Hi, My Name is Wealthy: Women’s Dating Behaviors in Relation to the Perceived Wealth of Perspective Mates
Bibliographic record
Abstract
It has been cross-culturally documented that women exhibit a preference for mates who possess resources or traits that signal potential wealth.The majority of this literature relies on self reported mate preferences.Here we report on two experiments to test whether women's willingness to date men is actually influenced by their perceived wealth.Online dating profiles were created to present photographs of men and information about their current bank account status (Study 1), or to indirectly indicate their level of wealth (Study 2).In Study 1, the faces were presented with alternating high and low bank account balances.We hypothesized that women who viewed men with high bank account values would evaluate them as more desirable than women who viewed men with low bank account values.That is, they would be more likely to engage with him in an online conversation, meet with him for a casual coffee, accept an invitation of a date, consider him for a one-night stand, consider him for a short-term relationship, or consider him for a long-term relationship.It was also hypothesized that women would rate the men with high bank account balances as more physically attractive than the men with the low bank account balances.The results generally do not support the hypotheses.In Study 2, we replaced bank account balances with indirect indicators of wealth.Our results indicate that women were significantly less interested in wealthier men as compared to poorer men, possibly because the wealthy men may be perceived as bragging.Together, these studies suggest men's wealth may not be as important to women as has been previously considered, but further research is needed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".