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Record W4413337600 · doi:10.1353/asa.2025.a967529

Documentary Capture: Mercedes Eng's Carceral Poetics

2025· article· en· W4413337600 on OpenAlexaff
Claire Farley

Bibliographic record

VenueASAP/journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American Literature Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPoeticsArtHistoryLiteraturePoetry

Abstract

fetched live from OpenAlex

ABSTRACT: This article focuses on documentary poetry's underdiscussed relationship to forms of surveillance and taxonomization. Mercedes Eng's first two books of poetry, Mercenary English (2013) and Prison Industrial Complex Explodes (2017), show how documentary's foundational strategies—photographing, surveying, reporting—have been instrumentalized as forms of disciplinary capture integral to the administration of the liberal state. By scrutinizing the convergence of documentary and corporeal capture, Eng composes a "carceral poetics" that demonstrates the fugitive potential of working through and underneath the disciplinary tendencies of documentary poetics. Eng's carceral poetics provides an example of "late documentary poetics," a recent phase of documentary poetry's generic development. Late documentary poets address bureaucratic processes thematically by reevaluating and recontextualizing documents from state and legal archives, but they also negotiate liberalism's infrastructure of governance by writing in a genre enmeshed in the biopolitical practices they critique.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.322
Teacher spread0.315 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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