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Record W7052297092

The sentence is a lively place: Virginia Woolf and Diane William's experiments in the short form

2018· dissertation· en· W7052297092 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typedissertation
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsSentenceNarrativePerceptionReading (process)Character (mathematics)Inverted sentencePoetics
DOInot available

Abstract

fetched live from OpenAlex

In "The Sentence is a Lonely Place" (2009), Gary Lutz calls for more literature that recognizes the sentence to be "the one true theater of endeavor, as the place where writing comes to a point and attains its ultimacy" (5).As a response, this thesis considers the role of the sentence and readerly perception in the experimental short fiction of Virginia Woolf and Diane Williams.Woolf and Williams use their short stories to write the perceptual moment and they leverage the sentence and its effects toward this end.The short story is the ideal form for this perceptual thematics and poetics of the sentence given its ability to focus readerly attention on the sentence unit.Woolf and Williams exploit this by breaking the sentence in their stories, privileging fragmentation and ellipsis over linear narrative strategies and relying on their readers to do the perceptual work of reading between the gaps for story.This thesis argues that such an active, participatory reading practice allows for an innovative approach to character that resists conventions of psychological realism.Ultimately, I suggest that the result of Woolf and Williams's sentence-oriented aesthetic provides a way of writing character that is specific to the short form.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.241
Teacher spread0.229 · 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
Published2018
Admission routes1
Has abstractyes

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