Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".