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Record W3184572730 · doi:10.5430/wjel.v11n2p19

Edward Said’s Memoir Out of Place: Postcolonial Tenets, Dissonant Voices, and Divided Loyalties

2021· article· en· W3184572730 on OpenAlexvenueno aff
Shadi Neimneh, Halla A. Shureteh

Bibliographic record

VenueWorld Journal of English Language · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMemoirHomelandAestheticsSociologyContext (archaeology)Identity (music)ConfessionalHistoryLiteraturePhilosophyArtLawPolitical science

Abstract

fetched live from OpenAlex

Edward Said’s Out of Place (1999), a memoir written after his diagnosis with leukemia in 1991, was begun in 1994 to document his sense of cultural displacement and imminent death. This article examines the divided loyalties and dissonant voices Said vents in this book through the lens of cultural theories. It argues that such a conflicting vision can provide a proper context for understanding Said’s contributions to cultural studies and literary theory via the construction of the other, the out of place, at the levels of language, religion, environment, and homeland. Said presents himself as a postcolonial subject par excellence with divided loyalties and “unhomely” feelings. He uses a confessional mode to convey a constant sense of exile and identity crisis. Said’s life negotiated the postcolonial parlance he preached in his academic life, which offers a unique case on the relationship between theory and practice. The memoir emerges not only as an autobiographical text but equally as a contribution to literary theory and overlapping postcolonial discourses. Thus, this autobiographical memoir is useful for the literature classroom due to its theoretical value as well as non-fictional import.

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)0.001
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.016
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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
Published2021
Admission routes1
Has abstractyes

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