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Record W3041612789 · doi:10.3138/utq.89.2.02

<i>Nox,</i> Unboxed: Anne Carson’s Uncommon Long Verse “Epitaph” (or Economies of the Unlost)

2020· article· en· W3041612789 on OpenAlexvenueno aff
Christine Wiesenthal

Bibliographic record

VenueUniversity of Toronto Quarterly · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsnot available
Fundersnot available
KeywordsElegyEpitaphLiteraturePoetryPhilosophyArtMateriality (auditing)Aesthetics

Abstract

fetched live from OpenAlex

Anne Carson’s Nox (2010) is a multi-form double elegy in memory of the poet’s brother, Michael, and of an elegiac precursor to Catullus’s “Elegy no. 101.” While Nox’s uniquely monumental form has invited analyses particularly by scholars of media studies and book history, this article focuses instead on Nox’s conceptualization at the intersection of elegy and epitaph. I argue that Nox’s peculiar contribution to contemporary elegy arises from its merging of the long poem elegy with the epitaph, resulting in a poetics of loss that is at once expansive and economical. As such, Nox embodies the paradox of an epitaph in long verse form, a form marked by a unique style of ironic economic rationalism. Further, I argue that Nox requires reading strategies that take into account both its materiality as a textual artefact and its simultaneous excess of that materiality, insofar as it can be read as a further unfolding from earlier phases of Carson’s work with elegy and epitaph, especially Economy of the Unlost (1999).

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.002

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 head0.180
Teacher spread0.154 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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