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Record W4220997665 · doi:10.5430/wjel.v12n2p3

The Role of Gender and Cultural Psychology in the Discourse of Chitra Banerjee Divakaruni’s Arranged Marriage

2022· article· en· W4220997665 on OpenAlexvenueno aff
C. G. Karthikadevi, C. Jothi, P. Priyadharshini

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCultural psychologyPopularitySociologyHofstede's cultural dimensions theoryPsychologyCultural issuesCultural studiesSection (typography)PsychoanalysisSocial psychologyCultural diversityEpistemologyAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

The term 'Cultural Psychology' refers to the idea that culture and mind are inseparable. Cultural Psychology has its root from the 1960s and 1970s. But it has attained its zenith and popularity during the 1980s and 1990s. Some of the prominent cultural psychologists are Harry C. Triandis, Fiske, Hofstede, Susan T. Fiske, Eva Magnusson, Jeanne Marecek, Hazel Rose Markus, Shinobu Kittayama, Richard Shweder etc. The present study aims to portray the issues of gender bias and male domination through the cultural conflict which affects the characters physically and psychologically in Chitra Banerjee Divakaruni’s Arranged Marriage. The Introduction deals with the overall view of the stories and themes. The Literature review focuses on the studies relevant to cultural psychology. The Methodology section discusses the cultural and gender issues with the theory and approaches of Eva Magnusson and Jeanne Marecek's Gender and Culture in Psychology. The Discussion part gives the results of the study. The study is compared and discussed with the other studies relevant to gender-based and cultural psychology concepts. The conclusion sums up the entire study and its limitation and scope for future researchers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.173
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.022
GPT teacher head0.341
Teacher spread0.319 · 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.

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
Published2022
Admission routes1
Has abstractyes

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