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Record W4414444869 · doi:10.53555/wwxx5g79

Voicing The Silenced: Care Ethics And Intersectional Identity In The Feminist Reimaginings Of Jaya And Sita

2025· article· en· W4414444869 on OpenAlexvenueno aff
Kumari Manju

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIntersectionalityEthics of careSilenceIdentity (music)EmpathyFeminist ethicsVoiceToll

Abstract

fetched live from OpenAlex

This paper presents a comparative study of care ethics and Intersectionality in Shashi Deshpande’s That Long Silence (1988) and Chitra Banerjee Divakaruni’s The Forest of Enchantments (2019). Both novels explore the emotional and moral dimensions of caregiving within patriarchal contexts. Sita’s roles as daughter, wife, and mother in The Forest of Enchantments reveal the undervaluation of care labor and the ethical weight of empathy and compassion. In contrast, That Long Silence portrays Jaya’s internal conflict between personal aspirations and traditional caregiving expectations, exposing the psychological toll of gendered roles. By applying Intersectionality, this study examines how the protagonists’ identities shaped by gender, class, and familial roles inform their caregiving experiences. Care ethics provides a lens to understand the relational and moral significance of their actions. Through this dual framework, the paper highlights how both authors challenge patriarchal norms and advocate for a deeper recognition of care labor and women’s resilience in literature.

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)0.005
metaresearch head score (Gemma)0.005
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 score0.023
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0230.049
Scholarly communication0.0070.008
Open science0.0010.012
Research integrity0.0020.008
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 head0.174
GPT teacher head0.392
Teacher spread0.218 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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