Isn’t that like saying psychology is useless since humans have “free will”? It may not be perfectly predictive, but it’s still interesting and useful to know what the underlying math and incentives tend to.
In any case, if there are major exceptions that deviate form the mathematical political optima, I want to know why that is.
Isn’t that like saying psychology is useless since humans have “free will”?
The problem isn’t uselessness it’s that people think they understand more than they do and make a lot of silly mistakes because they are overconfident that their models matter.
In particular people it makes people underrate the value of the public debate and complex coalition building and focus to much on elections as if they are the only way that public policy get’s decided.
Whether or not humans have free will is also arguable.
I think plenty of people in political science departments misunderstand politics because they are in their ivory tower. On the other hand that doesn’t mean that everybody in political science doesn’t know what they are talking about.
“In particular people it makes people underrate the value of the public debate and complex coalition building and focus to[sic] much on elections as if they are the only way that public policy get’s[sic] decided.”
There’s a lot more to political science than non-causal models predicting elections. Coalition-building, to borrow your example, is a particularly rich topic of study.
There’s a lot more to political science than non-causal models predicting elections.
Here my core concern isn’t so much political science but people from a STEM mindset trying to understand politics and then focusing their energies on easily modeled processes and thereby misunderstand the complexity of politics.
Isn’t that like saying psychology is useless since humans have “free will”? It may not be perfectly predictive, but it’s still interesting and useful to know what the underlying math and incentives tend to.
In any case, if there are major exceptions that deviate form the mathematical political optima, I want to know why that is.
The problem isn’t uselessness it’s that people think they understand more than they do and make a lot of silly mistakes because they are overconfident that their models matter.
In particular people it makes people underrate the value of the public debate and complex coalition building and focus to much on elections as if they are the only way that public policy get’s decided.
Whether or not humans have free will is also arguable.
Is your disagreement with Capla’s interest in electoral dynamics, or with Political Science writ large?
I think plenty of people in political science departments misunderstand politics because they are in their ivory tower. On the other hand that doesn’t mean that everybody in political science doesn’t know what they are talking about.
“In particular people it makes people underrate the value of the public debate and complex coalition building and focus to[sic] much on elections as if they are the only way that public policy get’s[sic] decided.”
There’s a lot more to political science than non-causal models predicting elections. Coalition-building, to borrow your example, is a particularly rich topic of study.
Here my core concern isn’t so much political science but people from a STEM mindset trying to understand politics and then focusing their energies on easily modeled processes and thereby misunderstand the complexity of politics.
If you want to know more about my position see the discussion on http://lesswrong.com/lw/krp/three_methods_of_attaining_change/ .
Ah, the sweet smell of common ground! I definitely agree with this.
It’s in quotes for a reason.