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Record W4289534981 · doi:10.37648/ijrssh.v12i03.007

SILENCE IN JANE URQUHART’S THE STONE CARVERS

2022· article· en· W4289534981 on OpenAlexaboutno aff
Hussein Ali Abbas

Bibliographic record

VenueInternational Journal of Research in Social Sciences and Humanities · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSilenceMeaning (existential)InjusticeFeelingContext (archaeology)Theme (computing)AestheticsVariety (cybernetics)LiteratureHistorySociologyPsychologyPsychoanalysisArtPhilosophySocial psychologyEpistemologyMathematicsComputer science

Abstract

fetched live from OpenAlex

Silence is traditionally recognized as a space of time in which words are not articulated and meaning is not convened. But, silence emerges to have a variety of meanings in literary texts, and that meaning is determined by the context within which silence is placed. The treatment of the theme of silence in 19th century fiction is associated with social injustice and war violence. As shown in the writings of that century, silence replaces feelings and ideas that the authors and/or their characters cannot find the words which can express the victims’ profound pain. In The Stone Carvers (2001), Canadian novelist Jane Urquhart introduces silence as moments of unspoken language, each moment produces two, or more, oppositional meanings, which may affect the characters differently. This research sheds light on the moments of silence that are shown in Urquhart’s novel.

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)0.008
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 score0.083
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0200.026
Scholarly communication0.0080.006
Open science0.0010.005
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.203
GPT teacher head0.447
Teacher spread0.244 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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Same venueInternational Journal of Research in Social Sciences and HumanitiesSame topicDiscourse Analysis in Language StudiesFrench-language works237,207