Thread: Politics: Liberal Arts vs. Quantitative

I've only been a member for a couple of days, but I get the feeling this particular area of the forum doesn't get much activity. Still, I thought I'd ask those of you who consider yourselves to be scholars of politics what you think about the increasing mathematization of political science.

The traditionalists favor a liberal arts approach, which generally falls into one of three camps: political thought, political theory, and political philosophy. This is more of a Straussian categorization, so there are probably other ways of dissecting the field; the point is, the liberal arts approach is non-quantitative.

The modernists favor a quantitative approach, which includes game theory, data collection, and regression models.

So, to those of you who study politics, do you tend to place one approach over the other? Or do you think the two are somehow mutually supportive? Do you think they're equally useful?

Originally Posted by Anakrino

I've only been a member for a couple of days, but I get the feeling this particular area of the forum doesn't get much activity. Still, I thought I'd ask those of you who consider yourselves to be scholars of politics what you think about the increasing mathematization of political science.

The traditionalists favor a liberal arts approach, which generally falls into one of three camps: political thought, political theory, and political philosophy. This is more of a Straussian categorization, so there are probably other ways of dissecting the field; the point is, the liberal arts approach is non-quantitative.

The modernists favor a quantitative approach, which includes game theory, data collection, and regression models.

So, to those of you who study politics, do you tend to place one approach over the other? Or do you think the two are somehow mutually supportive? Do you think they're equally useful?

The quantitative approach didn't exist when I was in school. It was a different era. What is a regression model?

When I was an undergraduate we never touched the stuff. The quantitative stuff, I mean. I didn’t even know that there was a quantitative method (beyond simple descriptive statistics, at least) for studying politics. As students we learned about politics simply by opening up and reading old texts, from Plato onward. These days political science students at research universities spend a good deal of time learning about data collection and processing. “Data” in politics can either be continuous, like values of income and time, or discrete, which are more arbitrary and categorical, like party affiliation, race, and level of agreement on an issue (e.g., strongly agree, weakly disagree, etc.). The new political science folks take these data and then process them using statistical software in an effort to determine correlations between a dependent variable and at least one (but almost always, several) independent variable.

A basic example of what occurs when someone builds a model goes like this. The political scientist asks a question like, “Is there a statistically significant correlation between race and party affiliation?” In this case, party affiliation would become a discrete dependent variable, which means assigning arbitrary values for the purpose of numerical categorization—so, e.g., 0 = Republican, 1 = Democrat, 2 = other. The main independent variable race could be a so-called dummy variable (e.g., 1 = black, 0 = all other races) or discrete (e.g., 0 = black, 1 = white, Hispanic = 2, etc.). The dependent variable is then “regressed” on the independent variable, as well as any control variables (because other factors besides race may be important), to search for significance. Typically, the output will not be a graphic, like a bar chart, but rather a table showing a list of standard error and coefficient numbers. These numbers are then measured against a pre-determined value to check for significance.

Granted, I’m glossing over a lot of information about things I know and things I don’t know; but in a very general sense this is what modern political scientists do. I uploaded an example of what you can expect to see in today’s academic journals. Here you’ll see a combination of formal theoretic modeling (the “sequential game” with branches) and a so-called probit model (the output tables).

Anyway, my apologies for posting such a tedious comment, but there you have it. Personally, I dislike the quantitative approach. I don’t view it as particularly useful to understanding politics as such. But many larger universities promote the approach because it’s useful in securing grants from the government.

Originally Posted by Anakrino

I've only been a member for a couple of days, but I get the feeling this particular area of the forum doesn't get much activity. Still, I thought I'd ask those of you who consider yourselves to be scholars of politics what you think about the increasing mathematization of political science.

The traditionalists favor a liberal arts approach, which generally falls into one of three camps: political thought, political theory, and political philosophy. This is more of a Straussian categorization, so there are probably other ways of dissecting the field; the point is, the liberal arts approach is non-quantitative.

The modernists favor a quantitative approach, which includes game theory, data collection, and regression models.

So, to those of you who study politics, do you tend to place one approach over the other? Or do you think the two are somehow mutually supportive? Do you think they're equally useful?

So basically there are two differnt types. One type focues on Statistics, and another on philosphy correct?

Originally Posted by Kranes56

So basically there are two differnt types. One type focues on Statistics, and another on philosphy correct?

Basically, though some scholars of the liberal arts tradition distinguish between the types of non-quantitative studies. Earlier I mentioned Strauss, who once pronounced that while all political philosophy is political thought, not all political thought is political philosophy. To the extent that a liberal arts approach adheres to the agenda of political philosophy, it finds itself further removed from the world of statistics.

My own view of the quantitatively model-based approach to politics is that it's glorified soothsaying. Most modern political scientists will quickly admit that statistical models are not meant to "prove" anything, nor are they intended to predict events with any guaranteed level of certainty. We then find ourselves asking the political scientist, "Well, then, what good is your work?" A frequent response is, "The output data help us better to understand such and such aspect [congressional voting, presidential speech making, etc.] of politics." But many of these aspects occupy that sphere of political inquiry accessible by common sense, prudence, and reason for ages; and if the models cannot guide us with certainty, it's not clear to me that they do much to support our traditionally non-quantitative methods.

I suppose that reply turned into a rant, but I think there's an answer in there.

Originally Posted by Anakrino

Basically, though some scholars of the liberal arts tradition distinguish between the types of non-quantitative studies. Earlier I mentioned Strauss, who once pronounced that while all political philosophy is political thought, not all political thought is political philosophy. To the extent that a liberal arts approach adheres to the agenda of political philosophy, it finds itself further removed from the world of statistics.

My own view of the quantitatively model-based approach to politics is that it's glorified soothsaying. Most modern political scientists will quickly admit that statistical models are not meant to "prove" anything, nor are they intended to predict events with any guaranteed level of certainty. We then find ourselves asking the political scientist, "Well, then, what good is your work?" A frequent response is, "The output data help us better to understand such and such aspect [congressional voting, presidential speech making, etc.] of politics." But many of these aspects occupy that sphere of political inquiry accessible by common sense, prudence, and reason for ages; and if the models cannot guide us with certainty, it's not clear to me that they do much to support our traditionally non-quantitative methods.

I suppose that reply turned into a rant, but I think there's an answer in there.

I guess you're correct in one sense or another. Though stastics are useful, they are only predications. I think Philosphy has more to deal with the roots of the probelm, and then by using statistics, you can prove your point.

Originally Posted by Kranes56

I think Philosphy has more to deal with the roots of the probelm...

It's this point in particular that I reinforce with my students. My typical spiel goes something like this: Quantitative political science can tell us whether Hitler's Nazi policies of genocide were more or less efficient, but it cannot tell us whether those policies were more or less good. Efficiency is more easily quantifiable because there is little dispute over how to recognize it; yet in the last 2,000 years of Western political philosophy, we have not been able to agree upon a single definition of ideas like justice and goodness. How do you quantify "justice"?

To me, it's those "roots of the problem" you mentioned that constitute the soul of politics.

The Quantitative Approach sounds like the elevation of technological process and procedure over ideological substance.

Originally Posted by Anakrino

It's this point in particular that I reinforce with my students. My typical spiel goes something like this: Quantitative political science can tell us whether Hitler's Nazi policies of genocide were more or less efficient, but it cannot tell us whether those policies were more or less good. Efficiency is more easily quantifiable because there is little dispute over how to recognize it; yet in the last 2,000 years of Western political philosophy, we have not been able to agree upon a single definition of ideas like justice and goodness. How do you quantify "justice"?

To me, it's those "roots of the problem" you mentioned that constitute the soul of politics.

Right, but I think that the Liberal way, gives you what you determine as justice, and quantive supports your point of view. For instance, let's say I like Ice cream. A stuipd example, but it'll work. I could say that Ice Cream is the best desert in the world. I can then support that through facts saying it was the most sold desert in the world.

Originally Posted by Albert Di Salvo

The Quantitative Approach sounds like the elevation of technological process and procedure over ideological substance.

This is a frequent complaint of those from the liberal arts schools. It's one reason, I think, that in an academic article containing quantitative methods you'll generally find (what I call) a lip-service section entitled "Theory." Most political statisticians are somewhat aware that every model needs at least some cerebral underpinnings in order to be plausible; however, it's notable that they title these sections "Theory" and not "Political Philosophy."

Kranes56, it's here where your comment comes somewhat into play. I understand this may seem semantic but the distinction between a theory and philosophy is that the former accepts a concept or policy without much, if any, cross-examination; while the latter, by classical definition, is more interested in uncovering the truth of a matter.

But now I worry that my bias against the quantitative approach is making me out to be a curmudgeon. So I'll say that I certainly see the attraction in temporarily abandoning the path of philosophy (the ethereal, the vague) for the practical world in which we all live. It's possible, I think, to do something like what you suggested, Kranes, which is to settle on at least one definition of, say, justice and then attempt to examine it within a quantitative framework.

I suppose my official stance is this: if we are to arrange a hierarchy of study within the field of politics, I would prefer that the quantitative approach be made subordinate to the philosophic approach. This order, however, is being reversed in many larger institutions, and I find that worrisome.