Marital Ideoscapes in 21st-Century India: Creative Combinations of Love and Responsibility
Bibliographic record
Abstract
Although arranged marriage has survived in India, the custom is increasingly challenged by the current influx of new commodities, media, and ideas. Interviews with 15 male and 15 female unmarried professionals, age 22 to 29, in Vadodara, Gujarat, showed that educated youth have moved beyond the conventional love-versus-arranged marriage dichotomy. They instead focus on achieving specific goals: intimacy, equality, and personal choice, along with supernatural support, growing into love, and brides joining husbands’ families. To achieve these aims, they use both systems: separately, simultaneously, and in creative combinations. The theories of Arjun Appadurai explain that as the Western-inspired ideoscape of romantic love encounters Indian family values, Indian upper-middle-class youth respond by generating hybrid goals and systems of mate selection. They have linked imagination to hope and are using voice within their families to win the recognition, and often the partners, they seek.
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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 | 0.002 | 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 | 0.012 | 0.015 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".