The Error of Looking at Indian Marriages Through Occidental Lenses
Bibliographic record
Abstract
This is a cautionary illustration of what errors may occur when marital concepts and assessment tools based on one culture are used to explore another. The Marital Satisfaction Inventory - Revised, largely standardized on Western populations, was administered to 88 male and female middle class urban Hindus (MCUH) residing in New Delhi, India. The inventory items were modified so that the questions asked the respondents to reply in terms of their beliefs about marital relationships. Subsequent exploratory and confirmatory factor analyses clearly demonstrated that the theoretical infrastructure of the MSI-R—its item content and sub-scales—was not at all a “good fit” for the data of these MCUH. These findings are discussed in terms of the challenges of cross-cultural social research and their shaping of all future work by the researchers. The ultimate goal is to produce a behavior actually shaped by other forces. The present study utilizes the National Longitudinal Survey of Youth 1979 and discrete-time event history analysis to examine the influence of religious affiliation and attendance on ethnic remarriage differences. The findings suggest that Catholicism does not account for the lower rates of remarriage of Latinos compared to Whites and provide strong evidence for dispelling the previously untested but frequently assumed Catholic influence on ethnic differences in remarriage.Additionally, Evangelical Protestants, particularly men, appear the most likely to remarry. culturally relevant and valid Indian marital survey instrument for both clinical and academic use.
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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 | 0.024 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".