https://en.wikipedia.org/wiki/Lattice_of_stable_matchings
The problem is it's a lattice and not fully ordered. There are cases where there are two or more pairings that are worse for women and better for men, but we cannot determine which pairing is superior to the other overall.
But this isn't raw Gale-Shapley-- the participants aren't ranking all hundreds/thousands of others. In particular, the preference matrix is based on identical mutual compatibility scores, so there's a unique stable solution (not multiple stable ones!), and there's no "side" that benefits, since the solution is identical no matter who does the "proposing".
For marrying: I suspect they are about as picky?
This is absolutely not an accidental phenomenon, this is the optimal outcome for dating apps, because that's the only way to prevent women from finding what they are looking for too quickly (and then leaving the app).
NO dating executive thinks like "women leaving too early because they found what they searched". This sentence does not exist in any of the teams.
Instead, they fear that women are leaving too early because of traffic they bought and that they have a bad experience and leaving, so they are no more a magnet to other males to swiper their credit card for a new subscription.
These are on platforms where you have profile pics and jobs, front and center on your profile, and the algorithm learns from your preferences based on that. The questions on this platform seem to suggest that the algorithm matches based on anything but that, so perhaps we have different, more open-minded outcomes on what a good partner for someone is like rather than who the ideal man/woman is like.
Is that modeling the problem correctly? It seems pretty rare for two partners to have equal amounts of love for each other.
If I have 10/10 love for Halle Berry, and she has 4/10 love for my Jeff-Bezos-looking ass, it's the 4/10 that's going to dictate whether we live happily ever after. So our mutual compatibility is probably well below 10/10.
There are far more people unhappily married with 4/10 attraction for each other because it is better being alone.
That's why it needs to be a stable matching instead of "high compatibility matching".
In the UK male plus joint is roughly the same as female.
You also need to take the reasons into account as well as why. There are multiple reasons for this. The better off partner has more to lose from divorce, women tend to get custody of children, they might have different feelings of obligation to keep a marriage going (I cannot extrapolate this to other men, but I felt an obligation not to file for divorce until I had exhausted all other possibilities), social pressures and responses are different, etc.
> When filtered to those with a college degree it's 90%
Interesting, but why? I suspect the answer is economics.
Or that out of all the initiators with college degrees, 90% are women?
does mutual divorce figure into this, and if so, how is one party be both parties having a college degree counted?
But I dunno. Divorce stats tend to be reported with less meaningful stats that are easy to calculate, but don't mean much.
You've never seen this discussed as a drawback? I've seen it mentioned quite a bit. For instance, it came up on the last big thread on this just the other day: https://news.ycombinator.com/item?id=49915825
“The active salesman got better sales than the person that just sat there and accepted offers? Outrageous!!!”
Here is why:
A dating sites primary KPI are mainly "new signups per day" and "subscriptions signed per day". For a lot of reasons listed above,dating sites in general _cant_ever_ work for the majority of people.(yes,there is this one neighbour who is happily married, they exist, sure, but this is not the majority)
Integrating something like Gale-Shapley would require your company to focus on othe matching part and integrate it somehow - but there is no reason for you to do so, because if you keep the primary KPI in the correct range, you are printing money, regardless if your matching algo is scientic sophisticated or not. So why bother?
Apart from that - also this algo cant check for chemical compatibility and friendship compatibility.
I've never heard this discussed or mentioned as a drawback because it's Nobel Prize winning and "stable" is a shorthand for "fair". Even though there's many unique stable matches that each offer participants different utilities even if individual participants don't have incentives to change their pairing.
In practice, the more powerful party seems to be the proposing side, e.g. hospitals are the "proposing side" when using Gale-Shapeley to match w/ med school students and get their ideal students.
I wonder if anyone who works on dating apps knows if men or women are the preferred side? And is there any research on stable matching that ensures equity (or ideally arbitrary distribution of utility) between the two groups in their stable matches?