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Poetry & Commons

2022· book· en· W4389635682 on OpenAlexaboutno aff
Daniel Eltringham

Bibliographic record

VenueLiverpool University Press eBooks · 2022
Typebook
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
Fundersnot available
KeywordsCommonsPoetryPoeticsPoliticsVernacularRomanceHistoryLiteratureAgrarian societySociologyArtPolitical scienceLawArchaeology

Abstract

fetched live from OpenAlex

The commons and enclosure are among the most vital ways of thinking about poetry today, posing urgent ecological and political questions about land and resource ownership and use. Poetry & Commons is the first study to read postwar and contemporary poetry through this lens, by putting it in dialogue with the Romantic experience of agrarian dispossession. Employing an innovative transhistorical structure, the book demonstrates how radical Anglophone poetries since 1960 have returned to the “enclosure of the commons” in response to political and ecological crises. It identifies a “commons turn” in contemporary lyric that contests the “new” enclosures of globalized capital and resource extraction. In lucid close readings of a rich field of experimental poetries associated with the “British Poetry Revival,” as well as from Canada and the United States, it analyses a landscape poetics of enclosure in relationship with Romantic verse. Canonical Romantic poetry by Wordsworth and Clare is understood through the fine-grain textures of the period’s vernacular and radical verse and discourse around enclosure, which the book demonstrates contains the seeds of neoliberal political economy. Poetry & Commons ’ contribution to debates in the environmental humanities engages with the work of Anne-Lise François and Anna Tsing, theorizing commoning as marking out subsistence “rhythms of resource,” which articulate plural, irregular, and tentative relations between human and nonhuman lifeworlds.

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)0.003
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 score0.053
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.010
Scholarly communication0.0080.007
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0530.018

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 head0.026
GPT teacher head0.172
Teacher spread0.146 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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