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Record W4388734154 · doi:10.1080/17449855.2023.2248555

Interpoetics or the poetics of culture and the culture of poetics in Hannah Lowe, Russell Leong, Marilyn Chin, and Fred Wah

2023· article· en· W4388734154 on OpenAlexaboutno aff
Jonathan Locke Hart

Bibliographic record

VenueJournal of Postcolonial Writing · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicPoetry Analysis and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsPoeticsLiminalityLiteraturePoetryIdentity (music)HybridityArtChinAestheticsHistory

Abstract

fetched live from OpenAlex

Interpoetics is the betweenness and connection between poetry and poetics, viewed from different angles – an examination of the space between that uncovers more about poet, text, image, influence, and genre because it is between and of both sides. The inter is a hyphen, representing either/or and both/and: the cultural poetics of betweenness. Such liminality relates to identity and, thus, a Chinese diasporic or hyphenated poetics. This article examines the poets Hannah Lowe, Russell Leong, Marilyn Chin, and Fred Wah, who explore their own identities: Chinese, American, Canadian, English-speaking, hybrid, and the voice of the poet. How do these poets speak for themselves in a culture that did not always let them speak, and negotiate their art and hybridity or other aspects of their selves as people and artists in ways that refuse, evade, or break the stereotype? Being “Anglo Chinese” is being or writing in English in an English-speaking country.

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: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.037
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.266
Teacher spread0.249 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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