Last night I bought Christian Rudder’s Dataclysm: Who We Are (When We Think No One’s Looking) and started reading it. I’m now about 10% into the book, well past the Kindle sample (I bought the book in entirety after I’d finished the sample). I’m past the first couple of chapters and am now reading a chapter on the contributions of Twitter to linguistics.
Rudder is a co-founder and Chief Data Scientist at the matchmaking website OkCupid, and he draws upon some aggregate data that his website has collected to point out some rather interesting stuff about how people think, view themselves, and the kind of partners they are looking for. One very interesting piece of analysis (which includes a couple of brilliant graphs) shows the preference for the partner’s age among men and women of different ages. So far the book has been absolutely spectacular.
The part of the book that I’ve found most fascinating so far is the one on averages and variances. Rudder looks at the average ratings of a large number of women registered on OkCupid (as rated by men) and tries to correlate their ratings with their success on the site (measured in terms of the number of messages they have received from men on the site wanting to date them). Given the scale of the data that Rudder has access to (rather large), the results are rather stupendous.
What Rudder finds is that for a given level of average rating for a woman, the higher the variance in her rating, the more the number of messages she receives. There are some quirky statistics he quotes (a lot of which has been extracted in this post on Brain Pickings - it was after a friend sent me this post that I got interested and bought the book) which show that women who are consistently rated a 3 (on a scale of 1-5) by men are much less likely to get a message than someone who gets a mix of 1s and 5s.
From this Rudder concludes that negative ratings actually boost a woman’s chances of getting a date – the fact that a number of men have rated someone unattractive means that there is something about her that a lot of men don’t like. This implies that the “competition” for getting her is possibly low, and you might be able to get a “bargain” or an “arbitrage” if you are able to get her.
While this is a plausible and rather palatable thesis, I have an alternate explanation for the same data – I posit that low ratings don’t matter. Some people might have rated you lowly but they don’t matter since they aren’t interested in you. What matters simply is the number of high ratings that you get – people are always on the lookout for spectacular people to date, and by getting a number of 5s, you are showing that you are found rather attractive by a number of people. The ratings of 1 that you have received are an anomaly – messages of rejection from people who don’t want to date you, and all they do is to pull down your average. A better way of comparing women would be to throw away the bottom 20% of all ratings that a woman gets and then calculate the average – and a lot of 3s that Rudder has analysed in his book are likely to come out as something more than that.
Irrespective of the reason for the correlation of variance with attractiveness, though, what is undisputed is that people look for spectacular people to date. If you are a consistent three, irrespective of whether you go by Rudder’s thesis or mine, a large number of men are likely to rate you as being “unspectacular”. When given a choice between dating someone who is a “common minimum program” on most dimensions and someone who has a “spike” (as recruiting management consultants like to put it), you are likely to be more interested in the one that has the spike. What you consider to be a spike might be considered to be a trough by others, which probably leads to an average average rating (but high variance), but it is the spike that attracts you to her.
The problem with the arranged marriage market in India is that it is set up such that people show off their “average” side. As I had argued several years earlier (back when I was in the market), the Indian arranged marriage market is dominated by people who are themselves “common minimum programmes” and who are looking for “common minimum programmes” to marry. Thus, if you want to enter that market yourself, you try to mould yourself as yet another common minimum program and try to hide your spike rather than to enhance it (it is also a result of counterparties sharing notes in the arranged marriage market, something that doesn’t happen in the dating market. If you have a spike that one girl considers to be a trough, her folks are likely to tell people known to them about your trough (which is actually a spike), and that might pull down your average rating).
Most Indian parents bring up their kids to become good materials in the arranged marriage market, and since it is the unspectacular CMP that succeeds in that market, parents aspire to get their grown up kids to fit such moulds. Any possibly deviant behaviour is quickly dissed, non-standard careers are strongly discouraged, you are encouraged to dress unspectacularly and so on. Taking this together with Rudder’s thesis, what this means is that if you prime yourself for the arranged marriage market, you are losing out on the dating market!
What it takes to be a success in the arranged marriage market (solidity, unspectacularity, CMPness) are directly at odds to what it takes to succeed in the dating market (a spike, quirkiness, character) and so once you have decided to enter one market you automatically become a failure in the other. This thesis also explains why people who break up in their mid/late twenties and who consequently enter the arranged marriage market (possibly since it offers the quickest chance of a rebound) struggle significantly in that market – they have been primed for the dating market which makes them unhot in the arranged marriage market.
One “spike” that I consider to be a part of my character is this blog. Back in the Benjarong conference, I was given sage advice that I do not disclose this blog to prospective brides from the arranged marriage market, thanks to posts like this one and this one. Finally I ended up marrying someone who I met as a consequence of this blog (this post to be precise – she later told me) – who messaged me on Orkut saying she likes my blog, because of which we got talking and so forth. It was the spike – possibly considered abhorrent by many – that was responsible for my finding my wife!
So decide which market you actually want to be in before you prime yourself. “I’ll also casually look at the other market” is never likely to work.