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Record W2747613864 · doi:10.15353/cjds.v6i3.370

Escaping “The Organism, Signifiance, and Subjectification” in the Recounting Huronia Project

2017· article· en· W2747613864 on OpenAlexaffvenue
David Fancy

Bibliographic record

VenueCanadian Journal of Disability Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsBrock University
Fundersnot available
KeywordsSubjectificationDeleuze and GuattariContext (archaeology)SociologyAestheticsEpistemologyJigsawPoetryKey (lock)OrganismPsychologyComputer scienceLinguisticsPedagogyHistoryPhilosophy

Abstract

fetched live from OpenAlex

Describing creative activity undertaken by researchers and co-researcher survivors in the context of the Recounting Huronia project, this paper extends existing literature on Deleuze & Guattari and disability arts by exploring how artistic activity provides opportunities for escape from the constraints of what Deleuze and Guattari (1987) describe as the three central strategies by which restrictive systems capture bodies, namely the stratifications of “the organism, signifiance, and subjectification.” Examined in this paper are the specific ways in which one survivor’s involvement in storybook making, poetry, and performance lead to the bundle “percepts” and “affects” in such a way as to generate what Deleuze and Guattari (1994) describe as artistic “monuments.” Far from being constituted by fixities, such monuments provide key pathways for potentially liberatory disarticulations of the restrictive organism, for experimentation in the face of limiting signifiance, and new individuations beyond institutionally coded subjectifications.

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)0.009
metaresearch head score (Gemma)0.011
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: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0180.040
Scholarly communication0.0090.004
Open science0.0030.012
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.149
GPT teacher head0.424
Teacher spread0.276 · 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
Published2017
Admission routes2
Has abstractyes

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