hyksos » Tue Jan 10, 2017 4:55 pm wrote:
From the perspective of science as a tool for solving practical problems, wouldn't it be just as meaningful to say that there is a constant correlation between the presence of sodium cyclamate and cancer in laboratory mice?
The answer is no. We have way more than a mere statistical correlation. In lab science you have a control group kept under the same conditions. Or if you really want to drive the argument, you have 18 control groups and 6 mouse environments with the cyclamate. I would say you have confused science with journalism.
Does the concept of cause and effect allow the solving of practical problems that cannot be equally solved by just referring to constant correlations rather than cause and effect?
The solving of "practical problems" might involve Church going or community basketball... both outside of my realm of expertise.
An instrumentalist knows that at the stage of science in which numbers are being "written on paper" he has nothing (At that stage) other than correlations. That is not somehow washed away by ideology. The elevation of a theory from petty correlation to Strong Causation
comes with more tedium. Usually control groups, and often the ability of far-away labs to reproduce the same result.
I didn't say that there aren't other means to solve practical problems but that the view of instrumentalism in science is that science is not
about trying to find out what physical reality is but instead science is a tool used to address certain kinds of practical problems. How would you characterize scientific instrumentalism?
I get that "correlation does not (necessarily) imply causation" and that much diligent work must be done in many cases to establish what are spurious correlations rather than what are said to be causes. How do scientists go about separating spurious correlations from causes? They change the variables until there is, as much as they can determine, only one variable that consistently precedes the targeted type of event. For example:http://www.encyclopedia.com/humanities/ ... hy-science
The most reliable causal knowledge comes not from passive observations, but from controlled experimentation. In the medical sciences, the experiments often take the form of randomized clinical trials. Consider the claim that a particular drug causes lowered blood pressure. How might one test this claim? One possibility would be to make the drug available on the open market and observe hypertension patients who choose to take the drug and those who do not. There is a problem with this methodology. Suppose that the drug is expensive; one might expect that patients who buy the drug will be wealthier on average then those who do not. Wealthier patients might enjoy any number of other benefits—such as access to better healthcare generally, better diets, and so on—that influence whether or not they experience a reduction in hypertension. If one finds that patients who take the drug do in fact experience greater reduction in blood pressure levels than those who do not, it can still not be known whether this reduction is due to the drug or due to one of the other advantages associated with wealth. In a randomized trial, it is determined randomly which patients will receive the drug and which will be given a placebo instead. Randomization helps to ensure that treatment is not correlated with any other causes that might influence recovery.
Notice, though that what is being done is establishing that only one correlation is constant through all the changes in variables. That one constant correlation through changes in variables is what is then called a cause and effect relationship.
When I said "constant correlation" what I meant is a correlation that persists through all changes in variables. I did not mean to imply that spurious correlations are constant correlations. I probably should have clarified that. The notion of causation goes beyond merely positing a constant correlation that persists through changes in variables. The notion of causation contains the concept of "producing a change". It's not just that two types of events are constantly correlated and that persists through changes in variables but that one type of event produces another type of event.
To me the term "instrumentalism" when applied to science implies that science is only a tool to be used to achieve some goal (not give us a description of objective reality). I have taken it that the goal is to solve certain kinds of practical problems (like finding a medicine to alleviate symptoms of a particular disease). Given that understanding of what scientific instrumentalism is about, I don't see where there is practical benefit to saying one type of event "produces" another type of event over simply saying that there is a constant correlation the persists through changes in variables. Either way, it works - take the medicine and the symptoms are alleviated (given the right conditions).
Now if you have a different take on what scientific instrumentalism is about, then that may imply something different.