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Record W4214519311 · doi:10.5430/wjel.v12n1p221

Between the Homeland and Diaspora: Identity Dilemma in Indian Literature

2022· article· en· W4214519311 on OpenAlexvenueno aff
Indrani Atul Borgohain, Deema Ammari

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsHomelandCasteDiasporaSociologyGender studiesCultural identityIdentity (music)Identity formationIdentity politicsPoliticsAlienationPolitical scienceSocial scienceLawAestheticsNegotiation

Abstract

fetched live from OpenAlex

The article aims to analytically and comparatively examine how the negotiation of identity is represented in Indian literature, both in the homeland and abroad, in a situation where cultures meet, collide, and merge. The focus of the article will be on four books: Aravind Adiga’s The White Tiger (2008), Bapsi Sidwa’s Water (2006), Kiran Desai’s The Inheritance of Loss (2006), and Bharathi Mukherjee’s Jasmine (1989). All the authors write about identity from a particular cultural context: the Bengali community in the USA, Brahmins in the Indian caste system, the privileged and less-privileged status of Indian individuals, and the hegemonic aspirations of the middle class that have taken the form of politics and produce socio-cultural inequalities. Because of the complex social structure dominated by the Indian caste system, one aspect of migrant experiences is the limitations placed by society on their identity, which can also be a critical determinant of their economic well-being and thus affect identity formation. Accordingly, the presumption is that the utility of the protagonists, both the immigrants and the locals in their homeland, encompasses economic well-being and cultural identity. Despite their sense of alienation, displacement, and rootlessness, the protagonists in all the novels that I have mentioned above manage to carve out a space of belonging for themselves, be it in their homeland or abroad, despite social, political, and cultural obstacles.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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.

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

Citations4
Published2022
Admission routes1
Has abstractyes

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