Some highlights:
• What Liberaltarian Means To Me
• Where I Stand, Structurally
• Activism Theater
(Just in case people are stumbling onto my blog who don't know me.)
Tuesday, January 11, 2011
Recent Activity
Most of my writing lately has been going to Free Keene and Blue Hampshire and Will May's page.
Some highlights:
• What Liberaltarian Means To Me
• Where I Stand, Structurally
• Activism Theater
(Just in case people are stumbling onto my blog who don't know me.)
Some highlights:
• What Liberaltarian Means To Me
• Where I Stand, Structurally
• Activism Theater
(Just in case people are stumbling onto my blog who don't know me.)
Friday, December 10, 2010
My Favorite Social Science Books
If you want to understand how society works, these books are a good start. (I'll probably alter this from time to time.)
In order from extremely amazing to moderately amazing:
The Blank Slate -- Steven Pinker
Discusses the implications of modern psychology for the social sciences, with an illuminating focus on political issues.
Bowling Alone -- Robert Putnam
A look at the decline in community involvement over the past 50 years, drawing on many aspects of modern sociology.
Guns, Germs, and Steel -- Jared Diamond
A wide-ranging look at how environmental and demographic factors influenced human civilization.
Paul Krugman delivers the smackdown to dumb non-economists, and in the process provides the most entertaining presentation of economics since Frederic Bastiat's hilarious Economic Sophisms.
The Death and Life of Great American Cities -- Jane Jacobs
The Skeptical Environmentalist -- Bjørn Lomborg
The optimistic truth about the environment, resource scarcity, overpopulation, and world poverty.
How We Know What Isn't So -- Thomas Gilovich
The title says it all.
Why Societies Need Dissent -- Cass Sunstein
An entire book about how groups screw things up.
Hard Heads, Soft Hearts -- Alan Blinder
One of the very few popular macroeconomics books ever written. It can be hard to find macroeconomics interesting, so I recommend reading some other econ book (or two or three) before this one.
The Bottom Billion -- Paul Collier
In my opinion the best of the books on global poverty. He finds the common sense middle ground between leftist Jeffrey Sachs and libertarian William Easterly, and then he adds more common sense and a lot of practical political science.
Criterion used:
1) Must broadly agree with the academic literature. This rules out most everything written by John Kenneth Galbraith (if only he wasn't a crazy eccentric!) as well as Frederic Bastiat's Economic Sophisms (if only he had started writing after the labor theory of value was abandoned!).
2) Must cover a wide subject area. This rules out excellent books like Robert Axelrod's The Evolution of Cooperation and Andrew Gelman's Rich State, Poor State, Red State, Blue State.
3) Must be easily decipherable by an intelligent layman. This rules out John Zaller's The Nature and Origins of Mass Opinion and Tullock and Buchanan's The Calculus of Consent.
4) Must be well written. Nothing bothers me more than a sentence that should be simple but instead reads like a math equation. (Yes, I'm looking at you, Friedrich Hayek.) Nothing, that is, except writers who get sidetracked by dumb irrelevant ideological issues. (Strange example: Nicholas Christakis and James Fowler talking complete nonsense about superorganisms in Connected.)
Wednesday, November 10, 2010
Reverend Thomas Bayes vs. 9/11 Conspiracies, version 3
(with gratitude to William Zinsser) (but I still can't get this to work like I want!)
9/11 Truth debunkers usually concern themselves with the obvious point of contention: the evidence. Invariably, they get bogged down in never-ending debates about obscure details of materials science, physical chemistry, and the like. But this is unnecessary. These debates just don't matter— and we can prove it logically. The solution lies, instead, with an 18th century Presbyterian minister.
Thomas Bayes was born in 1702. In 1763, two years after his death, his famous theorem surfaced at the Royal Society of London. Here is one formulation:
This modest equation has earned Bayes immortality in the rationalist pantheon. It shows that, when evaluating a hypothesis, there's more to consider than just the evidence. Prior expectations also count.
As an example, let's suppose a man visits his doctor, suspecting he has a certain rare disease. Our hypothesis is that he has the disease. According to studies, only 1 in 10,001 people have it. The prior odds are therefore 1:10,000, which goes into our equation as 1/10,000.
The doctor then takes a blood sample and runs a test. The test is 99% accurate. It comes back positive, making the likelihood ratio 99. (Specifically, the likelihood ratio is the probability that the disease will cause the result — 99% — divided by the probability that a healthy person will cause the result — 1%.)
Now the man panics, but Thomas Bayes knew better. If we do the math to find the odds that the man has the disease, taking all data into account — if we multiply to find the the posterior odds — we get 99:10,000, or a slightly less than 1 in 100 chance that he has the disease:
In short, because the disease is so rare, he's 99 times more likely to be a healthy person with a false positive than someone with the disease. (There's an extensive introduction to Bayesian reasoning here, by Eliezer Yudkowsky, if this explanation is not doing the trick.)
On to the point: When thinking about 9/11 conspiracies, Bayes matters. This time let the hypothesis be that George Bush orchestrated 9/11. What are the prior odds (which exclude evidence collected after the event) that president Bush could have coordinated all of this? Given the complexity of the operation, it would have been very difficult. Dozens, if not hundreds, of top officials must have been involved, and all of them could have been treated like heroes if they had prevented it. How did he keep them from talking? How did he keep other people from noticing? The idea strains credulity. What about the angry Muslims hypothesis? After 50 years of malevolent U.S. intervention in the Middle East, it sounds plausible. Even more so after the U.S.S. Cole incident and other terrorist acts. Due to the extreme imbalance between the two options, the prior odds are very low. Since we need a number for the equation, let's go with 1:500 (if only to make the math easy).
What about the evidence collected after the disaster? It's plausible that it could have been caused by explosives. It's also plausible that 9/11 conspiracy theorists are not very good at forensics, and would make the same claims even if there were no explosives. So we can give the likelihood ratio a value of 1:1, which seems about right.
By choosing 1:1, we are saying that explosives and the official explanation are equally likely to cause our evidence. The man who panicked earlier would now panic again— there's a 50/50 chance that George Bush caused 9/11. But we know better. We need to account for our prior expectations. If we solve Bayes' equation — 1/500 × 1 = 1/500 — we find that it's still extremely unlikely that George Bush caused 9/11.
We can take this further. Our numbers so far have been based on crude guesswork. What if they were wrong? We can use more favorable numbers, and still we find that it's unlikely: 1/50 × 10 = 1/5. For an abstract equation based on so little data, Bayes' theorem provides us with surprisingly consistent answers.
In fact, given our earlier value of 1/500 for the prior odds, if we wanted to achieve merely 50/50 posterior odds that George Bush was responsible, the evidence collected after 9/11 would have to suggest a likelihood ratio of 500:1, meaning explosives were 500 times more likely to cause the evidence than planes alone. To get this number, we would have to find the detonator intact, and then get confessions from a dozen senior officials. And then find written instructions for the destruction of the twin towers in a drawer of the desk in the Oval Office.
The odds are against 9/11 Truthers.
9/11 Truth debunkers usually concern themselves with the obvious point of contention: the evidence. Invariably, they get bogged down in never-ending debates about obscure details of materials science, physical chemistry, and the like. But this is unnecessary. These debates just don't matter— and we can prove it logically. The solution lies, instead, with an 18th century Presbyterian minister.
Thomas Bayes was born in 1702. In 1763, two years after his death, his famous theorem surfaced at the Royal Society of London. Here is one formulation:
prior odds × likelihood ratio = posterior odds
This modest equation has earned Bayes immortality in the rationalist pantheon. It shows that, when evaluating a hypothesis, there's more to consider than just the evidence. Prior expectations also count.
As an example, let's suppose a man visits his doctor, suspecting he has a certain rare disease. Our hypothesis is that he has the disease. According to studies, only 1 in 10,001 people have it. The prior odds are therefore 1:10,000, which goes into our equation as 1/10,000.
The doctor then takes a blood sample and runs a test. The test is 99% accurate. It comes back positive, making the likelihood ratio 99. (Specifically, the likelihood ratio is the probability that the disease will cause the result — 99% — divided by the probability that a healthy person will cause the result — 1%.)
Now the man panics, but Thomas Bayes knew better. If we do the math to find the odds that the man has the disease, taking all data into account — if we multiply to find the the posterior odds — we get 99:10,000, or a slightly less than 1 in 100 chance that he has the disease:
1/10,000 × 99 = 99/10,000
In short, because the disease is so rare, he's 99 times more likely to be a healthy person with a false positive than someone with the disease. (There's an extensive introduction to Bayesian reasoning here, by Eliezer Yudkowsky, if this explanation is not doing the trick.)
On to the point: When thinking about 9/11 conspiracies, Bayes matters. This time let the hypothesis be that George Bush orchestrated 9/11. What are the prior odds (which exclude evidence collected after the event) that president Bush could have coordinated all of this? Given the complexity of the operation, it would have been very difficult. Dozens, if not hundreds, of top officials must have been involved, and all of them could have been treated like heroes if they had prevented it. How did he keep them from talking? How did he keep other people from noticing? The idea strains credulity. What about the angry Muslims hypothesis? After 50 years of malevolent U.S. intervention in the Middle East, it sounds plausible. Even more so after the U.S.S. Cole incident and other terrorist acts. Due to the extreme imbalance between the two options, the prior odds are very low. Since we need a number for the equation, let's go with 1:500 (if only to make the math easy).
What about the evidence collected after the disaster? It's plausible that it could have been caused by explosives. It's also plausible that 9/11 conspiracy theorists are not very good at forensics, and would make the same claims even if there were no explosives. So we can give the likelihood ratio a value of 1:1, which seems about right.
By choosing 1:1, we are saying that explosives and the official explanation are equally likely to cause our evidence. The man who panicked earlier would now panic again— there's a 50/50 chance that George Bush caused 9/11. But we know better. We need to account for our prior expectations. If we solve Bayes' equation — 1/500 × 1 = 1/500 — we find that it's still extremely unlikely that George Bush caused 9/11.
We can take this further. Our numbers so far have been based on crude guesswork. What if they were wrong? We can use more favorable numbers, and still we find that it's unlikely: 1/50 × 10 = 1/5. For an abstract equation based on so little data, Bayes' theorem provides us with surprisingly consistent answers.
In fact, given our earlier value of 1/500 for the prior odds, if we wanted to achieve merely 50/50 posterior odds that George Bush was responsible, the evidence collected after 9/11 would have to suggest a likelihood ratio of 500:1, meaning explosives were 500 times more likely to cause the evidence than planes alone. To get this number, we would have to find the detonator intact, and then get confessions from a dozen senior officials. And then find written instructions for the destruction of the twin towers in a drawer of the desk in the Oval Office.
The odds are against 9/11 Truthers.
Friday, October 29, 2010
Reverend Thomas Bayes vs. 9/11 Conspiracies, version 2
9/11 Truth debunkers usually concern themselves with the obvious point of contention: the evidence. Predictably, they get bogged down in mind-numbing details of materials science and physical chemistry. I take no such approach here. Instead I argue, paradoxically, that the evidence is irrelevant to this debate. The real key lies in an 18th century Presbyterian minister.
Thomas Bayes was born in 1702. In 1763, two years after his death, his famous theorem surfaced at the Royal Society of London. Here is one formulation:
This modest equation has earned Bayes immortality in the rationalist pantheon. In short, it shows that, when evaluating a hypothesis, there's more to consider than just the evidence. Prior expectations also count.
As an example, let's suppose a man visits his doctor, suspecting he has a certain rare disease. Our hypothesis is that he has the disease. According to studies, only 1 in 10,001 people have it. The prior odds are therefore 1:10,000, which goes into our equation as 1/10,000.
The doctor then takes a blood sample and runs a test. The test is 99% accurate. It comes back positive, making the likelihood ratio 99. (Specifically, the likelihood ratio is the probability that the disease will cause the result — 99% — divided by the probability that a healthy person will cause the result — 1%.)
At this point, the man panics. But Thomas Bayes knew better. If we do the math to find out the odds that the man has the disease, taking all the data into account — multiplying to find the the posterior odds — we get 99:10,000, or slightly less than a 1 in 100 chance that he has the disease:
Basically, because the disease is so rare, he's 99 times more likely to be a healthy person with a false positive than someone with the disease.
On to the point. When thinking about 9/11 conspiracies, Bayes matters. This time let the hypothesis be that George Bush orchestrated 9/11. What's the likelihood (ignoring the evidence collected after the fall of the twin towers) that president Bush could have coordinated all of this? Given the complexity of the operation, it would have been very difficult. There must have been dozens, if not hundreds, of top officials involved in this, all of whom had a good chance of being treated like heroes if they prevented it. How did he keep them from talking? How did he keep other people from noticing? The idea strains credulity. What about the angry Muslims hypothesis? After 50 years of malevolent U.S. intervention in the Middle East, it sounds pretty plausible. Even more so after the U.S.S. Cole incident and other terrorist acts. Due to the extreme imbalance between the two options, I give the prior odds a value of 1/500.
What about the evidence collected after the disaster? It's plausible that it could have been caused by explosives. It's also plausible (to me) that 9/11 conspiracy theorists are not very good at forensics, and simply read too much into the evidence. So I give the likelihood ratio a value of 1/1, or just 1.
Wow, that's unsettling! A 50/50 chance that the evidence was caused by explosives! Well, no, not really. If you do the math — 1/500 × 1 = 1/500 — you find that it's still extremely unlikely that George Bush caused 9/11.
Many 9/11 Truthers, like the panicked patient earlier, are looking at their data out of context, ignoring the extreme unlikelihood of their hypothesis in the first place.
Just for fun, let's take this a little further. Even given assumptions that are far too kind, it's still unlikely: 1/50 × 10 = 1/5.
In fact, given my value of 1/500 for the prior odds, if I wanted merely 50/50 posterior odds that George Bush was responsible, the evidence collected after 9/11 would have to suggest a likelihood ratio of 500 to 1 that explosives, not planes, destroyed the buildings. In order to get this number, we would basically have to find the detonator intact with George Bush's fingerprints on them. And then get confessions from a dozen senior officials. And then find written instructions for the destruction of the twin towers in a drawer of the desk in the Oval Office. It's silly.
And that's why I don't bother with this issue.
Thomas Bayes was born in 1702. In 1763, two years after his death, his famous theorem surfaced at the Royal Society of London. Here is one formulation:
prior odds × likelihood ratio = posterior odds
This modest equation has earned Bayes immortality in the rationalist pantheon. In short, it shows that, when evaluating a hypothesis, there's more to consider than just the evidence. Prior expectations also count.
As an example, let's suppose a man visits his doctor, suspecting he has a certain rare disease. Our hypothesis is that he has the disease. According to studies, only 1 in 10,001 people have it. The prior odds are therefore 1:10,000, which goes into our equation as 1/10,000.
The doctor then takes a blood sample and runs a test. The test is 99% accurate. It comes back positive, making the likelihood ratio 99. (Specifically, the likelihood ratio is the probability that the disease will cause the result — 99% — divided by the probability that a healthy person will cause the result — 1%.)
At this point, the man panics. But Thomas Bayes knew better. If we do the math to find out the odds that the man has the disease, taking all the data into account — multiplying to find the the posterior odds — we get 99:10,000, or slightly less than a 1 in 100 chance that he has the disease:
1/10,000 × 99 = 99/10,000
Basically, because the disease is so rare, he's 99 times more likely to be a healthy person with a false positive than someone with the disease.
On to the point. When thinking about 9/11 conspiracies, Bayes matters. This time let the hypothesis be that George Bush orchestrated 9/11. What's the likelihood (ignoring the evidence collected after the fall of the twin towers) that president Bush could have coordinated all of this? Given the complexity of the operation, it would have been very difficult. There must have been dozens, if not hundreds, of top officials involved in this, all of whom had a good chance of being treated like heroes if they prevented it. How did he keep them from talking? How did he keep other people from noticing? The idea strains credulity. What about the angry Muslims hypothesis? After 50 years of malevolent U.S. intervention in the Middle East, it sounds pretty plausible. Even more so after the U.S.S. Cole incident and other terrorist acts. Due to the extreme imbalance between the two options, I give the prior odds a value of 1/500.
What about the evidence collected after the disaster? It's plausible that it could have been caused by explosives. It's also plausible (to me) that 9/11 conspiracy theorists are not very good at forensics, and simply read too much into the evidence. So I give the likelihood ratio a value of 1/1, or just 1.
Wow, that's unsettling! A 50/50 chance that the evidence was caused by explosives! Well, no, not really. If you do the math — 1/500 × 1 = 1/500 — you find that it's still extremely unlikely that George Bush caused 9/11.
Many 9/11 Truthers, like the panicked patient earlier, are looking at their data out of context, ignoring the extreme unlikelihood of their hypothesis in the first place.
Just for fun, let's take this a little further. Even given assumptions that are far too kind, it's still unlikely: 1/50 × 10 = 1/5.
In fact, given my value of 1/500 for the prior odds, if I wanted merely 50/50 posterior odds that George Bush was responsible, the evidence collected after 9/11 would have to suggest a likelihood ratio of 500 to 1 that explosives, not planes, destroyed the buildings. In order to get this number, we would basically have to find the detonator intact with George Bush's fingerprints on them. And then get confessions from a dozen senior officials. And then find written instructions for the destruction of the twin towers in a drawer of the desk in the Oval Office. It's silly.
And that's why I don't bother with this issue.
Sunday, September 19, 2010
Reverend Thomas Bayes vs. 9/11 Conspiracies
The 9/11 Truth movement has come up a few times lately, so I thought I'd take the time to sketch out my reasoning for being so skeptical, as well as so apathetic about the evidence.
I cannot properly do this without using Bayes' theorem, so I need to explain that first. (Bayes' theorem is very useful, and I would recommend learning it even if you don't care about 9/11 conspiracies.)
In plain English, the theorem says you should take prior probabilities into account when judging how likely something is. Symbolically, it can be formulated like this:
I cannot properly do this without using Bayes' theorem, so I need to explain that first. (Bayes' theorem is very useful, and I would recommend learning it even if you don't care about 9/11 conspiracies.)
In plain English, the theorem says you should take prior probabilities into account when judging how likely something is. Symbolically, it can be formulated like this:
[ P(H) / P(~H) ] × [ P(D|H) / P(D|~H) ] = P(H|D) / P(~H|D)
This looks like a mess, but it's fairly simple once you know what the symbols mean.
I'm using "H" to stand for "hypothesis", and "D" for "data". P(H) is the probability that the hypothesis is true, to the best of our knowledge, before we examine the data. "~" means "not", so P(~H) is the probability that it is not true, as far as we can make out, before we look at the data.
This means the first third of the equation,
I'm using "H" to stand for "hypothesis", and "D" for "data". P(H) is the probability that the hypothesis is true, to the best of our knowledge, before we examine the data. "~" means "not", so P(~H) is the probability that it is not true, as far as we can make out, before we look at the data.
This means the first third of the equation,
[ P(H) / P(~H) ]
is the prior odds (not the probability, but the odds now) of the hypothesis being true. If we think, before looking at the data, that the odds are 50/50, then this part of the equation is 50/50 (or, after simplifying, just 1).
P(H|D) is the probability that the hypothesis is true, after taking into account the new data. P(~H|D) is, likewise, the probability that it is not true after accounting for the new data. Thus, the right side of the equation,
P(H|D) is the probability that the hypothesis is true, after taking into account the new data. P(~H|D) is, likewise, the probability that it is not true after accounting for the new data. Thus, the right side of the equation,
P(H|D) / P(~H|D)
is the posterior odds, the odds of the hypothesis being true after seeing the new data.
Lastly, in the middle, we have
Lastly, in the middle, we have
[ P(D|H) / P(D|~H) ]
P(D|H) is the probability that we would see the data we have if our hypothesis is true. P(D|~H) is the probability of seeing the same data if the hypothesis is false. Combined in this middle term, they are called the likelihood ratio.
We can now make the equation more manageable by substituting English:
Let me use an example. Let's suppose you went to a doctor, suspecting you had a certain disease. We'll say the hypothesis, H, is that you have the disease. According to studies, only 1 in 10,001 people have this disease. So the prior odds that you have it are 1/10,000.
The doctor then takes a blood sample and runs a test. The test is 99% accurate, making the likelihood ratio 99. It comes back positive.
This is really terrible news. Or is it?
If we do the math to find out the odds that you have the disease, taking all the data into account — solving for the posterior odds — we get 99 to 10,000, or slightly less than a 1 in 100 chance that you have the disease.
How did that happen? Basically, because the disease is so rare, you're 100 times more likely to be a healthy person who receives a false positive than to be someone who actually has the disease.
On to the point. When I think about 9/11 conspiracies, I think about them in Bayesian terms. This time let H be the hypothesis that George Bush orchestrated 9/11. What's the likelihood — ignoring the evidence collected after the fall of the twin towers — that president Bush could have coordinated all of this? Given the complexity of the operation, it would have been very difficult. Not to mention that there must have been dozens, if not hundreds, of top officials involved in this, all of whom had a good chance of being treated like heroes if they prevented it. How did he keep them from talking? How did he keep other people from noticing? The whole idea strains credulity. How about the angry Muslims hypothesis? After 50 years of malevolent U.S. intervention in the Middle East, it sounds pretty plausible. Even more so after the U.S.S. Cole incident. Because of the extreme imbalance between the two options, I'm giving the prior odds the value of 1/500.
What about the evidence collected after the disaster? I guess it's plausible it could have been caused by explosives. It's also plausible (to me) that 9/11 conspiracy theorists are not very good at forensics, and simply read too much into the evidence. So I'll give the likelihood ratio a value of 1/1, or just 1. Wow, that's a little unsettling, a 50/50 chance that the evidence was caused by explosives! Well, no, not really. If you do the math,
We can now make the equation more manageable by substituting English:
prior odds × likelihood ratio = posterior odds
Let me use an example. Let's suppose you went to a doctor, suspecting you had a certain disease. We'll say the hypothesis, H, is that you have the disease. According to studies, only 1 in 10,001 people have this disease. So the prior odds that you have it are 1/10,000.
The doctor then takes a blood sample and runs a test. The test is 99% accurate, making the likelihood ratio 99. It comes back positive.
This is really terrible news. Or is it?
If we do the math to find out the odds that you have the disease, taking all the data into account — solving for the posterior odds — we get 99 to 10,000, or slightly less than a 1 in 100 chance that you have the disease.
How did that happen? Basically, because the disease is so rare, you're 100 times more likely to be a healthy person who receives a false positive than to be someone who actually has the disease.
On to the point. When I think about 9/11 conspiracies, I think about them in Bayesian terms. This time let H be the hypothesis that George Bush orchestrated 9/11. What's the likelihood — ignoring the evidence collected after the fall of the twin towers — that president Bush could have coordinated all of this? Given the complexity of the operation, it would have been very difficult. Not to mention that there must have been dozens, if not hundreds, of top officials involved in this, all of whom had a good chance of being treated like heroes if they prevented it. How did he keep them from talking? How did he keep other people from noticing? The whole idea strains credulity. How about the angry Muslims hypothesis? After 50 years of malevolent U.S. intervention in the Middle East, it sounds pretty plausible. Even more so after the U.S.S. Cole incident. Because of the extreme imbalance between the two options, I'm giving the prior odds the value of 1/500.
What about the evidence collected after the disaster? I guess it's plausible it could have been caused by explosives. It's also plausible (to me) that 9/11 conspiracy theorists are not very good at forensics, and simply read too much into the evidence. So I'll give the likelihood ratio a value of 1/1, or just 1. Wow, that's a little unsettling, a 50/50 chance that the evidence was caused by explosives! Well, no, not really. If you do the math,
(1/500) × 1 = 1/500
you find that it's still extremely unlikely that George Bush caused 9/11.
Now, I get the impression that many 9/11 Truthers, like the patient who panicked earlier after getting positive results on his blood test, are looking at their data out of context, ignoring the extreme unlikelihood of their hypothesis in the first place.
Just for fun, let's take this a little further. Even if I give assumptions that are far too kind, it's still unlikely:
Now, I get the impression that many 9/11 Truthers, like the patient who panicked earlier after getting positive results on his blood test, are looking at their data out of context, ignoring the extreme unlikelihood of their hypothesis in the first place.
Just for fun, let's take this a little further. Even if I give assumptions that are far too kind, it's still unlikely:
(1/50) × 10 = 1/5
In fact, given my value of 1/500 for the prior odds, if I wanted merely 50/50 posterior odds that George Bush was responsible, the evidence collected after 9/11 would have to suggest a likelihood ratio of 500 to 1 that explosives, not planes, destroyed the buildings. In order to get this number, we would basically have to find the detonator intact with George Bush's fingerprints on them. And then get confessions from a dozen senior officials. And then find written instructions for the destruction of the twin towers in a drawer of the desk in the Oval Office. It's pretty silly.
And that's why I don't bother with this issue.
And that's why I don't bother with this issue.
Who Are The Real Democrats?
Here's a letter I recently wrote to the Sentinel:
Who's a "real" Democrat?
Who's a "real" Democrat?
There have a number of letters in the last month about libertarian Democrats, and how voters should “beware” of these candidates.
I am both amused and frustrated by these arguments.
The authors don’t seem to understand what the word “libertarian” actually means. Libertarians, for their information, want minimal government involvement in society. This means they generally oppose government intervention in the economy. They also oppose intervention in citizens’ private lives, as well as foreign wars of aggression.
If you’ll notice, this means that, though there may be times when they agree with conservatives, there are a considerable number of issues where libertarians naturally align with the left, including marijuana, gay rights, immigration, foreign policy, civil liberties, corporate welfare, and others. In fact, there are prominent libertarians, notably Will Wilkinson, arguing that libertarians should form a permanent alliance with liberals. This alliance has been branded “liberaltarianism,” and that’s exactly what some of us in Cheshire County have set out to do.
You would expect Democrats to be enthused by this influx of support. And, indeed, most have responded this way. Unfortunately, there are some who, due to narrow-minded ignorance and rampant fear-mongering, have decided that it’s their duty to oppose libertarianism in the Democratic Party. Apparently libertarians aren’t “real” Democrats.
Is that so? Well, let’s take a look at a few of these “real” Democrats. “Real” Democrat John Lynch vetoed medical marijuana and has pledged to oppose an income tax. (“Stealth” Democrat Andrew Carroll, on the other hand, supports medical marijuana and has refused to take the income tax pledge.) “Real” Democrat Bill Butynski opposes gay marriage and medical marijuana, and has been endorsed by Rep. Tim Butterworth. (“Stealth” Democrat Thom Simmons, however, supports gay marriage and medical marijuana, and has been endorsed by the Pink Pistols, a gay rights organization.)
If there is any systematic reasoning at all behind this categorization, I cannot see it.
I have therefore decided that I am not supporting real Democrats this year. Instead, I will support thoughtful and intelligent candidates who will vote with their consciences — candidates like Chuck Weed, Stephen Lindsey, Kris Roberts, Tim Robertson, Andrew Carroll and Thom Simmons.
WILL MAY
45 Elm St.
Keene
Wednesday, June 30, 2010
The Well Is (Probably) Resilient
Reckless civil disobedience is destroying the Free State Project. Free Staters are not served at restaurants, cannot get jobs, and are overwhelmingly held in contempt— all because aggressive civil disobedience ticks people off. The FSP is racing down a short path to irrelevance and failure.
Or so you would think, after hearing the rhetoric about "well-poisoning" from some political activists. To be fair, most of its advocates are not this extreme— and the person who did make these particular statements largely recanted. However, strong statements are being made, and they deserve a disinterested evaluation.
The basic story is this: The confrontational, unprofessional civil disobedience practiced by some Free Staters— particularly those in Keene— is upsetting people, and promoting a negative image of the FSP. You can tell it's upsetting people— just look at all of those rude comments on the newspaper articles! And you can tell it's promoting this image— just talk to local politicians!
The theory has a surface plausibility. But, as all libertarians should know, there are a lot of false theories with surface plausibility. We need to account for what is not seen as well.
As it turns out, upon closer inspection, the causal path from civil disobedience to well-poisoning is far from direct. First, a New Hampshirite has to actually notice the civil disobedience. Second, he has to react negatively to it. Third, he must alter his opinion of the FSP in response. And, finally, he must be spurred by this to actively oppose the goals of Free Staters.
Not only that, but aggressive civil disobedience can have positive effects as well, such as attracting more movers. If we define "poisoning the well" as "inhibiting the creation of a libertarian society", then it's not clear that the well is being poisoned at all. Perhaps the good from extra movers outweighs the bad from annoyed New Hampshirites.
1) So how many people hear about acts of civil disobedience? This is hard to say with the data we have. Those who read the newspaper, certainly, and those who are politically involved, certainly. But outside of this? Maybe those who spend time in or around Central Square. Most college students that I talk to seem blissfully unaware, suggesting that there are significant segments of the public who just don't notice.
2) How many of these people react negatively? The (non-Free Stater) comments on Keene Sentinel articles tend to be negative. However, this information will not help us measure general reactions until we understand the selection effects involved. (Are you more likely to respond to an article about an event that you disagree with? If so, how much more likely?) We know that certain people react in certain ways, but we can't estimate a percentage. And we know that a significant portion of the public responds positively. Nursing mothers, for example, seem generally supportive of Topless Tuesdays.
3) Out of those who react negatively, how many change their views of the FSP in response? This is also a tough question. Undoubtedly, some people do, judging by Keene Sentinel comments. Many, however, are deterred from this by non-disobedient FSP friends (and sometimes disobedient friends as well). I know for a fact that I have prevented multiple people from responding this way.
Other people don't even realize the FSP exists, or don't understand the relationship between the two. And, of course, a person can't change to a negative view of the FSP if he already has a negative view.
(Although, IMO, it's impossible to get an accurate estimate of this factor, we can predict trends. As more libertarians move, the likelihood of a person having an FSP friend increases, and the probability of him responding this way drops. Other things being equal, the FSP should suffer less fallout from each act of aggressive civil disobedience as more people move.)
4) Now, out of these people who are aware of the civil disobedience, react negatively to it, and decide they don't like the FSP, how many of them are able to wield political influence in a way that frustrates the goals of the FSP? As with the other questions, this is hard to answer. On the one hand, those that are aware of the civil disobedience, and know the FSP exists, are likely to be more politically active than the average New Hampshirite. On the other hand, it can be very difficult to discriminate between Free Staters and non-Free Staters. And because of the way Free Staters tend to work closely with other groups (at least in their political capacity), it would be difficult to target a serious attack on us.
And there's still the other side to account for. Aggressive civil disobedience can excite potential movers and encourage them to get up here (pronto!). Also, as in the nursing mothers above, people may respond positively and be led to promote FSP goals. It happens.
All of these intervening steps, and the complications involved, as well as the often-overlooked positive effects, lead to me to suspect that Keene-style civil disobedience does not add much poison to the well, and probably even has a positive effect, overall. However, I admit that there is enough uncertainty involved for civil disobedience to plausibly be anything from a significant obstruction to a wild boost for the FSP.
To those who are worried about this, what we need most is more info, and a more thoughtful approach. Should we pay for a poll, or try to organize some kind of informal polling? Given that there's a snowball's chance of Keene civil disobedience ending, can we reduce the negative impact by focusing on other links in the chain? For example, could we lower the negative reactions by offering to relocate protests, or by encouraging less offensive disobedience? Or weaken the link with the FSP by having the civilly disobedient emphasize the differences among FSP movers?
Research has shown that libertarians are, on average, the most intelligent of the major political groups. Selection biases in FSP recruitment magnify the difference. Let's use this advantage.
Addendum: Some people have interpreted this essay as giving license to all poorly-considered civil disobedience. That is not at all what I intended to do. My intention was to get some people who worry too much to worry a little less. It's an undeniable fact that much of the civil disobedience in Keene could be performed in a friendlier, more community-oriented manner, and it's a real loss when this doesn't happen. I certainly don't endorse that kind of thoughtlessness.
Or so you would think, after hearing the rhetoric about "well-poisoning" from some political activists. To be fair, most of its advocates are not this extreme— and the person who did make these particular statements largely recanted. However, strong statements are being made, and they deserve a disinterested evaluation.
The basic story is this: The confrontational, unprofessional civil disobedience practiced by some Free Staters— particularly those in Keene— is upsetting people, and promoting a negative image of the FSP. You can tell it's upsetting people— just look at all of those rude comments on the newspaper articles! And you can tell it's promoting this image— just talk to local politicians!
The theory has a surface plausibility. But, as all libertarians should know, there are a lot of false theories with surface plausibility. We need to account for what is not seen as well.
As it turns out, upon closer inspection, the causal path from civil disobedience to well-poisoning is far from direct. First, a New Hampshirite has to actually notice the civil disobedience. Second, he has to react negatively to it. Third, he must alter his opinion of the FSP in response. And, finally, he must be spurred by this to actively oppose the goals of Free Staters.
Not only that, but aggressive civil disobedience can have positive effects as well, such as attracting more movers. If we define "poisoning the well" as "inhibiting the creation of a libertarian society", then it's not clear that the well is being poisoned at all. Perhaps the good from extra movers outweighs the bad from annoyed New Hampshirites.
1) So how many people hear about acts of civil disobedience? This is hard to say with the data we have. Those who read the newspaper, certainly, and those who are politically involved, certainly. But outside of this? Maybe those who spend time in or around Central Square. Most college students that I talk to seem blissfully unaware, suggesting that there are significant segments of the public who just don't notice.
2) How many of these people react negatively? The (non-Free Stater) comments on Keene Sentinel articles tend to be negative. However, this information will not help us measure general reactions until we understand the selection effects involved. (Are you more likely to respond to an article about an event that you disagree with? If so, how much more likely?) We know that certain people react in certain ways, but we can't estimate a percentage. And we know that a significant portion of the public responds positively. Nursing mothers, for example, seem generally supportive of Topless Tuesdays.
3) Out of those who react negatively, how many change their views of the FSP in response? This is also a tough question. Undoubtedly, some people do, judging by Keene Sentinel comments. Many, however, are deterred from this by non-disobedient FSP friends (and sometimes disobedient friends as well). I know for a fact that I have prevented multiple people from responding this way.
Other people don't even realize the FSP exists, or don't understand the relationship between the two. And, of course, a person can't change to a negative view of the FSP if he already has a negative view.
(Although, IMO, it's impossible to get an accurate estimate of this factor, we can predict trends. As more libertarians move, the likelihood of a person having an FSP friend increases, and the probability of him responding this way drops. Other things being equal, the FSP should suffer less fallout from each act of aggressive civil disobedience as more people move.)
4) Now, out of these people who are aware of the civil disobedience, react negatively to it, and decide they don't like the FSP, how many of them are able to wield political influence in a way that frustrates the goals of the FSP? As with the other questions, this is hard to answer. On the one hand, those that are aware of the civil disobedience, and know the FSP exists, are likely to be more politically active than the average New Hampshirite. On the other hand, it can be very difficult to discriminate between Free Staters and non-Free Staters. And because of the way Free Staters tend to work closely with other groups (at least in their political capacity), it would be difficult to target a serious attack on us.
And there's still the other side to account for. Aggressive civil disobedience can excite potential movers and encourage them to get up here (pronto!). Also, as in the nursing mothers above, people may respond positively and be led to promote FSP goals. It happens.
All of these intervening steps, and the complications involved, as well as the often-overlooked positive effects, lead to me to suspect that Keene-style civil disobedience does not add much poison to the well, and probably even has a positive effect, overall. However, I admit that there is enough uncertainty involved for civil disobedience to plausibly be anything from a significant obstruction to a wild boost for the FSP.
To those who are worried about this, what we need most is more info, and a more thoughtful approach. Should we pay for a poll, or try to organize some kind of informal polling? Given that there's a snowball's chance of Keene civil disobedience ending, can we reduce the negative impact by focusing on other links in the chain? For example, could we lower the negative reactions by offering to relocate protests, or by encouraging less offensive disobedience? Or weaken the link with the FSP by having the civilly disobedient emphasize the differences among FSP movers?
Research has shown that libertarians are, on average, the most intelligent of the major political groups. Selection biases in FSP recruitment magnify the difference. Let's use this advantage.
Addendum: Some people have interpreted this essay as giving license to all poorly-considered civil disobedience. That is not at all what I intended to do. My intention was to get some people who worry too much to worry a little less. It's an undeniable fact that much of the civil disobedience in Keene could be performed in a friendlier, more community-oriented manner, and it's a real loss when this doesn't happen. I certainly don't endorse that kind of thoughtlessness.
Subscribe to:
Posts (Atom)
