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Does Scientific Realism Model Reality

On Scientific Realism

Des Pensable (copyright) 2011).

On Scientific Realism - an essay by Des

What is scientific realism? Should one be a scientific realist?

1. Introduction

Scientists must have absolute belief in science and the scientific method for it to have such a powerful influence over the world and society today. They must have truely believed in the results that they get from their experiments were true and valid and in no way effected by any supernatural effects. I have always believed that the world around me is real and not illusory. I have witnessed the miracles of science. So am I a scientific realist and should I suggest others believe in scientific realism?

Realism is the belief that reality exists independent of the observer (Wikipedia). Scientific realism is primarily about theories of the relationships among data obtained from physical measurements of objects and processes in the world. It is about how accurate they are and whether they truly and objectively represent an independent reality as it is. If theories are useful and valid they can be used to create new knowledge of the world which then might be useful for some purpose. If invalid they waste time, effort and resources and promote false belief.

Scientific method involves measurement of observable objects or processes. An observable object is one that can be directly perceived using our senses. These objects are measured in agreed physical units of measurement such as length, mass, volume etc. There is no dispute over these units of measurement. All observable objects and processes can be measured and their measurements agreed mutually by all.

Science theory also conceives of objects and processes that are outside the normal capability of our senses to perceive. These are named unobservable objects or processes. Examples of these are atoms, molecules, electrons, magnetic fields, radiation, gravity etc. Science realists form theories that describe these unobservable objects or processes and how they behave as if they are as real as observable objects or processes.

Since they can be described by the same physical units as an observable objects, an atom or molecule is considered as real as a tree by a scientist even though one might never be perceived directly. By extension, if an unobserved object or process can be given physical dimensions then it might be considered real.

It is mainly the nature and reality of the unobservable objects and processes which antirealists are apt to challenge. They would tend to argue that the theories that conceive of and describe these unobservable objects or processes can be faulty and consequently the unobserved object or process may not even exist. They quote cases or erroneous theories that were developed, widely believed and then later found to be false such as phlogiston and luminiferous ether.

2. Logical Positivism

The first fully cohesive philosophy of science in the twentieth century is considered to be logical positivism (reference) which in the context of science was trying to understand why empirical methodology had been so successful in transforming the world from a dark age where gods and superstition ruled to an enlightened age where superstition was banished and humanity has relied on its own senses to study and harness the natural laws of the world to work for its benefit. Logical positivism held that a sharp distinction can be drawn between observational terms and theoretical terms, the latter capable of semantic analysis in observational and logical terms. Logical positivism encountered difficulties with:
The verification theory of meaning ( Hempel,1950). Troubles with the analytic-synthetic distinction (Quine, 1950).
The theory ladenness of observation (Kuhn,1970 and Quine, 1960).
Difficulties moving from the observationality of terms to observationality of sentences (Putnam,1962). The vagueness of the observational-theoretical distinction (Maxwell, 1962).

3. Scientific Realism

Scientific realism superseded the Logical Positivism as it is more flexible, has less semantic problems and is generally more defensible against antirealist claims.

Scientific realism is defined in various ways but involves three basic positions, a set of claims about the features of an ideal scientific theory; the commitment that science will eventually produce theories very much like an ideal theory and that science has done pretty well thus far in some areas of science even though it may have a way to go in other areas.

It is important to realize that science is not homogeneous. A person might well be a scientific realist regarding some areas of sciences while not being a realist regarding others. For example, one might hold realist attitudes toward physics, chemistry and biology, but not toward pseudosciences such economics, psychology and sociology.

Main conjectures of Scientific Realism (Stanford and Wiki)

1. Metaphysical aspect – which holds that there exists a mind-independent reality. In scientific realism this reality is the material world.

This conjecture distinguishes scientific realism from idealism which denies the existence of an independent reality outside our minds and logical positivism which considers metaphysics as irrelevant, but also from internal realism (Putnam) , which defines reality as a function of human conceptualization of the world.

2. Semantic realism, which holds that science contains theories (propositions), that is statements capable of being true or false in the sense of correspondence to the reality to which they refer. The focus is on the theories about unobservable objects and processes rather than the observable.

This distinguishes scientific realism from an instrumentalism that regards statements about unobservable entities as useful fictions without propositional content.

3. Epistemic realism, which holds that it is possible to put forward theories (propositions) that are approximately true, that some theories (propositions) actually are approximately true, and that belief in their approximate truth can be justified. This applies primarily to theories and theoretical propositions about unobservable objects and processes.

This distinguishes scientific realism from a skepticism that affirms the first and second conjectures but denies that it is possible to acquire justified approximate knowledge of a mind-independent reality. On the other hand, the qualification "approximate" entails a dissociation from the naïve realist claim that reality is as it is perceived.

When combined, the metaphysical and semantic conjectures posit that an ideal scientific theory says definite things about genuinely existing objects and processes. The epistemic realism conjecture posits that we have reasons to believe that the things said about these objects and processes are true.

Typical Scientific Realism Claims

Owing to the wide variations in opinions on the nature of science's success in specific disciplines and the role of scientific realism in that success, a scientific realist might agree with some but perhaps not all of the following positions (Leplin, 1984).
• The best scientific theories are at least partially true.
• The best theories do not employ central terms that are non referring expressions.
• To say that a theory is approximately true is sufficient explanation of the degree of its predictive success.
• The approximate truth of a theory is the only explanation of its predictive success.
• Even if a theory employs expressions that do not have a reference, a scientific theory may be approximately true.
• Scientific theories are in a historical process of progress towards a true account of the physical world.
• Scientific theories make genuine, existential claims
• Theoretical claims of scientific theories should be read literally and are definitively either true or false.
• The degree of the predictive success of a theory is evidence of the referential success of its central terms.
• The goal of science is an account of the physical world that is literally true.

Regardless of the above claims scientific realism holds the view that science makes positive progress through scientific theories which usually get successively better and can therefore solve more problems. I suspect that there would be very few scientists that would disagree.

4. Arguments in Favor of Scientific Realism

The 'Miracles' argument Putnam (1975) argues that unless the theoretical entities employed by scientific theories actually existed and the theories themselves were at least approximately true, the evident success of science (in terms of its applications and predictions) would surely be a miracle.

Since it is unlikely that scientific processes use miracles to run the most likely explanation is the simplest and that is the scientific explanations are true. I believe that this is a very powerful argument which is somewhat difficult to refute as it seems intuitively valid.

Some authors contend that the miracle argument itself is an instance of fallacious reasoning called the base rate fallacy (Howson 2000, ch. 3). Consider the following. There is a test for a disease for which the rate of false negatives is zero, and the rate of false positives is one in ten (that is, disease-free individuals test positive 10% of the time).

If one tests positive, what are the chances that one has the disease? The probability is not 90%, for the actual probability depends on the base rate of the disease in the population (the proportion of people having it). The lower the incidence of the disease at large, the lower the probability that a positive result signals the presence of the disease. By analogy, using the success of a scientific theory as an indicator of its approximate truth is arguably, likewise, an instance of the base rate fallacy. The success of a theory does not by itself suggest that it is likely approximately true, and since there is no independent way of knowing the base rate of approximately true theories, the chances of it being approximately true cannot be assessed.

Others (Worrall, 2009) maintains that these contentions are ineffective against the miracle argument because they depend crucially on a misleading formalization of it in terms of probabilities.

I would tend to agree for the following reason. Most theories that are accepted are the surviving optimal theory which gives the best predictive success rate out of a series. Thus each in itself is an evolved theory that has different set of independent physical parameters to every other evolved theory. Each theory is then analogous to a different disease. The base rate argument would only be valid if all the theories were pertaining to the same phenomena and used the same variables ie they are all the same disease.

The Corroboration argument

One argument for realism in connection with unobservables described by scientific theories comes by way of “corroboration”. If an unobservable entity or property is putatively capable of being detected by means of a scientific instrument or experiment, then this could form the basis of a defeasible argument for realism regarding it.

If it is capable of being detected by two or more different means of detection that are distinct with respect to the apparatuses they employ and the causal mechanisms and processes they are described as exploiting in the course of detection—this may serve as the basis of a significantly enhanced argument for realism. This called consilient evidence ( Hacking, 1983, p. 201).

Corroboration not only occurs when a single investigator uses multiple methods to detect an unobservable but more importantly when multiple observers can detect the same unobservable.

Again I would argue this is intuitively a strong argument. It follows also that if that unobservable is further used to determine further results which are observable then the unobservable has an even higher chance of being real.

Selective Optimism or Skepticism arguments

The notion of selectivity can be used as a general strategy for maximizing the plausibility of scientific realism, particularly with respect to unobservables. Explanationism, entity realism, and structural realism are the most important variants of scientific realism to implement this strategy. (Miller, 1987)
Explanationists hold that a realist attitude can be justified in connection with unobservables described by our best theories precisely when appealing to those unobservables is indispensible or otherwise important to explaining why these theories are successful. (Psillos, 1999). This is similar to the argument used in the corroboration argument.

Entity realism is another version of realism that adopts the strategy of selectivity. Here the commitment is based on the putative ability to causally manipulate unobservable entities like electrons or gene sequences to a great degree. The greater the ability to exploit one's apparent causal knowledge of something so as to bring about outcomes, the greater the warrant for belief (Hacking 1982)

Structural realism is another view promoting selectivity, but in this case it is the natures of unobservable entities that are viewed skeptically, with realism reserved for the structure of the unobservable realm, as represented by certain relations described by our best theories. (Psillos, 1995).

I think that this approach is a lot weaker than the earlier arguments as its akin to cherry picking theories to fit the scientific realism model and as such is open to strong criticism.

5. Arguments against Scientific Realism

The Underdetermination of Theory by Data

Duhem (1954) noted that a hypothesis cannot be used to derive testable predictions in isolation; to derive predictions one also requires “auxiliary” assumptions, such as background theories, hypotheses about instruments and measurements, etc. If subsequent observation and experiment produces data that conflict with those predicted, one might think that this reflects badly on the hypothesis under test, but Duhem pointed out that given all of the assumptions required to derive predictions, it is no simple matter to identify where the error lies.

Basically this suggests that for every set of data there are conflicting theories that will completely explain the data. In theory this might be an arguable case where an hypothesis is created to explain or find a relationship within a set of data however in practice it is less likely as in reality scientific experiments are typically designed starting with an hypothesis. The data generated is then used to test the validity of the hypothesis.

In this way, control sets can be used to eliminate variability within experiments due to auxiliary assumptions and double blind studies can be used to eliminate observer bias within experiments where there is likely to be considerable variation from unknown sources as is often the case in biomedical studies such as the clinical effectiveness of drugs or medical procedures on people.

Skepticism about Inference to the Best Explanation.

Arguments for scientific realism often appeal to abductive reasoning or "inference to the best explanation". Scientific realists point to the success of scientific theories in predicting and explaining a variety of phenomena, and argue that from this we can infer that our scientific theories (or at least the best ones) provide true descriptions of the world, or approximately so.

In other words, ‘One infers, from the premise that a given hypothesis would provide a “better” explanation for the evidence than would any other hypothesis, to the conclusion that the given hypothesis is true’ (Harman 1965, p. 89).

The antirealist would argue that in order to judge that one hypothesis furnishes a better explanation of some phenomenon than another, one must employ some criterion or criteria on the basis of which the judgment is made. The realist can counter this by proposing criteria such as simplicity; consistency and coherence; scope and unity and so on. However, the antirealist then can then counter with the argument whether criteria such as these can be defined precisely enough to permit relative rankings as to whether one hypothesis is better than another.

Again from a practical point of view it is rare to have two competing hypotheses and having to make a decision as to which is more correct. It is more than likely in this case that an experiment could be structured to satisfy all contenders as to which of competing hypotheses are more correct or more accurate or whatever criteria are best to judge the optimal outcomes.

One argument that might be made under these circumstances is whether the experimenter is the best person to judge the outcome as they might be subject to bias for or against specific hypotheses . They might chose a favorite hypothesis for a variety of reasons that have nothing to do with the validity, efficiency or accuracy of the hypothesis.

There are two possible counters to this problem. The first is that any hypothesis or theory is going to be exhaustively examined by other scientists and if found to be suboptimal will be readily replaced by better hypotheses by the other scientists. This is how science works so efficiently. Theories evolve to best fit the niche in which they are used in an analogous way to organisms.

The second is that even if an hypothesis is not completely accurate or correct as long as it is better than any competing hypothesis then it may well have value in its own right. The expectation here is that at some later date the hypothesis will be replaced by one that is more efficient or accurate at predicting a better outcome.

Pessimistic Induction

This argument goes as follows. If one considers the history of scientific theories in any given discipline, what one typically finds is a regular turnover of older theories in favor of newer ones, as scientific knowledge develops. From the point of view of the present, most past theories must be considered false; indeed, this will be true from the point of view of most times. Therefore, by generalizing from these cases, theories at any given time will ultimately be replaced and regarded as false from some future perspective. Thus, current theories are also false.

In response to this argument I would argue that as theories mature they tend to last for longer periods and truth or falsity is dependent upon the time that the theory is current. As knowledge progresses truths can change and it is not valid to judge a theory on new knowledge but only upon the knowledge available at the time of its inception. It could also be argued that replaced theories are not false per se but less true than they were initially as the quality of the knowledge used to generate them improves.

Another response is to simply argue that there is no reason for pessimism as any theory that is replaced with a better one is reason for optimism that the system works.

Scepticism about the Approximate Truth.

The scientific realist argument that theories can be viewed as gradually converging on an ideal theory which represents the truth over time suggests that such progress might be assessed or measured in some way. It is important then for the realist to be able to suggest how this might be done to counter any antirealist argument that the concept of approximate truth is false.

There have been several attempts to create formal measurements of approximate truth. Popper (1972, pp. 231–236), defined relative orderings of ‘verisimilitude’ (literally, ‘likeness to truth’) between theories in a given domain over time by means of a comparison of their true and false consequences; the possible worlds approach according to which the truth conditions of a theory are identified with the set of possible worlds in which it is true, and ‘truth-likeness’ is calculated (Tichý 1976); and the type hierarchy approach, which analyzes truth-likeness in terms of similarity relationships between nodes in tree-structured graphs of types and subtypes representing scientific concepts on the one hand, and the entities, properties, and relations in the world they putatively represent on the other (Aronson 1990).

One of the less formal methods is that a theory may be considered more approximately true than one that preceded it if the earlier theory can be described as a “limiting case” of the later one. The idea of limiting cases and inter-theory relations more generally is elaborated by Post (1971).

6. Alternatives to Scientific Realism

Several alternatives to scientific realism have been developed over the last few decades including internal realism (Putnam, 1981), constructive empiricism (van Fraassen, 1980) and the natural ontological attitude, or NOA (Fine, 1986).

If we consider that realism seeks truth as a goal and when a realist accepts a theory it is accepted as true. In his internal realism, Putnam proposed a perspectival position in which truth is relative to language. He could then allow scientific claims to be true in their proper domain but deny that they tell the whole story, or even that there is a whole story to tell.

Constructive empiricism, by contrast, takes empirical adequacy (not truth) as the goal of science and when it accepts a theory it accepts it as empirically adequate.

Unlike the others, Fine's NOA is not a general interpretive scheme but simply an attitude that one can take to science. It is critically positive, looking carefully at particular scientific claims and procedures, and cautions us not to attach any general interpretive agenda to science. Thus NOA rejects positing goals for science as a whole, as realists and constructive empiricists do. NOA accepts 'truth' as a semantic primitive, but rejects any general theories or interpretations of scientific truth, including the perspectivalism built into internal realism and the external-world correspondence built into realism itself.

Social Constructivism

The term ‘social construction’ refers to any knowledge-generating process in which what counts as a fact is substantively determined by social factors, and in which different social factors would likely generate facts that are inconsistent with what is actually produced.

There are numerous ways in which social determinants may be consistent with realism; for example, social factors might determine the directions and methodologies of research permitted, encouraged, and funded, but this by itself need not undermine a realist attitude with respect to the outputs of scientific work.

Often, however, work takes the form of case studies that aim to demonstrate how particular decisions affecting scientific work were influenced by social factors which, had they been different, would have facilitated results that are inconsistent with those ultimately accepted as scientific fact.

By making social factors an inextricable, substantive determinant of what counts as true or false in the realm of the sciences, social constructivism stands opposed to the realist contention that theories can be understood as furnishing knowledge of a mind-independent world. Hence social constructivism is generally seen as antirealist.

Finally, should one be a scientific realist? As a witness and observer who has actively been involved in several fields of science I would definitely state that all of my experience would suggest that scientific realism gives the best account of the success of science to date.

Its metaphysical claim that that there exists a mind-independent reality which can be examined using scientific methodology opens up a universe of knowledge that might be obtained in the future.

Its semantic claims that it is possible to create theories about the world around us that are true and false give us confidence that we are in control of our future and not subject to the whims of the supernatural.

Its epistemological claims that we can create propositional theories that are give an truthful approximation of reality that can be considered to be valid gives us the ability to shape the world around us in our image not that of some supernatural entity.

With respect to the mature sciences such as chemistry, physics and biomedicine the answer would have to be yes. However, considering that the pseudoscinces of economics, psychology and sociology perhaps the answer is a more cautious maybe.

References

Aronson, J. L. (1990) ‘Verisimilitude and Type Hierarchies’, Philosophical Topics, 18: 5–28.

Duhem, P. M. M., 1954 (1906), The Aim and Structure of Physical Theory, P. P. Wiener (tr.), Princeton: Princeton University Press.

Fine, A. (1986) ‘Unnatural Attitudes: Realist and Antirealist Attachments to Science’, Mind, 95: 149–177.

Hacking, I.(1982) ‘Experimentation and Scientific Realism’, Philosophical Topics, 13: 71–87.

Hacking, I. (1983) Representing and Intervening, Cambridge: Cambridge University Press. Harman, G. (1965) ‘The Inference to the Best Explanation’,Philosophical Review, 74: 88–95.

Hempel, Carl. (1950). "Empiricist Criteria of Cognitive Significance" in Boyd, Richard et al. eds. (1990). The Philosophy of Science Cambridge: MIT Press..

Howson, C. (2000) Hume's Problem: Induction and the Justification of Belief, Oxford: Oxford University Press.

Kuhn, Thomas. (1970). The Structure of Scientific Revolutions, 2nd Edition Chicago: University of Chicago Press.

Leplin, J (1984), Scientific Realism, University of California Press, p. 1, ISBN 0-520-05155-6

Maxwell, Grover (1962). "The Ontological Status of Theoretical Entities" in Feigl and Maxwell Scientific Explanation, Space, and Time vol. 3, Minnesota Studies in the Philosophy of Science, 3-15.

Miller, R. W. (1987) Fact and Method: Explanation, Confirmation and Reality in the Natural and the Social Sciences, Princeton: Princeton University Press.

Popper, K. R. (1972) Conjectures and Refutations: The Growth of Knowledge, 4th edition. London: Routledge & Kegan Paul.

Post, H. R. (1971) ‘Correspondence, Invariance and Heuristics: In Praise of Conservative Induction’, Studies in History and Philosophy of Science, 2: 213–255.

Psillos, S. (1999) Scientific Realism: How Science Tracks Truth, London: Routledge.

Psillos, S. (1996) ‘On van Fraassen's Critique of Abductive Reasoning’, Philosophical Quarterly, 46: 31–47.

Putnam, H. (1975), Mathematics, Matter and Method, Cambridge: Cambridge University Press.

Putnam, Hilary. (1962). "What Theories are Not" in Ernst Nagel et al. (1962). Logic, Methodology, and Philosophy of Science Stanford University Press.

Putnam, H. (1981) Reason, Truth and History, Cambridge: Cambridge University Press. Quine, W.V.O. (1951). "Two Dogmas of Empiricism" in his (1953)[1]. From a Logical Point of View Cambridge: Harvard University Press.

Quine, W.V.O. (1960). Word and Object Cambridge: MIT Press.

Tichý, P. (1976) ‘Verisimilitude Redefined’, British Journal for the Philosophy of Science, 27: 25–42.

van Fraassen, B. C. (1980) The Scientific Image, Oxford: Oxford University Press.

Worrall, J., (1989), ‘Structural Realism: The Best of Both Worlds?’, Dialectica, 43: 99–124.

End

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