Thread by @Brooks_Rob

How do gender inequality and within-sex inequalities influence the way people mate? And what are the consequences for politics and culture? Well, a few people asked for a thread on this after our recent @EvolHumBehav paper and my @CulturalEvolSoc talk today at #CESConf2022.

The @EvolHumBehav paper and all details on our simulation model is free to download (for the next 40 days) at authors.elsevier.com/a/1fja13tz48~w…

To begin, people weigh many traits when choosing a mate. While the traits women & men use (for heterosexual choice) are often similar (e.g. both sexes value kindness) they differ in average importance to the sexes. One difference is the emphasis on partner wealth and status.

Women's stronger preference for high wealth/status men (compared to men's preference) is known scientifically as 'Hypergyny' & colloquially as 'marrying up'. It can be strict (marrying down as taboo or source of shame) or a weaker bias.

If people choose mates based on wealth, then you'd expect economic conditions to affect mating. We modelled the effects of gender inequality (differences in average wealth between women and men) and wealth inequality within the sexes.

We modelled four different kinds of choice rules, each including some hypergyny. Results were similar, so results below are from pairing rule #1: women only pair with men of equal or greater wealth than themselves. (men only pair w women who will pair with them).

In each iteration, individuals encountered a random potential mate. If they satisfied the 'pairing rule', they paired (+ left the simulation). If not they entered the next iteration. After 100 iterations, we were interested in who was paired vs remained unpaired at the end.

Here's what happens after 1, 10 and 100 iterations. Red=women, blue=men. Solid= pairing success when men and women mean income is equal; dash= 1 SD gender gap M>W.

In words, wealthy men and poor women enjoy highest pairing success (most likely to meet a partner where Man$>Woman$). A modest gender gap softens things for poor men/rich women, compared with equality.

Big M-F gaps relieve the rather dire pairing success of poor men (red; + numbers indicate improvement in pairing success). Things don't change for top 50% of men who were already pairing. That advantage weakens (blue, -ve) when women out-earn men.

Gender inequality also improves the pairing success of wealthy women. And F>M inequality weakens the advantage of poorer women.

Wealth inequality (among men + among women) reduces pairing success of below-average wealth men and above-average wealth women.

Summary so far:
-Hypergyny lowers pairing success of poorer men and richer women.
- Gender gaps (M>F) alleviate these effects
- Income inequality reduces success of below-average $ men and above average $ women.

Might these effects influence attitudes toward gender/wealth inequality? YES! (at least in men). One e.g.: Our work shows #Incels (men angry at lack of mating success) are more common in places of gender equality and, especially, high income inequality. journals.sagepub.com/doi/abs/10.117…

It gets even more interesting (I reckon) if you vary only the inequality within one sex ... in this case among men. Again, you see that dip in mating success for below average men (red arrow, left panel). BUT...

You see a narrow sliver of average $ men who do better. The transition from those men worst-served and those best-served by male inequality is abrupt. No longer a conflict between wealthiest and poorest.

And women's response to male inequality is quite different from when m&f inequality is the same. Wealthiest women do *better* when inequality among men is high. Makes sense if the tail of the male $ distribution extends beyond that for female.

There's a similar kind of effect if m-inequality stays constant and f-ineq. varies. Again the near neighbours (right panel) between the women who benefit most and suffer most from high inequality.

Overall then, I found this exercise useful for exposing some of the complex conflicting interests -between & within sex - associated with mating. Some are obvious, some unexpected.

Models like these can help predict who will oppose/favour changes to resource distribution like moves toward gender equity, redistribution of wealth etc.

They can also help predict attitudes to hypergyny, marriage, monogamy norms, & even the value of papers about hypergyny.

Again - the paper is free to download over the next few weeks. authors.elsevier.com/a/1fja13tz48~w…