Emotional Consequences of Gender-Based Violence: Influences on Ratnamala’s Decision-Making in The Story of Felanee
Bibliographic record
Abstract
This study analyses how the emotional consequences of gender-based violence (GBV) shape Ratnamala's decision to elope with Kinaram in Arupa Patangia Kalita's novel, The Story of Felanee (2011). Focusing on the sociocultural practices of 1940s Assam, this research reveals how GBV, particularly the oppressive norms of widowhood prevalent in Ratnamala's patriarchal, upper-caste Hindu community, profoundly impacts her emotional landscape and ultimately fuels her act of resistance through elopement. By integrating the decision-making framework of Ernst and Paulus with Damasio's Somatic Marker Hypothesis and Kahneman and Tversky's Prospect Theory, this paper provides a nuanced understanding of the interplay between GBV, emotional responses, and Ratnamala's pursuit of autonomy and happiness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".