Exam essay: What is a theory?
January 4, 2009
In this essay, I describe what we mean when we talk about scientific theories.
Exam essay: What is a theory?
What is theory, how do we test theory, how do we prove (tentatively) that a theory is true, what are the different kinds of theory; compare and contrast the various styles of theories.
In this essay, I describe what we mean when we talk about scientific theories, I discuss how theories are made, and how they are tested, and what we mean when we say a theory is “true.” I describe a taxonomy of theories types, and give advantages and disadvantages of the different types.
A theory is a claim on the natural world which is supported by observational evidence. Scientific theories are testable statements, testable through observation and interaction with the world we all share. The National Academy of Sciences goes somewhat further and says that a theory is a claim about the world supported by observational evidence which is unlikely to be disproved by further evidence, and they give the theory of biological evolution and the germ theory of disease as examples. Theories make up the scientific body of knowledge, and serve one of four roles: they allow us to classify things in the world; they describe part of the world and allow us to make predictions about that part (correlation); they provide a sense of understanding about the world (causation); and possibly they allow us to control that part of the world (use our sense of understanding to change the world in a predictable way). Good theories are tentative, malleable and available to be falsified, and are parsimonious: given options to choose among several theories that explain the same observational evidence, we should prefer theories that describe the world in the simplest way (Occam’s razor). They are abstract (not tied to a particular time or place) and intersubjective (all scientists in a field agree on what they mean).
Reynolds describes three forms of theory: set of laws, axiomatic, and causal process. A law is a correlative relational statement between two variables in the world that is well supported by observational evidence to the point where it is accepted as “true” by the relevant field. A set of laws theory describes an area of the world via a set of independent laws. Set of laws theories can be used to explain and predict things (show correlation) but not give a sense of understanding (show causation) or control. The main problems with set of laws theories are that they can’t describe unobservable features of the world, and they suffer from a massive combinatorics problem when having to describe interrelationships among many variables. An axiomatic theory proposes a set of interrelated statements (axioms) which can be combined in prescribed ways (typically mathematical or logical) to generate other, derived statements called propositions. Support for any proposition or axiom gives support to the theory as a whole. The good thing about axiomatic vs set of laws is that we have to do less work to show improve support for the theory, and axiomatic theories can encompass unobservables. Axiomatic theories can be used to explain and predict, and possibly to give a sense of understanding and offer control, but the latter two are not necessary for axiomatic theories. Causal process theories are like axiomatic theories in that they consist of a set of interrelated statements, but they differ in that causal process theories must relate cause and effect in the observed variables and thus implicitly offer a sense of understanding and possibly control. Causal process theories have all the advantages of axiomatic theories, with the benefit of conferring a sense of understanding. A problem with causal process theories, especially in complex systems, is to know when you are “done” adding bits to your model of the process.
“Truth” in science is not the same as truth in philosophy or mathematics in that science is inherently fallabilistic. Fallabilism in science says that we understand that our current theories of the world only approximate what is really happening in the world, and that they can be wrong. We expect both to make new theories in the future which explain parts of the world as yet unexplained, and to improve existing theories to better explain the parts we think we have explained. Truth, in science, has to do with the interaction between empiricism (theories are claims about the world supported by observational evidence), intersubjectivity, organized skepticism in the scientific community (we do not trust things implicitly; rigorous testing of ideas is necessary before acceptance) and consensus (many scientists in a field accept that a theory does actually reflect what is happening in the world). There is also a disagreement in what scientists think science can show as true. The hard core empiricists believe that the best we can do is to show correlation (A happens when B happens), and that causation is not the goal of science. There are problems with this stance when we try to use scientific knowledge in arguments in which we want to make predictions, because without causation we can make odd statements which would appear to be acceptable, such as “the height of a person is determined by the length of their shadow.” Scientific naturalists believe that the role of science is, in fact, to establish causation, and therefore the best kind of “truth” is the one which most accurately explains why something happens (causation) not simply that something happens (correlation).
I’ve talked about testing theories, but have not explained what that means. Theories are abstract (not tied to a particular time or place), but the world is concrete (particular time and space) and we need to derive ways to make concrete statements about the world (observational evidence) that we can tie back to our theories. The linkage that does that is called an operational definition, and it describes the methods and procedures to generate those concrete statements, and are defined in such a way (intersubjectively) that any scientist can use them to generate the same kinds (equivalent) concrete statements.
Theories are claims about the world based on evidence from the world, I have said, but how are they created? Several methods have been proposed, and are accepted in varying degrees by scientists and philosophers of sciences. The Baconian method (research-then-theory) says that we observe the world, look for recurrent patterns in it, and turn those patterns into theories. There are problems with this approach: complex systems with many independent and dependent variables may require huge amounts of observations over great periods of time, and even so some aspects of those systems may not be discernable to us, because we don’t know what to look at in all the data. Reynolds and Robson propose a composite, iterative approach to theory building. This involves starting by observing and describing a new area of interest in the world, noting interesting features, composing a theory (not necessarily a set of laws) that explains those features that conforms to the qualities of good theories I discussed above, and then testing our theory back against the world. After initially investigating our area, we may start by proposing hypotheses about the area (testable statements that have not been shown to be “true” or false), generating operational definitions and testing the hypotheses repeatedly. If our hypotheses are continuously supported by observational, we can begin to have confidence that they may be “true” in a scientific sense (inductive reasoning), and we call them empirical generalizations. If enough people believe our results (intersubjectvity and organized skepticism), our hypthotheses may be accepted as a good theory.
