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Record W4386847006 · doi:10.11648/j.ellc.20230803.17

The Changing Face of Conjugal Conflicts in Manju Kapur’s <i>The Immigrant</i>

2023· article· en· W4386847006 on OpenAlexaboutno aff
Shahida Begum

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsWifeImmigrationTheme (computing)Gender studiesFace (sociological concept)SociologyPolitical scienceLawSocial science

Abstract

fetched live from OpenAlex

Conjugal relationship is one of the basic human relationships which lay the foundation of family life and strengthen family bonding. Marriage is the basis of this relationship-it begins with marriage and ends with death of or divorce from the partner. It is considered to be the most important human relationships as it has a considerable bearing on domestic peace and social integration. Husband and wife are not just sexual partners in a household but two individuals physically, emotionally, financially, and socially interdependent and in serious commitment to each other. Conflicts arising out of the complications in conjugal relationship have been dealt with as an important theme in Indian English novels. Manju Kapur (b. 1948) is one of the reputed living Indian women novelists in English and her novel, the immigrant (2008), which primarily deals with the theme of immigration to Canada, also presents the changing faces of conjugal conflicts concerning a well settled immigrant who joins his family in India to marry an Indian girl, sponsors his wife for immigration to Canada and brings her to Canada as his conjugal partner. The paper seeks to explore the nuances of the conjugal life of the immigrant couple during the transition from nationalization to globalization, which create problems and trigger conflicts in their life abroad.

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)0.001
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: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.008
Scholarly communication0.0060.002
Open science0.0010.005
Research integrity0.0010.003
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 head0.046
GPT teacher head0.256
Teacher spread0.209 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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Same topicSouth Asian Cinema and CultureFrench-language works237,207