Estimated international population of gay men

I recently learned about the "fraternal birth order effect," where apparently for every older brother a man has, his probability of being gay as an adult increases. Here's a wikipedia entry.

Now, apparently there's some debate over how real or how strong this effect really is, so I'm almost certainly taking some numerical result a little too seriously. But, it occurred to me that data such as total fertility rate, and birth sex ratios are attainable international statistics. If this fraternal birth order effect is pretty strong and reliable, you should be able to estimate what percent of the male population of a country is gay.

So, I grabbed some data on international total fertility rate from here, and data on birth sex ratios here. Now, I have to make some assumptions. First, all of these calculations take the average total fertility rate as a country level descriptor, but there's almost certainly a unique probability distribution for different fertility rates for every country. Second, I have to treat the probability of having a male baby as being independent from the sex of the prior babies a woman has had. Third, and most importantly, I'm treating fraternal birth order as the only determinant of sexual orientation.

These are all pretty drastic assumptions. For instance, there's some evidence that my second assumption (birth sex of babies from the same mother are independent processes) is false. From the UN data I have, here's the total fertility rate of the country by the sex ratio:

This seems to suggest that as women have more babies, they're more likely to have girls. Note: I've left out data from four countries with highly skewed birth sex ratios, since these countries apparently have high rates of abortion of female fetuses.

So, I'm thinking about this as a very rough back of the envelope estimate, not to be taken too seriously, but maybe some sort of indicator of the shape of the world.

Here's the math:

• babies = 1, 2, ... total.fertility.rate
• boy.probability = male.ratio/2
• boy.babies = boy.probability^(babies)
• prob.gay.first.born = 0.12 (more on this below)
• prob.gay.n.born = prob.gay.n-1.born * 1.3 (from wikipedia)
• prob.gay = sum(prob.gay.1-to-n.born * boy.babies)

I hope that makes some sense. I grabbed 1.3 from wikipedia, which says "each older brother increases a man's odds of developing a homosexual orientation by 28–48%." I basically made up the probability that a first born son is gay. This was the one number that I couldn't seem to find, so I adjusted and played with it until the predicted percent of gay men in the United States was about 10%.

Here are my results for the top 10 countries for percent of gay men.

1. Afghanistan (19%)
2. Niger (18%)
3. Liberia (18%)
4. Mali (18%)
5. Nigeria (18%)
6. Burkina Faso (17%)
7. Guinea (17%)
8. Yemen (17%)
9. Iraq (17%)
10. Uganda (17%)

Unsurprisingly, the percent of gay men in a country is highly correlated with total fertility rate. I think this top 10 list highlights the importance of gay rights activism in Africa, especially in Uganda, which is considering making homosexuality a capital offense. 

And for the self obsessed, the United States looked like this:

• Smaller percent than 100 countries > tied with 17 countries > larger percent than 43.

Quantiative Reasoning Fail

Most of my research involves examining and reasoning about data. I'd say that in the course of my education as a linguist, I have developed some pretty ok quantitative and statistical reasoning skills. What's so great about having these reasoning skills is that they are very broadly applicable.

Occasionally, I'll observe, or hear second hand, someone with no quantitative reasoning skills discussing a topic that calls for them, and more often than not I'm blown away by the simple errors they make that lead to large confusions. For example, there was the time that George Will claimed that Obama is narcissistic because he used first person pronouns at a high rate.

"I," said the president, who is inordinately fond of the first-person singular pronoun, "want to disabuse people of this notion that somehow we enjoy meddling in the private sector."

Of course, George Will didn't exactly count how often Obama used the first person pronoun. And crucially, he didn't compare Obama's usage to any other president. Mark Liberman, calling himself "one of those narrow-minded fundamentalists who believe that statements can be true or false" counted and compared, and found that Obama's usage rate of first person pronouns was actually less than the previous two presidents, not that it even really means anything.

President	% of words which are first person pronouns
Obama	2.65%
Bush II	4.49%
Clinton	3.87%

More recently, you have Senator Jon Kyl stating on the Senate floor that over 90% of what Planned Parenthood does is abortions. Of course, when fact checked, it turned out that about what 3% of what planned parenthood does is abortions. Kyl's defense? "It was never intended as a factual statement." I think the Daily Show coverage says it best.

The Daily Show - Countdown to the Next Countdown - Jon Kyl's Planned Parenthood Statistics
Tags: Daily Show Full Episodes,Political Humor & Satire Blog,The Daily Show on Facebook

Now, in the next bit the Daily Show did, they called what Senator Kyl did "lying." I have a different take. Worse than lying, I think Senator Kyl has no notion that numbers mean anything. That "90%" is just an emphasis marker, like "so," or "extremely". Of course, this can't strictly be true, because there are some pretty important percentages that determine whether or not he keeps his job, and surely he attends to those.

The question remains, how can Jon Kyl or George Will think they can just say things without any regard to the actual facts of the world? I think the problem is not just isolated to these individuals, and the consequences are potentially severe.

Take the debate that was raging before the passage of healthcare reform. One topic that really caught my eye was rescission, which is when heath insurance companies drop individual's coverage. Insurance Company representatives testified that rescission is very rare, only effecting one half of one percent of customers.

And no one called them out on the uselessness of that number! 0.5% of all insurance customers is entirely uninformative! What really matters is what percent of people who file claims are dropped. And even then, what really matters is how often people who have really severe, and expensive illnesses get dropped. This blog post estimated that it was close to 50% of people who file large claims get their health insurance dropped.

And that's not rocket science! Yet, no one called these representatives out on the (probably intentional) uselessness of their data! I remember thinking to myself "What's wrong with all of you!?"

Here's what it comes down to. As I see it, if you don't understand data, then you don't understand the world, and you will make bad decisions, and be taken advantage of.

In conclusion, I think it would be a great idea to overhaul high school mathematics to make statistics the end game, instead of calculus, as proposed by Arthur Benjamin in this TED talk.

Intertwound

I recently had a conversation with someone who repeatedly used "intertwound" for the past participle of intertwine. If you Google intertwound, you only get about 160 hits. Admittedly, trying to figure out why a small (160 hits out of the whole internet? Maybe "infinitesimal" is a better word.) number of people do something out of the ordinary isn't necessarily interesting or fruitful. However, these hits all seem to be unreflecting attempts at forming the past participle of intertwine, and damnit, I'm intrigued.

At first I thought this was a natural enough reanalysis to make, thinking that twine formed its participle by changing the vowel from /ay/ to /aw/. BUT! As far as I can tell, all verbs which form their participle by changing /ay/ to /aw/ have the coda /aynd/ (wind, find, bind, grind). Twine ends in /ayn/.

So how did anyone come to reanalyze twine. There are a few possibilities. First, perhaps the /ay/ → /aw/ rule generalized to twine despite its not exactly having the right phonological shape. Second, it might be the case that some people have misanalysed this structure:

for this structure

That is, they've reanalyzed the final /d/ in intertwined as actually being part of the stem. This way, the stem actually does have the /aynd/ coda, making it natural to extend the /ay/ → /aw/ rule to it.

A third possibility, and the one that I think is closer to being the correct one, is that some people have reanalyzed the structure of intertwined as

There is definitely a similarity between the meaning of wind and intertwined, so it might not be the craziest thing to think that wind must be in intertwined somewhere. Of course, that means there's this -t- stuck in there which doesn't really mean anything at all.