computer science)Reading (process)PoliticsPerspective (graphical)PoetryHumanitiesSociologyPhilosophyAestheticsEpistemologyArtPolitical scienceLawLinguistics

Abstract

fetched live from OpenAlex

This article takes breadth to be the central fact to Robert Duncan’s poetry. It argues for a reading of Duncan’s work from the perspective of his yearning for synthesis, while acknowledging that the “grand collage” Duncan evokes must remain out of reach. It is this daring scope, with its own excesses and distortions, that accounts for the multiple challenges Duncan’s work continues to pose to his readers. This article suggests a different understanding of measure in Duncan­ – an ethical and methodological one, rather than a strictly formal or prosodic one. Duncan’s purpose is at once political, moral and aesthetic, directed toward the articulation of human collectivity, despite the recognition that modern societies are fraught with social and cultural difference.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.034
Scholarly communication0.0110.011
Open science0.0010.005
Research integrity0.0020.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.045
GPT teacher head0.273
Teacher spread0.228 · 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
Published2020
Admission routes1
Has abstractyes

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