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Political Science and “The Scientific Method

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1 Political Science and “The Scientific Method
Normative and Empirical Studies in Comparative Politics

2 The goals of this section
Normative versus Empirical Analysis: you should be able to distinguish between the two and relate them to the discussion in the text of value-judgments versus empirical analysis. We will illustrate this distinction with the example of how to approach the relationship between inequality and democracy Second, you should become intimately familiar with what we call the “Scientific Method”. You should be able to take a position on the following question (which not all political scientists agree upon): where is the Science in Political Science?

3 1. Normative and Empirical Approaches

4 Normative Approaches:
Emphasize what ought to happen, what should be. This is very different from describing and analyzing what actually is, what already exists. They often include value judgments about optimal standards (norms, hence the phrase normative approaches) They are closely connected with political philosophy. Some of the greatest questions in politics can be traced back to the earliest Greek philosophers. For example, Plato asked the question: “What kind of rule is best? How can we prevent tyranny?”. Through the centuries, political philosophers continued to ask such questions; for example, Locke asked “Why do we need government?”, Montesquieu asked, “How can we prevent the usurpation of power?”, Madison asked, “What is there to prevent the corruption of politics?”. Normative approaches are really important; they are the basis or starting point for most questions in empirical political science (which we will look at in a moment). It is almost impossible to conduct a ‘scientific’ investigation of something to do with politics without having some sort of normative concern. Equally, every empirical study carries, for better or for worse, some sort of normative meaning.

5 Empirical Approaches However, as social scientists, we seek to discover, describe, and explain facts and factual relationships. This is the foundation of empirical analysis. Although we may have our own opinions about things, and indeed, we might wish to find out that certain things are true or false, we try and keep those opinions out of the process as much as humanly possible. Our goal is to behave much as natural scientists do when investigating such phenomena as gravity, osmosis, etc. Thus we try to make sure that our studies remain remain value-free, and that we eliminate biases wherever and whenever they occur. In this goal, we use the tools of science (hence the label the scientific method); concepts, models, and “the scientific method” to uncover such relationships. These distinctions can be illustrated with an example.

6 Inequality, Democracy, and Comparative Politics
2. An example Inequality, Democracy, and Comparative Politics

7 The Normative Perspective
Normative theorists (political philosophers) might approach the relationship between inequality and democracy by asking questions like the following (indeed, these are representative of questions that have been asked by some of the most prominent political theorists though the centuries): Is inequality desirable? How much inequality is desirable? What is too much inequality? Should all people be considered equal? Is it the role of government to guarantee equality? Note that there is no right or wrong answer to these questions; almost everybody might have a slightly different opinion about them, and we have no scientific basis on which to distinguish between the answers. The only way that we could evaluate the answers people give is by the quality of the argument (whether it is logically sound, whether any facts used are correct, etc.). But we can never say that one person is right and another wrong, save on the basis of our own (inherently biased) views.

8 The Empirical Perspective
Empirical political scientists, on the other hand, might ask rather different questions. Before we get to the questions themselves, however, there are two steps that we would need to go through. First, an empirical political scientist would begin by asking: How do we define inequality? (this is what we call “the working definition of the concept”) Next, we would ask: How do we measure inequality? (this is what we grandiosely label “the operationalization of the concept”) Then we can get on and do what most empiricists do, look for the causes and consequences of the concept under investigation, in this case inequality (these are what we call “the correlates of the concept”). So, we can begin to put this in the form of particular questions; compare them with the kind of questions that normative theorists ask, and you can instantly see the difference… let us look at some questions that empirical political scientists have investigated and their findings.

9 Empirical Questions and Findings
Here’s a question that is quite interesting, if we are interested in inequality: “are democracies more equal in terms of wealth distribution than other forms of government?” (Note that straight away we can see the overlap between normative and empirical political science. From a normative perspective, we would probably really like it if the answer is yes, that democracies are more equal in terms of wealth distribution than other kinds of political systems). In fact, the answer is: No, they are not! Our evidence has already been seen, in the previous section when we discussed the Gini Index: we know, for example, that democratization in Eastern Europe was accompanied by greater inequality. Note also that the finding has a “real world” policy relevance: As we were trying to help former communist countries make the transition to democracy, we had to contend with the thorny issue of how do democratizing regimes deal with the increase in new forms of inequality?

10 More Empirical Findings
Does democracy lead to economic development? Again, we would probably really like it if we could find evidence that creating democracy in a country is a predictor of future economic development. It would be nice to think that the solution to the economic woes of much of the under-developed world lies in democracy. Unfortunately, again the answer is a resounding: No Our evidence is drawn from books such as that edited by Adam Przeworski and his colleagues, Democracy and Development (2000). Again, there is a real-world policy relevance: Should development efforts and our aid money concentrate on democratization? The answer, devoid of any moral content, is, no. However, perhaps we might want to make the choice to foster democracy anyway, all the while knowing that it will not automatically guarantee better standards of living. This is a normative question, however.

11 More Empirical Findings
Here’s another question of great interest: does inequality produce instability? In other words, if societies experience higher levels of wealth inequality, are they more likely to become unstable? The answer, as we might suspect, is a definitive: Yes Our evidence is drawn from a plethora of studies such as: Huntington (1967), Bingham Powell (1982) (this was a synchronic comparison, meaning that he compared different countries at the same point in time, and found that those with higher levels of inequality had greater instability); Piven and Cloward (1979, 1997) (this was a diachronic comparison, meaning that they compared the same society over time, and found that when wealth distributions were more unequal, that society exhibited greater levels of instability) POLICY RELEVANCE: Should we be concerned about the increase in inequality in Western societies since the 1960’s? As we saw in the example of the Gini Index, inequality has risen in the United States since In fact, this is true of the majority of western democratic nations.

12 3. The Scientific Method

13 The “scientific method”
The first to use the scientific method were Hellenistic philosophers (most often cited is Aristotle, who we have already seen cited as one of the ‘fathers’ of comparative politics) The “scientific revolution” occurs in the 16th and 17th centuries, with developments in physics, astronomy, mathematics, and chemistry However, the “scientific method” as a means to thinking about societal progress was really brought to wider attention in the 17th and 18th centuries (The period that we call The Enlightenment) The core of the scientific method is provided by understanding different modes of reasoning (inductive versus deductive), hypothesis-testing, and identifying the causal mechanism.

14 Inductive versus Deductive Reasoning
Inductive reasoning Francis Bacon ( ) argued that a sufficiently large number of observations would lead to theories accounting for relationships observed. In other words, we begin our scientific inquiry by looking at events taking place or things occurring, and, on the basis of what we see, we begin to build some large-scale theory can adequately account for them. Bacon, by the way, invented the expression “Knowledge is power”. (More about Bacon can be found at: Deductive reasoning Rene Descartes ( ) argued that we can only account for observed phenomena, things we witness, on the basis of clear and distinct ideas. In other words, we can’t really understand what is important and what is not unless we have some prior theories about the way things work. (More about Descartes can be found at:

15 Hypothesis-Testing This was first articulated by Galileo through his study of falling bodies. Observing that heavy objects fall with increasing speed, he formulated the hypothesis that the speed attained is directly proportional to the distance traversed. Being unable to test this directly, he deduced from his hypothesis the conclusion that objects falling unequal distances require the same amount of elapsed time. This was a false conclusion, and hence, logically, the first hypothesis was false. Therefore Galileo framed a new hypothesis: that the speed attained is directly proportional to the time elapsed, not the distance traversed. From this he was able to infer that the distance traversed by a falling object is proportional to the square of the time elapsed, and this hypothesis he was able to verify experimentally by rolling balls down an inclined plane. In other words: we form a hypothesis (which can be thought of as an educated guess), and then our job as scientists is to devise a way that we can test it. If the hypothesis fails to pass muster, we form a new, better one. Eventually, we will be able to confirm the hypothesis and thus gain knowledge.

16 The Causal Mechanism Newton invented the study of calculus as a means of abstracting from reality; Newton is the first to rely upon mathematical models rather than observation. But Newton stressed the need, under such conditions, not just to infer causality but to observe it. In other words, it is not sufficient to observe a correlation between two things to suspect that one has caused the other; we should be able to observe or understand the process by which it occurs. If we can’t live up to this standard, then all we can say is that there is a correlation, but we do not know what is causing what.

17 Other requirements Essentially, we can say that the application of the scientific method makes three demands upon the social scientist: The first of them is empiricism, which we can summarize in the aphorism “what I observe is what exists”. Alternatives to this might include; emotive evidence (feelings), hearsay, testimonial, circumstantial, revelatory, spectral, or authoritative evidence. All have their place in human relations, but only empiricism is allowed as the basis on which we admit evidence into our scientific endeavors. Rationalism, which we can define as the practice of logical reasoning. It is possible to argue cases on other bases, yet as social scientists we stick to logical reasoning. A healthy skepticism. We never allow ourselves to be too gullible, or too fall too quickly into the trap of believing something to be true because we want it to be true. As social scientists, we continually question whether we have done as a good a job as possible of testing our hypotheses in a critical fashion (by that, we mean in such a way as to permit us to tell whether the hypothesis is a good one or not).

18 The Four Basic Steps of Scientific Research
Observation and description of a phenomenon or group of phenomena Formulation of an hypothesis to explain the phenomena Use of the hypothesis to predict the existence of other phenomena, or to predict quantitatively the results of new observations Performance of experimental tests of the predictions by several independent experimenters and properly performed experiments

19 Common Mistakes

20 Confusing the hypothesis for the explanation
When testing an hypothesis or a theory, the scientist may have a preference for one outcome or another, and it is important that this preference not bias the results or their interpretation. The most fundamental error is to mistake the hypothesis for an explanation of a phenomenon, without performing experimental tests. Sometimes "common sense" and "logic" tempt us into believing that no test is needed.

21 Experimenter Bias Another common mistake is to ignore or rule out data which do not support the hypothesis. Ideally, the experimenter is open to the possibility that the hypothesis is correct or incorrect. Sometimes, however, a scientist may have a strong belief that the hypothesis is true (or false), or feels internal or external pressure to get a specific result. In that case, there may be a psychological tendency to find "something wrong", such as systematic effects, with data which do not support the scientist's expectations, while data which do agree with those expectations may not be checked as carefully. The lesson is that all data must be handled in the same way.

22 Systematic Error Another common mistake arises from the failure to estimate quantitatively systematic errors (and all errors). There are many examples of discoveries which were missed by experimenters whose data contained a new phenomenon, but who explained it away as a systematic background. Conversely, there are many examples of alleged "new discoveries" which later proved to be due to systematic errors not accounted for by the "discoverers."

23 Components of the Scientific Method
A hypothesis is a limited statement regarding cause and effect in specific situations; it also refers to our state of knowledge before experimental work has been performed and perhaps even before new phenomena have been predicted. The word model is reserved for situations when it is known that the hypothesis has at least limited validity. A scientific theory or law represents an hypothesis, or a group of related hypotheses, which has been confirmed through repeated experimental tests. The dependent variable is the measure of the phenomenon that is trying to be explained Explanatory (independent) variables are the measures of the phenomena that may explain variation in the dependent variable Correlation is when two variables seem to move in relationship to each other (i.e. education and voter turnout) A heuristic is a rough guide, a “rule of thumb”

24 Limits to the Method in the Social Sciences
Many people question whether it is, in fact, appropriate to use the scientific method in the social sciences. They argue, quite correctly, that unlike natural scientists, we cannot control experiments in laboratories; after all, we tend to observe human behavior and that behavior is much more wilfull and unpredictable than that of atoms! In fact, social scientists use what Campbell (1962) called ‘quasi-experiments’. What he meant was that, while we cannot control human behavior in a laboratory setting (and even if we could, it would be highly unethical and undesirable!), we can use careful observation and statistics to approximate the conditions under which natural scientists work. For a social scientist, the modern laboratory is the computer! This gives us the following distinction; natural sciences are predominantly deterministic , meaning that we can definitively identify universal laws (e.g. the law of gravity), whereas the social sciences are predominantly probabilistic, meaning that we can only say that, all things being equal, certain relationships are true most of the time. Critics of the social sciences see this as the biggest flaw in what we do. Finally, in the social sciences we not only use numbers but we also use everyday observations in non-statistical form. This we call qualitative data, and it is different from the numbers used by most scientists, i.e. quantitative

25 Logical Fallacies Finally, you should read the text and make sure that you are familiar with the following flaws in logical reasoning: Ecological fallacy Tautologies Post hoc ergo propter hoc A fortiori False analogies False inferences Reductivism


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