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Record W4409183225 · doi:10.55917/2154-2171.1099

Making (Non)Sense: On Ruth Ozeki's A Tale for the Time Being

2018· article· en· W4409183225 on OpenAlexaboutno aff
Yunfan Chang

Bibliographic record

VenueAsian American Literature Discourses & Pedagogies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Theory and Philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsSense (electronics)SociologyArt historyArtEngineering

Abstract

fetched live from OpenAlex

This essay investigates the knowledge produced around Ruth Ozeki’s novel A Tale for the Time Being through a discussion of its marketing processes and its reception, as well as through textual analysis. I first draw upon Sau-ling Wong’s observations about the problem of a US-centric referential framework in the internationalization of Asian American studies to examine a Western-centric framing in the marketing strategies of the US/Canada and the UK editions of Ozeki’s novel. Next, I turn to an examination of how reviews and selected readers’ responses to Ozeki’s novel show an at-times incoherent process of making sense of this text. In the latter part of the paper, I analyze the parallel depictions of Fukushima and Cortes Island, Ruth’s dreams, and Haruki #1’s diary in Ozeki’s novel. Attending to how Ozeki’s narratives destabilize the process of making sense, I argue that the novel is neither easy to read nor as transparent as the marketing strategies and reviews and readers’ responses suggest. The difficulties of making sense represented in A Tale for the Time Being thereby have the potential to intervene in a Western-centric, posivistic reading of the Asian other, challenging us to rethink the analytic frameworks we bring to bear while reading Asian American literary texts.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.405
Teacher spread0.373 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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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