Debt, shame, and survival: becoming and living as widows in rural Kerala, India
Bibliographic record
Abstract
BACKGROUND: The health and well-being of widows in India is an important but neglected issue of public health and women's rights. We investigate the lives of Indian women as they become widows, focussing on the causes of their husband's mortality and the ensuing consequences of these causes on their own lives and identify the opportunities and challenges that widows face in living healthy and fulfilling lives. METHODS: Data were collected in a Gram Panchayat (lowest level territorial decentralised unit) in the south Indian state of Kerala. Interviews were undertaken with key informants in order to gain an understanding of local constructions of 'widowhood' and the welfare and social opportunities for widows. Then we conducted semi-structured interviews with widows in the community on issues related to health and vulnerability, enabling us to hear perspectives from widows. Data were analysed for thematic content and emerging patterns. We synthesized our findings with theoretical understandings of vulnerability and Amartya Sen's entitlements theory to develop a conceptual framework. RESULTS: Two salient findings of the study are: first, becoming a widow can be viewed as a type of 'shock' that operates similarly to other 'economic shocks' or 'health shocks' in poor countries except that the burden falls disproportionately on women. Second, widowhood is not a static phenomenon, but rather can be viewed as a multi-phased process with different public health implications at each stage. CONCLUSION: More research on widows in India and other countries will help to both elucidate the challenges faced by widows and encourage potential solutions. The framework developed in this paper could be used to guide future research on widows.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".