Tag: good friend

Moron Astrology

So this morning I was discussing my yesterday’s post on astrology and vector length with good friend and esteemed colleague Baada. Some interesting fundaes came out of it. Since Baada has given up blogging (and he’s newly married now so can’t expect him to blog) I’m presenting the stuff here.

So basically we believe that astrology started off as some kind of multinomial regression. Some of ancestors observed some people, and tried to predict their behaviour based on the position of their stars at the time of their birth. Maybe it started off as some arbit project. Maybe if blogs existed then, we could say that it started off as a funda session leading up to a blog post.

So a bunch of people a few millenia ago started off on this random project to predict behaviour based on position of stars at the time of people’s birth. They used a set of their friends as the calibration data, and used them to fix the parameters. Then they found a bunch of acquaintances who then became the test data. I’m sure that these guys managed to predict behaviour pretty well based on the stars – else the concept wouldn’t have caught on.

Actually it could have gone two ways – either it fit an extraordinary proportion of people in which case it would be successful; or it didn’t fit a large enough proportion of people in which case it would have died out. Our hunch is that there must have been several models of astrology, and that natural selection and success rates picked out one as the winner – none of the other models would have survived since they failed to predict as well on the initial data set.

So Indian astrology as we know it started off as a multinomial regression model and was the winner in a tournament of several such models, and has continued to flourish to this day. Some problem we find with the concept:

  • correlation-causation: what the initial multinomial regression found is that certain patterns in the position of stars at the time of one’s birth is heavily correlated with one’s behaviour. The mistake that the modelers and their patrons made was the common one of associating correlation with causation. They assumed that the position of stars at one’s birth CAUSED one’s behaviour. They probably didn’t do much of a rigorous analysis to test this out
  • re-calibration: another problem with the model is that it hasn’t been continuously recalibrated. We continue to use the same parameters as we did several millenia ago. Despite copious quantities of new data points being available, no one has bothered to re-calibrate the model. Times have changed and people have changed but the model hasn’t kept up with either. Now, I think the original information of the model has been lost so no one can recalibrate even if he/she chooses to

Coming back to my earlier post, one can also say that Western astrology is weaker than Indian astrology since the former uses a one-factor regression as against the multinomial regression used by the latter; hence the former is much weaker at predicting.

Arranged Scissors 1 – The Common Minimum Programme

Now that I’m in the arranged marriage market, I’ll probably do a series on that. I think there has been this book that some female has written about it, but I haven’t read it. I periodically plan to write about this market, and its quirks, comparing it to the “normal louvvu market”. I’ll try my best to keep the identities of those I’m interacting with in the market secret – if not for anything else, because there is a good chance that they might be reading this.

A lot of people shudder at the thought of arranged mariage. They think it’s some kind of a failure. They say that it is a compromise. Some of them enter the market only grudgingly. If not anything else, presence in the arranged marriage market is an admission of failure to find a long-term partner without bankers’ support. Some people tend to take that personally. They think that they are failures in life because they had to request their parents to find them a partner in life.

Two years back, my good friend L Balaji (no, not the cricketer) came up with the hypothesis of a “common minimum programme job”, borrowing the phrase that our politicians are most likely to use when they form a coalition government, which is getting increasingly common nowadays. He defines a CMP job as one which “clears all cutoffs, but doesn’t perform spectacularly according to any criterion”. A CMP job offers you decent pay, keeps you in a decent city, gives you a good work-life balance, decent colleagues, etc. But you cannot really expect to get too much kick out of the job. You may not love the job, but it offers you enough to not get pained.

I think the traditional problem with the arranged marriage market is that people assume that people are in the market to find CMP spouses. Someone who looks “decent enough”, is “smart enough”, is “nice enough”, etc. Traditionally it seems like the evaluation in the arranged marriage market is a series of tickoffs – looks good? check. Can talk grammatical English? Check. I good to talk to? Check. And so forth. So what one ends up with is someone who clears all criteria, and not necessarily someone spectacular. You basicallly try to find someone you can share a house with until you are sixty four, and little else. Even that one major cutoff, I think, sometimes is given short shrift.

This boiling down of the market to CMPNess is responsible for the “compromise” label that the arranged marriage market attracts. And amazingly, a lot of people (who are lucky enough to have found someone better than CMP in the market) start talking about how one needs “to adjust”, “to compromise” etc. Definitely not the kind of stuff that the young person fresh into the market would love to hear. In fact, I think these CMP people are what gives arranged marriage a bad name.

Thinking about it, I think the CMP nature of the market doesn’t have much to do with the people who ended up choosing CMPs, or who ended up as CMPs (note that one can be both). It has structural origins. The problem, I think, lies with the structure of the market, and that all the CMP people have simply adapted to this particular market structure.

When you don’t like a set of rules, there are two ways to deal with it, or maybe three (depending upon whether you count like a mathematician or like a social scientist). First is to adapt yourself to the rules, basically to compromise. Then, you can allow the rules to stay in place, and you can work around them. Find loopholes and exploit them. This is what lawyers excel at. The final option is to bend the rules.

In my next post on this topic, I will talk about the structure of the arranged marriage market, and try to explain why it differs from the normal blading model.