Can Anything Be Said To Objectively Count As An Explaination Of An Event?

Student No. 11722219

Can Anything Be Said To Objectively Count As An Explanation Of An Event?

In this essay, I will first outline the criteria of a good scientific explanation as suggested

by Carl G. Hemple. I will then examine the two forms explanation which Hemple posits to fulfill these criteria. Proceeding, I will explore three cases which have been brought about as criticisms of Hemple‟s explanatory forms, but I explain why – despite these criticisms – Hemple‟s explanatory forms still hold true to his own criteria of a good scientific explanation. Finally, I will argue that each of us must make a personal judgment of validity in order to accept any given explanation, that all of the disagreements with regard to this issue arise simply due to the contrasting points at which individuals are satisfied to make such a judgment, and that as such there is no such thing as an explanation of an event which objectively counts as an explanation of an event – what counts as an explanation is a purely subjective judgement.

In the introduction to his essay entitled “Two Basic Types of Scientific Explanation”, Carl G. Hemple makes some simple assertions regarding the fundamental motivations which drive men to engage in all scientific research. Hemple claims there are two basic motivations at work. The first is suggested to be a desire to improve one‟s “strategic position in the world by means of dependable methods for predicting and, whenever possible, controlling the events that occur in it” (Hemple, 1998). The second, Hemple claims, is man‟s innate curiosity and desire “to know the world he lives in” (Hemple, 1998). It is questionable whether these motivations are really distinct from one another, as it is difficult to see how one could claim to have a dependable method of predicting or

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Student No. 11722219 controlling events in the world without claiming to know something about the world. But, pedanticism aside, if we take these motivations as whole to be the driving-force behind all of our scientific enquiries, we are left in a position to make a tentative claim about what a good scientific explanation should seek to do – A scientific explanation, it seems, should incorporate some knowledge about the world and structure said knowledge in such a way so as to bring about a dependable method of predicting and/or controlling events which relate to it. This sort of scientific explanation, Hemple explains, can take two different forms.

The first form of scientific explanation posited by Hemple is what he calls a “DeductiveNomological Explanation” (Hemple, 1998). Using an example from How We Think by John Dewey (1910), Hemple illustrates how this sort of explanation works. While washing some tumblers, Dewey observed that soap-bubbles expanded out from beneath a tumbler‟s rim and then slowly retreated back inside the rim each and every time a newlywashed tumbler was placed down on a plate to dry (Dewey, 1910). The explanation Dewey drew for this observed phenomenon went as follows: The heat from the hot water is partially transferred into the glass in each tumbler, the hot glass warms the air inside it when the tumbler is placed upside-down and this is coincides with an increase in the air‟s pressure, the increase in pressure leads to an expansion of the film of soap lying between the rim of the tumbler and the plate beneath it (creating the bubbles). Then, slowly the glass cools, along with the air inside it, and the soap bubbles gradually retreat back inside the tumbler accordingly. As such, Hemple suggests that this explanation can be regarded “as an argument to the effect that the event to be explained (or explanandum) was to be

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Student No. 11722219 expected by reason of certain explanatory facts” (Hemple, 1998). These explanatory facts are divided into two different groups – “particular facts and uniformities expressed by general laws” (Hemple, 1998). The particular facts are those which are simply observed as the component facts which make up the particular event in question. In the Dewey case, these particular facts include: the tumblers were immersed in soapy water, the soapy water was hotter than the air which surrounded it, the tumblers were turned upside-down and placed on a plate, a film of soap formed between the plate and the rim of the tumbler et cetera. What is meant by “uniformities expressed by general laws” is self-explanatory, and examples of these implicitly present in the explanation of the Dewey case include those laws “concerning the exchange of heat between bodies of different temperature, the elastic behaviour of soap bubbles, et cetera” (Hemple, 1998). Jointly, these particular and uniform explanatory facts become the explanans, which allow us to deduce the explanandum. In other words, if we take the uniform general laws and apply them to the particular facts of the case – we can deduce/predict/explain the explanandum. Thus, this form of explanation appears to fulfil the previously-outlined criteria for a good scientific explanation – it incorporates knowledge about the world (in the form of general laws and particular, empirically observed, facts) and enables us to make a reasonable prediction about the outcome of the event which relates to this knowledge. Thus, the prediction will be dependable provided the knowledge and laws upon which it is based are themselves dependable.

The second form of scientific explanation, according to Hemple, is an “inductive statistical explanation” (Hemple, 1998). Again, this form of explanation is nomological –

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Student No. 11722219 “it accounts for a given phenomenon by reference to general laws or theoretical principles” (Hemple, 1998). However, this time the laws/principles being referred to are of a probabilistic or statistical nature. In other words, they are assertions that if certain, specific, conditions are actualised – then there is a certain, specific, statistical probability that these conditions will lead to a particular result. Hemple uses the example of a case of hay-fever to explain how this type of explanation is employed. If a man were to experience an episode of hay-fever and the episode subsided after he took the recommended dose of an anti-hay-fever drug, we could not simply connect the explanans to the explanandum in a deductive manner – because there is no general law which states that the recommended dose of the drug will “invariably terminate a hay fever attack” (Hemple, 1998). With the lack of a finite law which can be applied here, all that can be asserted is a generalisation that there is a high statistical probability of hay-fever subsidence after administration of the recommended dose of the anti-hay-fever drug in question. As such, this form of explanation is similar in structure to that of deductive nomological explanation in that it takes particular facts together with general laws – only this time they are probabilistic laws – and uses them as the explanans. The difference lies in the fact that these explanans do not deductively imply the explanandum “John Doe‟s hay fever attack subsided” (Hemple, 1998), but rather the likelihood posited by the probabilistic law involved in the explanans can be “characterized as the strength of the inductive support, or the degree of rational credibility, which the explanans confers upon the explanandum” (Hemple, 1998). Thus, Hemple claims that this “explains a given phenomenon by showing that, in view of certain particular events and certain statistical laws, its occurrence was to be expected with high logical, or inductive, probability”

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Student No. 11722219 (Hemple, 1998). Again, this form of explanation appears to fulfil our criteria for a good scientific explanation – it incorporates knowledge about the world (in the form of particular facts and generalised, probabilistic, laws) and enables us to make a reasonable prediction about the outcome of the event which relates to this knowledge. This time, the dependability of the prediction is directly related to the truth/reliability of the probabilistic law upon which it is based (and, of course, the dependability of the percieved particular facts), or as Wesley Salmon puts it: “the event to be explained has high inductive probability relative to the explanatory facts” (Salmon, 2006).

One criticism raised against Hemple‟s nomological methods of explanation is brought about by Ardon Lyon, who criticises Hemple for crediting irrelevant premises with explaining explanandi. The example Lyon uses to illustrate this point, as summarised by Ruben (1998), is as follows:-

1. All metals conduct electricity.

2. Whatever conducts electricity is subject to gravitational attraction.

C. All metals are subject to gravitational attraction.

Lyon points out that “metals are not subject to gravitational attraction because they conduct electricity” (Lyon, 1974), and as such he suggests that the premises in this case are irrelevant to, and do not explain, the conclusion. However, if the premises are taken to be true, one cannot deny the logical validity of the conclusion. Therefore, if one were to possess knowledge of the two premises, then they certainly could take them to explain

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Student No. 11722219 the conclusion – Their knowledge that metals conduct electricity and their knowledge that whatever conducts electricity is subject to gravitational attraction would allow them to dependably predict that metals conduct electricity. If the knowledge is sound, then the explanandum will also be sound. Of course, the individual in question would not possess a wholesome or ultimate understanding of why metals are subject to gravitational attraction because the specific underlying mechanisms which render metals subject to gravitational attraction are not themselves contained within their explanation. However, despite not being The Explanation, their explanation remains an explanation which fulfils the necessary criteria posited by Hemple (although this time there is no need for particular facts as the example is entirely law-based).

Ruben (1998) raises a further objection to Hemple‟s methods of explanation in claiming that they permit cases in which some of “the explanans can be explained by the explanandum, as well as explain it” (Ruben, 1998). One of the example used is that of Ohm‟s law:-

Electric Current = Voltage/Resistance

In this case, if one possessed knowledge of any two of the variables and subsequently applied Ohm‟s law, they could predict the third variable (i.e. they could explain the third variable with reference to particular knowledge of the other two variables and the general knowledge of Ohm‟s law). Ruben wants to suggest that this is a problem because since all three variables are intrinsically connected by Ohm‟s law, we cannot say which

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Student No. 11722219 combination of two variables explains the other one. However, if we are simply looking for an explanation in Hemple’s sense, this is not an issue… It is true to say that we cannot ultimately deduce which variable is ultimately caused by which here – but, once again, we have our particular facts and our general law which jointly allow us to produce a reasonable and dependable explanation.

One final objection to Hemple‟s model comes from Salmon (1984) who raises an issue specifically related to the inductive statistical method of explanation. He explains that, based on Hemple‟s suggestions, “if two heterozygous brown-eyed parents produce a brown-eyed child, that fact can presumably be explained statically on the basis of the 0.75 probability of such an occurrence” (Salmon, 1984). However, if the same parents had a child with blue eyes, the phenomenon could not be explained by means of inductive statistical explanation due to the low probability of the child being born with blue eyes.

Thus, Salmon suggests that Hemple‟s conception in flawed, because we generally “understand each of these occurrences equally well” (Salmon, 1984). In this case, a brown-eyed child is to be expected with high logical probability. Nevertheless, it could be argued that a blue-eyed baby could be explained/expected in much the same way – because although the probability of a blue-eyed baby is much lower than a brown-eyed one, any probability is superseded by it being a possibility. Explaining a brown-eyed baby on the grounds that it was highly probable is ultimately just explaining a browneyed baby on the grounds that it was possible. This does not achieve anything more than explaining a blue-eyed baby on the grounds that it was in some minute way probable, because both explanations simply rest upon the claim that each explanandum was

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Student No. 11722219 possible. Taking this into account, the inductive statistical method of explanation is exposed as being weak, and solely based upon the „law‟ of possibility rather than that of probability. However, yet again, this example can be said to fall within our criteria for a good explanation – we have our particular facts that two heterozygous brown-eyed parents copulated and produced a blue-eyed child, and we have our law of possibility (derived from, yet superseding our law of probability) which allows us to form a dependable explanation/prediction. As I have previously outlined, the dependability of the prediction is directly related to the truth/reliability of the probabilistic law upon which it is based – but whether the probability is low or high, we can still say the explanation/prediction is dependable to that degree.

In conclusion, I have systematically pitted the objections to the validity of Hemple‟s forms of explanation against Hemple‟s own criteria for judging whether a scientific explanation is a good one or not, and I have shown Hemple‟s model to remain intrinsically coherent despite the adversity of these objections. This is due to the fact that the objectors‟ real issue in each case lies not with Hemple‟s forms of explanation, but with his fundamental criteria for judging whether a scientific explanation is a good one or not. Lyon‟s, Ruben‟s and Salmon‟s objections can only be seen as valid if viewed in light of an altered version of these criteria. In other words, their objections are simply based upon different definitions of „a good scientific explanation‟ to that of Hemple. In essence, what they appear to be looking for in order to deem an explanation a good one involves identifying a specific causal link to the event in question. This is, of course, a relatively common position to hold… However, even if one were to somehow identify

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Student No. 11722219 every direct cause involved in producing a specific event, there would still be room for questioning what caused the causes, what causes the causes of the causes, and so on and so on in an infinite regress. Thus, barring a miraculous and complete explanation of the entire universe, any assertion that a causal explanation is a good one involves making a judgement of validity that after a certain amount of causal links the explanation becomes acceptable – as the causal explanation cannot be complete. Hemple‟s criteria, too, involve a judgement of validity – but rather than appealing solely to the law of causality, they appeal to universal laws in general. These laws are intrinsically involved with causality, but by making the laws as laws (rather than the origin of the causality involved in them) the foundation for his judgement of validity – Hemple immediately avoids delving into the problem of infinite causal regression. Regardless, it is clear from what I have outlined that no judgement can be said to represent a complete or true explanation. Thus, no explanation can claim to objectively count as the explanation of an event. What counts as an explanation, then, is a purely subjective judgement.

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Student No. 11722219

Reference List:Dewey, J. S. (1910). How We Think. Boston: Heath. Chapter VI. Hempel, C. G. (1998) „Two basic types of scientific explanation‟, in Curd and Cover (eds.), Philosophy of Science: The Central Issues. Norton. pp. 685-694 Hempel, C. G. (1998) „The thesis of structural identity‟, in Curd and Cover (eds.), Philosophy of Science: The Central Issues. Norton. pp. 695-705.

Lyon, A. (1974). “The Relevance of Wisdom‟s Work for the Philosophy of Science: A Study of the Concept of Scientific Explanation”, in Wisdom: Twelve Essays, ed. Renford Bambrough. Blackwell: Oxford. pp. 218-248.

Ruben, D. H. (1998). „Arguments, Laws and Explanation‟ in Curd and Cover (eds.), Philosophy of Science: The Central Issues. Norton. pp. 808-825 Salmon, W. (2006). Four Decades of Scientific Explanation. First University of Pittsburgh Press: Pittsburgh.

Salmon, W. C. (1984). “Scientific Explanation: Three Basic Conceptions”. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, Vol. 1984,Volume Two: Symposia and Invited Papers. pp. 293-305.

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Student No. 11722219 Bibliography:Bortolotti, L. (2008). An Introduction to The Philosophy of Science. Cambridge: Polity.

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

Hempel, C. G. (1998). „Inductive-Statistical Explanation‟, in Curd and Cover (eds.), Philosophy of Science: The Central Issues. New York: Norton. pp. 706-16.

Lewis, D. (1987). „Causal Explanation‟, Philosophical Papers, volume II. Oxford: Oxford University Press.

Mauskopf, S. & Schmaltz, T. (2011). Integrating History and Philosophy of Science: Problems and Prospects. London: Springer.

Papineau, D. (1995). „Explanation‟ of A.C. Grayling ed. Philosophy: A Guide through the Subject. Oxford: Oxford University Press. pp. 171-179.

Railton, P. (1998). „A Deductive-Nomological Model of Probabilistic Explanation‟, in Curd and Cover (eds.), Philosophy of Science: The Central Issues. New York: Norton. pp. 746-764.

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