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Record W2055059917 · doi:10.1177/0021989408091229

“Dishonourably Postnational”? The Politics of Migrancy and Cosmopolitanism in Rohinton Mistry's A Fine Balance

2008· article· en· W2055059917 on OpenAlexaff
Caroline Herbert

Bibliographic record

VenueThe Journal of Commonwealth Literature · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsCosmopolitanismPoliticsDutyHomelandSociologyBalance (ability)Gender studiesNarrativeMedia studiesPolitical scienceLawLiteratureArtPsychology

Abstract

fetched live from OpenAlex

This article explores Rohinton Mistry's novel A Fine Balance (1996), alongside his short story “Lend Me Your Light” (1987), focussing on the tensions between the politically-distanced cosmopolitan migrant and the socially-committed local activist. My readings draw on Radhakrishnan's notion of diasporic “double duty” — of accountability to, rather than irresponsible detachment from, the homeland. Mistry's representations of migrants, I contend, are centrally concerned not only with the necessity, but also the difficulty, of performing such “double duty” through a sustained engagement with India's history and politics. In this light, I argue that Mistry offers representations of migrants whose attempts to distance themselves from local and national politics are revealed as impossible and irresponsible. Moreover, I suggest that Mistry's representations reveal an anxiety over his position as a migrant writer, and his work seems to mobilize writing as a means of avoiding a problematically apolitical detachment from India. Thus, Mistry establishes a tension between his representation of the migrant within his fiction and his negotiation of his own migrant position through his fiction.

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)0.002
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
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.018
Scholarly communication0.0050.004
Open science0.0000.003
Research integrity0.0010.003
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 head0.015
GPT teacher head0.222
Teacher spread0.207 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

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