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Negotiating Conflict between Personal Desires and Others' Expectations in Lives of Gujarati Women

2009· article· en· W2148889521 on OpenAlexaboutno aff
Vaishali V. Raval

Bibliographic record

VenueEthos · 2009
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsnot available
Fundersnot available
KeywordsPersonhoodGujaratiAgency (philosophy)SociologyGender studiesNegotiationNarrativeConceptualizationIndividualismInterpersonal communicationSocial psychologyPsychologyPolitical scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

Abstract A substantial body of literature in psychological anthropology has challenged the stereotypical depiction of South Asian women as passive subordinates in patriarchal families, and has provided accounts of these women as actors in their social world. Focusing specifically on situations of interpersonal conflict in this article, I analyze the narratives of Gujarati women from two cohorts, daughters‐in‐law in Gujarat, India and mothers‐in‐law in Gujarati immigrant families in Canada, to argue that these women actively engage in negotiating the conflict between their wishes and others' expectations. The mode of agency that they exercise is less egocentric and more relational—the decision making and negotiations occur within the parameters of their familial roles, rather than rebellion against family structures, and their actions are driven by motivations involving the welfare of their children and grandchildren, rather than “individualistic” desires. These narratives, along with ethnographic works exploring South Asian personhood, call for the need to broaden the conceptualization of agency, and challenge the appropriateness of traditional individualistic feminism in understanding the lives of women globally. [India, women, personhood, agency, interpersonal conflict]

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.012
Scholarly communication0.0060.002
Open science0.0010.006
Research integrity0.0010.002
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 head0.135
GPT teacher head0.403
Teacher spread0.268 · 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 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

Citations16
Published2009
Admission routes1
Has abstractyes

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