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Record W7041214738

Prose poems

2017· article· en· W7041214738 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2017
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryNarrativeSubject (documents)ExpansiveThe artsWhitingStudioComics
DOInot available

Abstract

fetched live from OpenAlex

Poems show us strange things about the world; they take us to strange new\n places where we, readers, become ‘strange cargo’ ourselves. At the same time, ours are the ‘foreign voices’ to which the poems wake. In this anthology, published in England, a selection of work by five Australian poets is subject to all these shifting perspectives. Interestingly, all five have spent significant and productive time overseas: Jen Webb lived in South Africa, New Zealand and Canada before settling in Australia; Sarah Holland-Batt spent her childhood in both Australia and the US; Cassandra Atherton has been visiting scholar at Harvard and a fellow at Sophia University, Tokyo; Paul Hetherington wrote a recent book while undertaking an Australia Council for the Arts Literature Board Residency at the BR Whiting Studio in Rome; and Lucy Dougan, born in Perth on the western coast of Australia, to which she has returned, is seen in this volume writing with disarming clarity about experiences in Naples and London. Notable here is the presence of the prose poem, a form enjoying considerable popularity in Australia, as indeed it is in the UK. One poet, Cassandra Atherton, writes exclusively in that form, weaving deft (and often very funny) intertextual references into her imaginative flights. For her, the prose poem is often an expansive poetic stage despite the relative brevity of the prose poem form. Jen Webb too prefers the fluid, often fragmented narrative that this form affords as\n her work explores the transformative nature of many ‘ordinary’ encounters and moments. Paul Hetherington has also adopted it for some of his poems, exploring within its frame the shifting and mysterious nature of the quotidian.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.031
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.007
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0310.010

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 head0.087
GPT teacher head0.292
Teacher spread0.205 · 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
Published2017
Admission routes1
Has abstractyes

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