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Record W7006836755

Voicing the Alternative in Michael Ondaatje's Fiction

2012· article· en· W7006836755 on OpenAlexaboutno aff

Bibliographic record

VenueArchivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Studies and Diaspora
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)ColonialismSri lankaIdentity (music)VoiceOrder (exchange)Prime ministerSpanish Civil War
DOInot available

Abstract

fetched live from OpenAlex

Abstract As well known, Michael Ondaatje, who was born in Sri Lanka (the old Colombo), moved to London in his prime and, then, to Toronto, becoming a Canadian citizen. In Ondaatje’s literary works there is a constant interweaving of voices: from colonial and postcolonial motifs to the use of geography, space, art and music, in order to subtlety suggest the underlining and pervasive theme of identity: in almost all his writings references to both the loss of identity in the colonial period and the atrocity of the civil war in Sri Lanka lead to a sort of image of the international bastard, as Ondaatje himself says in The English Patient. My paper, which is dealing with Ondaatje’s autobiography, Running in the Family, and the novels The English Patient and Anil’s Ghost, refers to other works by M. Ondaatje as well. If Running in the Family is imbued with the idea of a split identity, with recurring references to Canada and Sri Lanka, both The English Patient and Anil’s Ghost have an international setting: Italy, Africa (the desert, Cairo and Egypt), England, India and Canada in The English Patient, Sri Lanka (but several other places in Usa and in Europe, evoked by memory) in Anil’s Ghost, thus suggesting the idea of the “International bastard”. In the two novels, art, music, voices and new technologies interweave with the theme of identity being metaphorically or allusively presented.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.025
GPT teacher head0.223
Teacher spread0.197 · 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 teacher head, 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
Published2012
Admission routes1
Has abstractyes

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