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Record W2619055838 · doi:10.18778/2353-6098.3.06

Roll a Hard Six: Losing Your Noodle in Raymond Federman’s Double or Nothing

2015· article· en· W2619055838 on OpenAlexaff
Shawna Guenther

Bibliographic record

VenueAnalyses/Rereadings/Theories A Journal Devoted to Literature Film and Theatre · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicContemporary Literature and Criticism
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNothingNarrativeSubject (documents)PsycheThe ImaginaryRepresentation (politics)PsychoanalysisConstruct (python library)LiteraturePsychologyPhilosophyAestheticsHistoryEpistemologyArtComputer sciencePoliticsLaw

Abstract

fetched live from OpenAlex

Raymond Federman’s Double or Nothing is a convoluted representation of the mentallyunstable mind existing as a series of six characters that are at once separate and conjoined: the horrors and traumatic events of the narrative past dismantle the unified subject into a series of schizophrenic sub-personalities, parts of the destabilized Author’s psyche, existing as separate fragments that eventually collide. Further, the imaginary room emerges as the Fifth Person, promising, but failing, to be a central stabilizer of the other fractured selves. Finally, the design of the text echoes the patterns of the traumatized mind, illustrating the inability of a narrative to construct a stable, unified subject and demonstrating the inadequacy of traditional narrative forms. The text, with its obliterations, cropped phrases, and pictorial manifestations, becomes the Sixth Person. However, in the end, the text shows that the past cannot be erased, explained, or reversed; neither can the experimental nature of the novel reach beyond the traumatized, schizoid subject to represent the horrors of the past that caused the Author’s psychotic breach. Federman has rolled a hard six that will repeatedly fragment and unite, just as the traumatic past continues to repeat itself as one that defies representation.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0050.002
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 head0.080
GPT teacher head0.312
Teacher spread0.232 · 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
Published2015
Admission routes1
Has abstractyes

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