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Record W6987328786

Sounds of the Land of Promise: Listening to Ralph Ellison’s Metaphors of Memory in Invisible Man

2023· dissertation· en· W6987328786 on OpenAlexaff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldPsychology
TopicSound Studies and Aurality
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSoundscapeActive listeningBiographyMemory workOrder (exchange)Sound (geography)Period (music)Genius
DOInot available

Abstract

fetched live from OpenAlex

This project studies Ralph Ellison’s incorporation of sonic memory, soundscapes (sonic environments), and music into his novel Invisible Man (1952). The central focus of this dissertation is the influence of the sonic on Ellison’s work, beyond his interest in jazz. This project argues that Ellison’s work incorporates his memories of sound and music as well as the sonic imagery and philosophies of the sonic he draws from his literary influences, namely T.S. Eliot, James Joyce, and Fyodor Dostoevsky. I approach Invisible Man as a semi-autobiographical text, which I argue transfigures Ellison’s own sonic experiences into fiction. I draw on Ellison’s essays, interviews, and letters, as well as the two major biographies on Ellison, Lawrence Jackson’s Ralph Ellison: Emergence of Genius (2002) and Arnold Rampersad’s Ralph Ellison: A Biography (2007), in order to contextualize the sonic elements and metaphors of memory that Ellison integrates into the soundscapes of Invisible Man. \n \tThis project argues that Ellison is an “earwitness” who draws on the sonic in his work in order to emphasize the significance of listening as well as draw attention to overlooked African-American soundscapes. Carolyn Birdsall elaborates on the term “earwitness” as follows: “In 1977, Raymond Murray Schafer defined the earwitness as an author who lived in the historical past, and who can be trusted ‘when writing about sounds directly experienced and intimately known’ (1994 [1977], p. 6). Schafer’s understanding of the earwitness endorses the authority of literary texts for conveying an authentic experience of historical sounds” (169). Essentially, Ellison and his novel’s narrator are concerned with both the intimacy of listening and the critical consideration of the psychological and personal impact of diverse and unique sound memories and soundscapes. \n\tI employ a variety of approaches in my study of Ellison’s use of the sonic in his work – including history, autobiography, analysis, and compositional method – in order to contextualize the nuances of sonic experience that inform Ellison’s writing. I begin this project with a study of the historical context that informs Ellison’s work, and then I gradually introduce analytical perspectives of the sonic as the dissertation progresses. I scaffold this project in this way in order to foreground the historical, contextual, and subjective uniqueness of listening before I apply scholarly approaches and analysis of the sonic to Ellison’s work later in the dissertation. Chapters One and Two are history-based, as I provide historical context on Harlem’s soundscapes and Ellison’s education at the Tuskegee Institute. Chapters Three and Four are analytical approaches to Ellison’s use of the sonic which build on the background information I provide in Chapters One and Two. Chapter Five blends sonic analysis, autobiographical and historical context, and compositional method in order to demonstrate the breadth of Ellison’s nuanced integration of the sonic into his writing.

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)0.002
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.026
Scholarly communication0.0070.007
Open science0.0010.004
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 head0.020
GPT teacher head0.259
Teacher spread0.239 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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