Assortative match-making

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Be it math or match-making, I have ideas that I’d rather not explain since my rationale is usually a simple, non-foolproof and lazy way of doing things. Its some sort of an intuition that works for me, but might not for someone else as usually there’s no science to it and hence, I don’t both crystallising it into structured thoughts or sharing it with others. So, very often a question I’m asked is about why I make the matches I do and what is the rationale behind every match. I usually cover it up by saying it was a strong hunch that comes from experience, etc (which is true!) but the answer really is as trivial as assortative matching!

When people approach me (or not), I judge them. It is very essential to do so since it gives me a sense of who they are good (or good enough) for from the pool of people of the opposite gender I already have in my butti. The overarching metric of good for each other is driven by a combination of aspects like – general attitude, educational background, upbringing, family values, looks, general interests (or the lack of it as well), etc. Depending on how rational the person is, they either find my match on par/ below their aspirations. If I were to tell you that you’re no Angelina Jolie, but you’re still very much entitled to want a Brad Pitt but you don’t have to land one, you would not want me as your match-maker. So, let me try to rationalise this once and for all in a more palatable way.

There’s a popular algorithm known as the Gale Shapley’s algorithm that is popularly used in matching markets and is found to be very closely applicable even to online dating websites. In essence this algorithm states that if all parties in a matching market had a priority list of their preferred matches, then a stable match is possible within that market such that no one is cheating on the partners finally assigned to them through the matching algorithm. In the real world, making such priority lists is very costly. Firstly, you don’t have complete visibility of all users (of the opposite gender) at time zero and hence, you can’t possibly have your preference list ready. Secondly, it takes an incredibly long time to build a priority list since transaction cost is quite high.

Imagine you had a binder full of women, you’d pick your top 5 women and go down your order of preference one by one. Let’s say Woman No.4 is your ideal match at time zero but you wouldn’t know that till you came to Woman No.4. So, starting at Woman No.1, you put random whatsapp texting, maybe a meet or two, jataka matching and uppit kesaribath scenes (in random order depending on how orthodox your family is), only to get rejected by her. You end up repeating this process for Woman No.2 and 3 and finally arrive at Woman No.4. But thanks to the high transaction cost, Woman No.4 is probably gone or has just started the process unlike you and hence, puts reject on you since she’s still ambitious and so now you have no choice but to only pick from Woman No.5 and below. If you’re young, you are assured a fresh new pool of women and hence, there might be a greater chance of finding women who are far superior than the previous batch. But, very often, the pool only decreases with age. More so for women than men. If you don’t believe me, hopefully Christian Rudder’s Dataclysm could convince you better!

Recently, I made an assortative match and voila, the couple’s getting married later this year! When I got the details of the girl, I immediately knew a boy in my Marriage Broker Auntie database who’d be good enough (more like perfect, in this case!) for her and I didn’t waste a second trying to set them up. It took nearly 2 months to just organise the introductions (as both of them had been busy on Bharatmatrimony and what not) but since I had very strongly and explicitly anchored the match as being perfect (while essentially it was based on assortative matching), the 2 month transaction cost didn’t matter. This is a great anecdote to show that clearing house models take forever to find you matches unless you have a well-wishing judgemental broker auntie working exclusively for you. Ahem!

 

 

 

 

 

 

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