Do spouses influence each other's stated son preference?
Bibliographic record
Abstract
Purpose This paper aims to understand the motivations behind married men preferring sons and to quantify the association between a couple’s stated son preferences. Son preference is an endemic problem in India. With half a million female foetuses aborted each year, the root causes of son preference in India have been widely studied. Little is known, however, on how couples mutually decide on their desired child sex-ratio. Design/methodology/approach Using data from the third National Family and Health Survey, the authors apply three-stage least square and optimal general method of moment methods to demonstrate association. Robustness checks are performed on plausibly exogenous instrumental variables and selection issues in the marriage market. Findings The authors show that their spouse's son preference is by far the most significant factor associated with a person's own stated son preference. The association between spouse's stated son preference is observed only for couples being married for three to five years. It is postulated that this is the critical period when sex-selective abortion decisions are being made. Originality/value The focus of existing empirical studies is nearly always on the mother's son preference only. The hypothesis is that spouses mutually influence each other’s preferences and models estimating determinants of son preference should include preferences of both spouses. To the best of the authors’ knowledge, this is the first attempt to understand the motivations of married men towards preferring sons and quantify the association between spouse's stated son preference and respondent's stated son preference.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".