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Record W7015201383

Reviving the vanishing subject: the subject as abject in postmodern memoir

2017· dissertation· en· W7015201383 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicVladimir Nabokov Literary Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPostmodernismSubjectivityBiographySubject (documents)Deconstruction (building)Rhetorical questionMemoirDialecticSelf
DOInot available

Abstract

fetched live from OpenAlex

My dissertation contemplates rhetorical and ontological problems of self-representation in twentieth century postmodern memoir. Many postmodernists contend the self merely deteriorates amid the fallibility of memory, instabilities of ‘truth’, a Lacanian notion of language as inexpressible of the self, and a subjectivity so multiplicitous and constructed that it is impossible to write. Yet Julia Kristeva’s psychoanalytic notion of abjection – a dialectical process that simultaneously dismantles and reinforces the self – illuminates postmodern autobiographical subjectivity as ultimately revived through literary self-alienation. As such a process of abjection, postmodern autobiography thus involves reconstruction amid deconstruction – wherein a “weight of meaninglessness . . . crushes me” (Kristeva Powers 2) while also ensuring “that ‘I’ does not disappear in it but finds, in . . . sublime alienation, a forfeited existence” (Kristeva Powers 9). This approach resituates the genre as an ethical form of heteroglossic self-renewal, wherein the recognition of self-as-other facilitates an ethical engagement with community in an increasingly pluralistic world. Postmodern autobiography is thus revealed as a relevant, productive space of renewal despite its own claims of futility. I focus on five exemplars of postmodern autobiography – texts written by Lucy Grealy, Suniti Namjoshi, Vladimir Nabokov, Robert Kroetsch, and Michael Ondaatje – to demonstrate how a view of postmodern autobiography as abject translates across such diverse social constructs as nation, gender, diaspora, physicality, memory, class, and the family.

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)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0100.064
Scholarly communication0.0130.018
Open science0.0010.007
Research integrity0.0030.006
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 head0.021
GPT teacher head0.264
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 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
Published2017
Admission routes1
Has abstractyes

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