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Record W594286511

Marginalisation and the construction of South-Asian identity in novels by Rohinton Mistry, Shyam Selvadurai and Moyez Vassanji

2002· article· en· W594286511 on OpenAlexaboutno aff
Narvadha Salaye

Bibliographic record

VenueKnowledge UdeS (Institutional Deposit of the University of Sherbrooke) · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)South asiaHistoryGender studiesSociologyAestheticsArtAncient history
DOInot available

Abstract

fetched live from OpenAlex

The three texts analysed in this thesis are A Fine Balance by Rohinton Mistry, Funny Boy by Shyam Selvadurai and No New Land by Moyez Vassanji. These novels represent characters who experience different types of marginalisation that mediate their South-Asian identity, marginalisation based on caste, class, gender, sexual orientation, race, language and exile. These novels suggest that marginalisation can take place at home or abroad, for the stories are set in India, Sri Lanka and Canada. The thesis discusses the role of diasporic writing in constructing a sense of South-Asian identity. I explore the way these fictional works by South-Asian Canadian writers construct the identity of different minority groups such as women, untouchables, homosexuals, and immigrants through realism and cultural memory. This thesis is divided into three chapters in which marginalisation will be examined in its various forms."--Résumé abrégé par UMI

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.017
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.180
Teacher spread0.167 · 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 designQualitative
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
Published2002
Admission routes1
Has abstractyes

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