Social Dimensions of Human Development: Trends of Union Dissolution in India
Bibliographic record
Abstract
Union dissolution, encompassing divorce and separation, is an integral aspect of social transformation, reflecting shifts in societal norms, gender roles, economic independence, and legal frameworks. In India, while marriage has traditionally been seen as a lifelong commitment, increasing urbanisation, economic independence of women, and legal reforms have contributed to shifting perceptions of marriage, leading to greater acceptance of dissolution. The incidence of divorce and separation in India has historically been low compared to Western societies. However, there has been a steady increase in marital dissolution as indicated in this exploratory study that impacts the women immensely. Women, particularly in middle age groups, are more vulnerable to dissolution, with separation rates significantly higher than divorce rates. Factors such as financial independence, domestic conflicts, changing social norms, and globalisation have influenced this trend. Union dissolution varies across regions, showing a distinct north–south divide, with southern states experiencing higher dissolution rates. Among religious groups, Christians have the highest dissolution rates, particularly in urban areas. Across all demographics, separation remains the dominant form of dissolution. While union dissolution is increasing in India, challenges such as social stigma, economic hardship, and legal battles persist. Addressing these concerns through legal reforms, social awareness, and economic empowerment is crucial for ensuring the well-being of individuals undergoing marital dissolution.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".