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Record W1782637181

Restorative Nostalgia and Reconstruction of Imaginary Homeland in The Namesake

2014· article· en· W1782637181 on OpenAlexvenueno aff
Ling Yun

Bibliographic record

VenueStudies in literature and language · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHomelandDiasporaHybridityIdentity (music)The ImaginaryIdeologyCompromiseSociologyAestheticsGender studiesHistoryAnthropologyArtPolitical scienceLawPsychologyPsychoanalysisSocial science
DOInot available

Abstract

fetched live from OpenAlex

As a writer of Indian diaspora in America, Jhumpa Lahiri explores the themes like dislocation, displacement and identity. In The Namesake , she writes about the Indian American people’s nostalgia for their home country. The couple Ashima and Ashoke reconstruct an imagined homeland through their interaction with Indian American community around them. The Indian American community helps preserve Indian cultural heritage through holiday celebrations and other parties in which the people in exile speak their own language and perform their cultural rituals. Striding Indian and American two cultures, the Indian American community also has a hybrid identity. This hybridity is a compromise people have to make in order to survive in a different culture but meanwhile it can also be a way to resist against the main stream ideology. In this way, people in the community transcend their former nostalgia and become more open, global nomads in the world.

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)0.003
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 score0.028
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0280.038
Scholarly communication0.0070.006
Open science0.0010.008
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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
Published2014
Admission routes1
Has abstractyes

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