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Record W136477721 · doi:10.4000/lisa.6026

« Little grunts, the grins and grimaces of recognition »: Resistance and Exchange in Paul Muldoon and Norman MacBeath’s Plan B

2014· article· en· W136477721 on OpenAlexaff
Alexandra Tauvry

Bibliographic record

VenueRevue LISA / LISA e-journal · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsTrinity College
Fundersnot available
KeywordsHumanitiesArtPoetryPhilosophyLiterature

Abstract

fetched live from OpenAlex

Une grande partie du récent travail de Paul Muldoon a été consacrée à l’expérimentation avec les arts visuels et, en particulier, la photographie. Il a récemment publié un ouvrage intitulé Plan B (2009) en collaboration avec le photographe écossais Norman McBeath. Cet ouvrage présente au lecteur un nouveau genre : la « photoetry » (de l’anglais photography et poetry). En effet, Muldoon explique dans l’avant-propos que les poèmes et les photographies établissent « toutes sortes de connections qui leur sont propres, aucune n’étant évidente […] elles sont néanmoins d’une certaine manière toutes significatives, toutes accompagnées de petits grognements, les sourires et grimaces de la reconnaissance ». Cependant, bien que cet ouvrage mette en regard les poèmes et les photographies, Muldoon a de plus en plus recours au procédé littéraire de l’ekphrasis dans le but d’exploiter le travail des photographes. La poésie de Muldoon est parfois proche du palimpseste, une réserve de mots et d’images cachés qui n’apparaissent qu’en filigrane.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.066
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.039
Scholarly communication0.0110.009
Open science0.0010.007
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0050.001

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 head0.034
GPT teacher head0.215
Teacher spread0.181 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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Same venueRevue LISA / LISA e-journalSame topicPhotography and Visual CultureFrench-language works237,207