Abstract
Different why-questions emerge under different contexts and require different information in order to be addressed. Hence a relevance relation can hardly be invariant across contexts. However, what is indeed common under any possible context is that all explananda require scientific information in order to be explained. So no scientific information is in principle explanatorily irrelevant, it only becomes so under certain contexts. In view of this, scientific thought experiments can offer explanations, should we analyze their representational strategies. Their representations involve empirical as well as hypothetical statements. I call this the “representational mingling” which bears scientific information that can explain events. Buchanan’s thought experiment from constitutional economics is examined to show how mingled representations explain.
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Notes
Salis and Frigg (2020) also treat models and thought experiments as the same thing. Their analysis focuses on the imaginative activities in these two scientific practices.
See Thoma who argues that thought experiments are to be considered as an informal piece of reasoning whereas the models to be the formal one. Her main thesis is that thought experiments, are supportive to the formal models in the sense that they provide an illustrative hypothetical scenario that the formal model does apply to (Thoma 2016).
Chandrasekharan et al. (2013) in an article under the tantalizing heading: “Computational Modeling: Is this the End of Thought Experiments in Science?” share a similar view, i.e. that thought experiments are supportive to computational models in science nowadays. I would like first to take issue with one of the premises upon which their conclusion is drawn. In particular, they claim that thought experiments were more suitable to a more limited problem-environment which included paper, pencil and brain and thus they cannot tackle problems of contemporary science (ibid. 259). This is not the case though. Thought experiments have been mushrooming since antiquity and are perennially used in scientific tasks even in times of advanced and highly subtle scientific practices which alongside thought experiments involve instruments (telescopes, microscopes, spectographs et.al.), observation and real experimentation. Thus they are used even when the scientific environment is not confined to a “pencil, paper and brain” environment. Finally, to say that thought experiments are only supportive to computational modeling this suggests that the differences between models and thought experiments are obvious, which is hardly the case and neither Chandrasekharan et al. nor Thoma confront themselves with the task of discriminating between them.
To be clear, I do not deny that exploring possible similarities between thought and real experiments could be an epistemologically interesting project (Buzzoni 2008, 2013, 2018); my concern though is that this approach to thought experiments appears to strengthen the claim, explicitly held by some philosophers (Mach, 1897/1905; Gooding, 1992; Snooks, 2006; Sorensen, 1992; Schabas, 2018), that there must be an “experimental character” (or the so-called “experimental-ness of thought experiments”) which has to be set as a criterion that an account has to meet in order to be considered as a thought experiment which suggests that there are mingled representations that should not be considered thought experiments since they have no “experimental-ness”. This is the view I am opposing in this section.
Since I have discriminated between thought and real experiments and since I accept as thought experiments all mingled representations and I claim that they are to be viewed as what the individual who constructs them thinks it is appropriate to represent, then one could argue that, if that is the case, then there is no reason to call them “thought experiments” at all since they have no distinctive feature that should make us call them that way. While this is not the place to make such a case, I would not object that this point is consistent with the preceding and, if some time in the future the tide of opinion turns that way, it would not be at odds with what in fact happens in science. Thus I could see a scenario whereby the discussion is seguing neatly from the current distinction between thought experiments, models and computer simulations to one in which we are getting rid of these terms and start calling them all “mingled representations”. This could give rise to a novel tripartite distinction between empirical representations (where, among many other practices, real experiments could belong), mingled representations and merely hypothetical representations. The differences between the three are more clearly figured out than the assumed differences between models and thought experiments and even though this framework would not be without its own philosophical intricacies, it may turn out to be a more accurate way to describe scientific activities in comparison to the current distinction between models, computer simulations and thought experiments which often suggests that thought experiments are closer to real experiments than to models or computer simulations.
Norton offers a detailed discussion of Einstein’s principle of equivalence (Norton, 1985).
For a discussion see also Thoma (2016).
A is a reason that explains Pk and thus the word “because” does not necessarily imply a causal connection (van Fraassen ibid).
Buchanan illustrates the transition from natural distribution to constitutional contract through a diagram (ibid. 75) which bears pretty much the same information as the linguistic representation of the same state of affairs. Hence, a full presentation of this diagram would be rather redundant here.
De May and Weber (2003) have published an interesting piece in which they discuss the role of thought experiments in history. Their theory allows that thought experiments are used by historians when they try to establish causality. So, when more than one events appear as plausible explanations of a historical event, historians ask hypothetical questions in order to figure out which of the candidates gives the best causal explanation. While their proposal seems to square very well with how historians work, it gives thought experiments mostly the role of evaluating answers and not the role of relevance relation. Of course, thought experiments are versatile and providing explanations is only one of the roles that they perform and so the authors could be definitely accurate in describing them as tools that could help us derive causal explanations in history. However, it is one thing to say that thought experiments help us reach a causal explanation, which is in fact an explanation of an event explained by another event, and another thing to say that the information the mingled representations of thought experiments bear is the one that explains an event, or, more generally, that thought experiments are explanatory relevance relations, which is the thesis I am proposing. I make this point here because the paper by De May and Weber could be, unbeknownst to the authors, a possible source of confusion among scholars who could mistakenly take it to discuss how thought experiments provide explanations, while in fact the authors discuss how thought experiments can be used by historians to reach the most appropriate causal explanation.
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Karadimas, P. Thought Experiments and The Pragmatic Nature of Explanation. Found Sci (2022). https://doi.org/10.1007/s10699-022-09844-2
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DOI: https://doi.org/10.1007/s10699-022-09844-2