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Record W3159602815 · doi:10.24908/iqurcp.8319

Naming and Indication in The One Secret That Has Carried

2016· article· en· W3159602815 on OpenAlexvenueno aff
Ryan McQuaid

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)PoetryReflexive pronounReading (process)Theme (computing)LiteratureSelfPhilosophyAestheticsHistorySociologyLinguisticsPsychologyArtEpistemologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This essay explores the ways in which Foucaldian indication and naming operate as mediums through with truth, sex, and sujectivities communicate in the poem The CarrieOne Secret That Has Carried by Jason Shinder. The essay examines the position of sexual acts in the poem, and determines that they function as sites of indication from which truth can be procured. These sites of indication operate as privileged spaces of truth within the poem which imply a compulsory body project fro the subject reading them. Self-naming is also explored. The ways that the narrating subject names himself and other spaces/subjects in the poem is examined to elucidate how a healthy/sick binary is generated and how this binary is implemented and enforced in discourse. A theme discussed in connection with these investigations is the pathologizing of the narrating subject of the poem. This discussion centres around what structures inform the subjects reading of himself ans pathologized. As well as how the subject's self-naming operates to effect and consolidate eht epathology to which he is predicated.

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)0.005
metaresearch head score (Gemma)0.008
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 score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.044
Scholarly communication0.0050.008
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.354
GPT teacher head0.365
Teacher spread0.011 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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