Empirical Progress and Pseudoscience

This definition may be conceived as too strict. In Subsection 6.1.4., dealing with symmetric forms of theory comparison, we will define the notion of `almost more successful’. In a quantitative approach (see CHAPTER 12) the presented definition only represents a condition of adequacy, specifying a sufficient condition.Google Scholar

It will become clear in CHAPTER 9 and 10 that this definition of ‘more successful’, and hence what will be based on it in this chapter, is naive in at least two senses. In later chapters it will be called more specifically the `basic’ definition, to distinguish it from the `refined’ definition.Google Scholar

Note that,when applied to not yet falsified theories, it concerns one aspect of Popper’s idea of severe testing: severe testing as comparative testing.Google Scholar

However, we will see in CHAPTER 9 that the theory realist may even have good reasons to prefer a theory which is explanatory more successful, but instantially somewhat less successful. The reason is that the preferred theory may still be closer to the theoretical truth, in which case the other theory misses the extra counter-examples due to a lack of observational sensitivity.Google Scholar

Note that crucial experiments are a kind of symmetric comparative evaluation, designed to generate good reasons for asymmetric comparative evaluation. In a later subsection we will deal with them and show, in some detail, how they stimulate the application of RS.Google Scholar

Note that in the asymmetric approach an individual problem of one theory can only become a non-problem for the other. The possibilities of becoming a individual success or a neutral instance are not differentiated. The situation is, though technically somewhat different, essentially similar for the way general successes are treated in the asymmetric approach. In sum, the asymmetric approach is less differentiated than the two symmetric ones as far as neutral results are concerned.Google Scholar

It is clear what the differences are between the three resulting definitions of more success, the asymmetric one of subsection 6.1.1. and the symmetric micro and macro ones of the present subsection. It will depend largely on pragmatic considerations which one will be preferred in a specific case.Google Scholar

See Note 1 to CHAPTER 2 dealing with the role of aesthetic criteria as presented by McAllister (1996).Google Scholar

If one uses the quantitative evaluation matrix, the consequence is that simplicity only comes into play in the case of quantitatively equal success, where the latter possibility is just a matter of sheer accident.Google Scholar

It is plausible to distinguish some grades of testability. One might call a general testable conditional (GTC) directly testable,and a theory, merely, testable if it does not coincide with a GTC, but has GTC’s as (general) test implications. Note that this definition of testable theories comes close to imposing the FIT-ness condition of Simon and Groen (1973): finite (i.e., by a finite number of observations) and irrevocable testability.Google Scholar

A similar difference applies to Lakatos construal of `naive falsificationism’ and our explication of it.Google Scholar

This even suggests just an ordering of a theory in terms of the shells, the outer ones will be given up c.q. changed earlier than the inner ones (see Darden 1991).Google Scholar

Besides irresponsible dogmatism, pseudoscience frequently suffers from lack of reproducibility and from causal and statistical fallacies. As is clear from our exposition, testing a GTI of a theory will lead to a success of that theory only if the corresponding ITI’s can be reproduced. Causal fallacies arise from `similarity thinking’, i.e., taking similarities as proofs of causal relations, and from irresponsible ‘correlation thinking’, i.e., taking correlations as proofs of causal relations. Since similarities are neither necessary nor sufficient for causal relations, similarity — thinking can, at most, be of some heuristic value. Since correlations are not sufficient for causal relations, they can at most play the role of (quasi-)necessary conditions (not strict, in view of the possibility of counteracting forces). See (Thagard 1988) for causal fallacies deriving from similarity thinking. Moreover, as is well-known, there are lots of types of statistical fallacies.Google Scholar