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Record W2337809523 · doi:10.3138/topia.34.39

Dionne Brand’s Environmental Poetics

2016· article· en· W2337809523 on OpenAlexvenueno aff
Cheryl Lousley

Bibliographic record

VenueTOPIA Canadian Journal of Cultural Studies · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
Fundersnot available
KeywordsPoeticsPoliticsPoetryMultitudeMetaphorIdentity (music)AestheticsSublimeSociologyInjusticeGazeArtLiteratureLinguisticsPsychologyPolitical sciencePhilosophyLawPsychoanalysis

Abstract

fetched live from OpenAlex

The language of nature that permeates Dionne Brand’s poetry is often read as a metaphor for place, a site from which the politics of identity, home and belonging are negotiated. But the places through which the politics of inclusion and exclusion are enacted are alive in Brand’s poetry. This essay reads her attention to the living world of nature as an ethical and political engagement with the complex intersections of social injustice and environmental degradation, as traced through the motifs of landscape, territory, cartography, and planetarity in four poetry collections: No Language Is Neutral (1990), Land To Light On (1997), thirsty (2002), and Inventory (2006). In these poems, nature becomes the lived world when experienced through bodily movement not totalized cartography, when voiced in sound rather than pinned down by the gaze, and when recognized as a multitude of both friends and strangers. The expression of love for nature makes the disjuncture between place, belonging, and justice so painful in Brand’s poetry. In marking so carefully the relations of love and power that bind and rupture identity and place, Brand shows how necessary but difficult is the task of making the places we live in actually liveable.

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)0.002
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 score0.992
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.010
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0010.002
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 head0.026
GPT teacher head0.211
Teacher spread0.185 · 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
Published2016
Admission routes1
Has abstractyes

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Same venueTOPIA Canadian Journal of Cultural StudiesSame topicEcocriticism and Environmental LiteratureFrench-language works237,207