Young adults' partner preferences and parents' in‐law preferences across generations, genders, and nations
Bibliographic record
Abstract
Abstract To examine cultural, gender, and parent–child differences in partner preferences, in eight countries undergraduates (n = 2,071) and their parents (n = 1,851) ranked the desirability of qualities in someone the student might marry. Despite sizable cultural differences—especially between Southeast Asian and Western countries—participants generally ranked kind/understanding (reflecting interpersonal communion) highest, and intelligent and healthy (reflecting mental/physical agency) among the top four. Students valued exciting, attractive partners more and healthy, religious partners less than parents did; comparisons with rankings by youth in 1984 (i.e., from the parents' generation) suggested cohort effects cannot explain most parent–child disagreements. As evolutionary psychology predicts, participants prioritized wives' attractiveness and homemaker skills and husbands' education and breadwinner skills; but as sociocultural theory predicts, variations across countries/decades in gendered spousal/in‐law preferences mirrored socioeconomic gender differences. Collectively, the results suggest individuals consider their social roles/circumstances when envisioning their ideal spouse/in‐law, which has implications for how humans’ partner‐appraisal capabilities evolved.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".