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Record W2496177078

Ethics, Intention, and Affect: A Proprioceptive Poetics in Roy Miki’s Mannequin Rising

2014· article· en· W2496177078 on OpenAlexaffvenue
Ranbir K. Banwait

Bibliographic record

VenueStudies in Canadian Literature · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPoeticsCommodificationAppropriationAestheticsSocialitySociologyConsciousnessBiopowerGlobalizationEpistemologyLiteratureArtPhilosophyPoetryLawPolitical sciencePolitics
DOInot available

Abstract

fetched live from OpenAlex

In Mannequin Rising , poet Roy Miki explores the active and ongoing constitution of the subject in order to consider how globalization and market forces are rewriting the spaces we inhabit. Critiquing the commodification, appropriation and consumption of different forms of life, the poet situates the human body within a vast network of globalizing processes and in the array of human and extra-human infrastructures underlying them. In particular, Mannequin Rising suggests how a biopolitics of life – intent on policing, manipulating and mining the parameters of human life and human sociality – consumes and melds into the material world. Exploring Miki’s poetics, this article examines how Mannequin Rising channels a need to address the historical processes that shape a place, while being attentive to the body’s contemporaneity. As the text reflects, the frames of globalization are bound up with the legacies of colonialism and racialization. This article argues that Miki’s engagement with the body as a proprioceptive and affective entity creates space for the workings of memory and historical consciousness. In other words, a proprioceptive poetics represents the poet’s task of encountering and apprehending the world.

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 score0.850
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.048
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0020.003
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 head0.038
GPT teacher head0.370
Teacher spread0.332 · 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
Published2014
Admission routes2
Has abstractyes

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Same venueStudies in Canadian LiteratureSame topicGeographies of human-animal interactionsFrench-language works237,207