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Record W4406289668 · doi:10.2979/vic.00160

Revisioning Victorian(ist) Listening: Rereading Elizabeth Gaskell's Canadian Landscapes through Inuk Sound

2024· article· en· W4406289668 on OpenAlexaboutno aff
Erin Cheslow

Bibliographic record

VenueVictorian Studies · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicPoetry Analysis and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningSound (geography)ArtLiteratureSociologyAcousticsCommunication

Abstract

fetched live from OpenAlex

Abstract: Colonial landscapes permeate the English imagination of the nineteenth century, and our gaze has been fixed on them. There is much more to the Victorian world, however, than meets the eye. The Victorians were immersed in sound, and colonial landscapes were also soundscapes. Elizabeth Gaskell's Mary Barton (1848) ends with Mary looking out over a pristine Canadian landscape from which sound is conspicuously absent. I propose that we reread novels like Gaskell's through the soundscapes of Tanya Tagaq's Split Tooth (2018). The unrepresented soundscapes of Tagaq's narrative refigure sound as form, and, through her text, we are invited to listen differently. Only by hearing the sounds of Victorian novels can we begin to reimagine relations that stem from colonial encounters depicted in their many silences.

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)0.006
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 score0.095
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0290.029
Scholarly communication0.0120.003
Open science0.0020.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.054
GPT teacher head0.310
Teacher spread0.256 · 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
Published2024
Admission routes1
Has abstractyes

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