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Record W1558656819

David Malouf: Exploring Imperial Textuality

2006· article· en· W1558656819 on OpenAlexvenueno aff
Saadi Norman Nikro

Bibliographic record

VenuePostcolonial text · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature, Film, and Journalism Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsThe ImaginarySubjectivityTextualityNarrativeLiteratureAestheticsWildernessHistoryPhilosophyArtEpistemologyPsychoanalysis
DOInot available

Abstract

fetched live from OpenAlex

David Malouf's novels An Imaginary Life and Remembering Babylon explore the figure of an otherness that both disrupts and eludes the familiar and habitual. Both novels situate this figure of otherness at the very edge of the cultural landscape, undermining the neat division of self and other, in effect rewriting frontier narratives of conquest and exploration. Such narratives structure their writing in terms of a journey into the wilderness or outback whereby an experience of the lack of sense and meaning serves mainly to assert the subject's capacity to express its developing understanding of the world around it. As the writing of Malouf's novels draws subjectivity to a fugitive terrain where the terms of self-understanding recede into the infinite murmur of an apparent senselessness, the figure of otherness comes to speak a language of creative self-learning. And yet this figure of otherness in An Imaginary Life tends to disappear into the folds of a Rousseauian concept of Nature that works to stage a transcendental recuperation of both self and other. Remembering Babylon does not share this romantic conception of otherness, and could be read as a rewriting of the earlier novel. Emphasis would be placed on how subjectivity comes to stage itself as the scene of a learning of the cultural landscape.

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)0.005
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 score0.011
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.016
Scholarly communication0.0080.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.036
GPT teacher head0.235
Teacher spread0.199 · 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

Citations2
Published2006
Admission routes1
Has abstractyes

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