Abstract
Roman Frigg and James Nguyen present a detailed statement and defense of the fiction view of scientific models, according to which they are akin to the characters and places of literary fiction. They argue that while some of the criticisms this view has attracted raise legitimate points, others are myths. In this chapter, they first identify and then rebut the following seven myths: (1) that the fiction view regards products of science as falsehoods; (2) that the fiction view holds that models are data-free; (3) that the fiction view is antithetical to representation; (4) that the fiction view trivializes epistemology; (5) that the fiction view cannot account for the use of mathematics in the modeling; (6) that the fiction view misconstrues the function of models in the scientific process; and (7) that the fiction view stands on the wrong side of politics. As a result, they conclude that the fiction view of models, suitably understood (as an account of the ontology of models, rather than their function), remains a viable position.
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Notes
- 1.
For a review of the various options see Chap. 6 of Frigg and Nguyen (2020).
- 2.
Other versions of the fiction view take the descriptions to be fictional direct descriptions of their targets. See, for instance, Levy (2015) and Toon (2012); for a discussion of their views see Frigg and Nguyen (2016). The distinction between the two versions of the fiction view is not too important for our current purposes.
- 3.
The notion of fiction as infidelity is common sense and can found in most dictionaries. The online version of Oxford Living Dictionaries, for instance, defines fiction as “something that is invented or untrue”. The idea that fiction is defined in terms of imagination is developed in Evans (1982) and Walton (1990).
- 4.
Imagination can be propositional and need not amount to producing mental pictures. For a discussion of the notion of imagination with special focus on imagination in scientific modeling see Salis and Frigg (2020).
- 5.
This would be in line with Friend (2020, p. 103) who speaks of an “account of models as imagined systems” and Frigg (2003, p. 87) who speaks of “models as imagined objects”. It would also be in line with Thomson-Jones (2020, p. 75) who notes that scientists “devote considerable time and energy to describing and imagining systems that cannot be found in the world around us”, and Thomasson (2020, p. 51) who sets herself the task of analyzing the core idea of regarding models as “imaginary” objects.
- 6.
This point has been made by Martin Zach in his presentation at the workshop ‘Scientific Contents: Fictions or Abstract Objects?’ at University of Santiago de Compostela in January 2017.
- 7.
Usually, at best parts of such descriptions are true of actual systems, but nothing rules out the existence of limiting cases where even the entire description can be true.
- 8.
The point has been made in a talk in Prague on 29 May 2018. The quotes are from the slides; italics are original; bold-face has been removed for typographical unity. The talk is available online at http://stream.flu.cas.cz/categories/representation-in-science.
- 9.
A parallel point is true of models, which are often poor in detail because certain details don’t matter in a given context. It would, however, be mistaken to take models to be defective just because they do not contain certain details. Thanks for Martin Zach for pointing this out to us.
- 10.
There is another objection to the fiction view lurking in the vicinity of this myth. Roughly speaking, it runs as follows: if works of literary fiction contain facts, these facts are not relevant to the aesthetic value of the work of fiction; they are not relevant to the value of the fiction qua fiction. Or more generally, the epistemic value of a work of fiction is not relevant to its aesthetic value. In contrast, whether a scientific model, understood as a work of fiction, contains or doesn’t contain the relevant facts is clearly relevant to the value of the scientific model. Therefore, scientific models and works of literary fictions should not be identified, because what makes them valuable qua model and qua work of fiction respectively, are not the same. We return to this objection in Sect. 6.
- 11.
Another objection might be that the fiction view cannot account for the idea that models denote their targets, which is a requirement of many accounts of representation. A failure of denotation is supposed to come about because in order for X to denote something X has to exist in some ontologically robust sense which fictions lack. We answer that objection in Salis et al. (2020).
- 12.
- 13.
A related objection that has been directed at the fiction view is that it cannot accommodate “design models” (i.e. blueprints, plans, and so on), precisely because the fiction view requires comparing the features of models with the features of their targets. In the case of design models, there is no target system (at least at a certain stage in the modeling process), and therefore no target features with which to compare to the model’s features (Currie 2017). In response to this objection we note, again, that the fiction view concerns the ontology of models, not their representational content. As such, a model doesn’t have to represent in order to be considered a fictional object. Such models are a kind of targetless model, and we discuss them in Frigg and Nguyen (2020, see in particular Chaps. 8-9).
- 14.
For a discussion of how the fiction could be combined with different accounts of representation see Frigg and Nguyen (2016).
- 15.
The notion of a key was also invoked by one of us in a sketched precursor to the DEKI account (Frigg 2010b). As stated there, keys work by taking “facts” about the model to claims about the target. Toon (2012, p. 58) and Levy (2015, pp. 789–90) objected that according to the fiction view there are no facts about models, thus there is nothing for the key to apply to. This objection relies on an overly stringent understanding of “model-fact”: there’s nothing to prevent keys being applied to “facts” which are only fictionally true in the game of make believe associated with the model. Indeed, articulating what is fictionally true in a model is one of the main tasks for the fiction view of models.
- 16.
We use the phrases “cognitive value” and “epistemic value” interchangeably.
- 17.
As we will see, it’s important to distinguish between these two aspects of cognitivism in the context of the fiction view of models, but it is also important in the context of analyzing the value of art itself. Both Gaut (2003) and Thomson-Jones (2005) characterize the debate about art in this way. Gibson (2008) prefers a different characterization according to which the question is whether the artwork itself, qua artwork, contains cognitive content. The difference is not important for our current project.
- 18.
Something similar to this argument is considered by G. Currie (2016, p. 304). Note, however, that he does accept that we can learn from fictions in some sense, albeit in a sense that doesn’t support the analogy between literary fiction and scientific modeling. The problem with locating this myth, as Currie points out, is that there is relatively little agreement about the extent to which fictions hold cognitive or epistemic value. As such, those who think they don’t will take the fiction view of models to be a non-starter (Portides 2014).
- 19.
G. Currie gestures at a similar worry when he notes that “[w]e have no more than the vague suggestion that fictions sometimes shed light on aspects of human thought, feeling, decision, and action” (2016, p. 304). We take it that the below discussion concerning whether what we learn from fiction is “trivial” or “banal” carry over to whether what we learn “sheds light” on phenomena in the world. A position similar to G. Currie’s is also advocated by Portides (2014).
- 20.
Kvasz offers the further objection that scientific models should be distinguished from works of fictions because the former, but not the latter, provide novel knowledge about their targets. Again, it is unclear to us why one should think that by working through the implications of a fictional novel one would not learn anything new.
- 21.
In order to handle these sorts of examples in the context of discussing the cognitive, or epistemic, value of art, the anti-cognitivist can accept that we do learn from fiction, but argue that the fact that we do so is irrelevant to the works’ aesthetic value (this may seem plausible with respect to learning about Dublin’s geography from Ulysses, but we’re unsure whether it’s correct with respect to the other examples discussed). However, here it serves to distinguish between the debate in the philosophy of art and the fiction view of models. In the case of the latter it’s irrelevant as to whether or not what we learn contributes to the works’ aesthetic value. So once the anti-cognitivist’s target is the connection between learning from fiction and its aesthetic value, rather than whether or not we learn from fiction at all, the fiction view of models is no longer threatened by their claims.
- 22.
See Frigg and Nguyen (2017, pp. 56–58) for further elaboration.
- 23.
We want to further note here that we think many literary fictions do have target systems—Animal Farm is quite clearly targeted at Soviet Communism and further examples are not difficult to find; Erich Maria Remarque’s All Quiet on the Western Front and Kurt Vonnegut’s Slaughterhouse-Five are passionate denunciations of the horrors of the First and Second World Wars (respectively)—and as discussed above at least some scientific models lack targets. So this way of distinguishing between literary and scientific fictions seems implausible.
- 24.
Friend (2017a) argues in favour of pluralism about interpretation—which she construes in terms of what is true in the fiction—but her arguments carry over to what the resulting fictions tell us about the world.
- 25.
While this may be the case in general, there are cases from the history of science where considering an alternative interpretation of a model has increased its cognitive value in a way to be celebrated. Consider, for instance, Bohr’s interpretation of a celestial two-body model in terms of atomic structure, or Goodwin’s interpretation of an ecological predation model in terms of economic firms.
- 26.
This objection has been put to us in personal conversation, but we have not been able to locate it in print. However, given that the main competitor to the fiction view, at least in terms of the ontology of scientific models, is the structuralist view, understanding how mathematics enters the picture on the fiction view is crucial for understanding what’s at stake in the debate. Structuralism about models comes in two versions. The traditional version, associated with Suppes (2002) submits that models are structures, while a contemporary alternative, associated with Bueno and French (2018), regards structures as a meta-level representation of models.
- 27.
Even in cases where they are not explicitly mathematical, one might still want to apply mathematical tools to them, we discuss these sorts of cases in Frigg and Nguyen (2016).
- 28.
Friend (2017b) offers a slightly different rule, the “Reality Assumption”, according to which everything which is actually true is fictionally true, just so long as it isn’t explicitly ruled out by the primary truths.
- 29.
Again, the quote is from the slides of his talk, cf. footnote 6.
- 30.
- 31.
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Acknowledgements
We would like to thank Martin Zach and an anonymous referee for comments on an earlier draft, and Joe Roussos and Fiora Salis for helpful discussions when producing the manuscript. James Nguyen recognizes the support of the Jeffrey Rubinoff Sculpture Park for support during the preparation of this chapter. Thanks also to Alejandro Cassini and Juan Redmond for inviting us to contribute to this project.
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Frigg, R., Nguyen, J. (2021). Seven Myths About the Fiction View of Models. In: Cassini, A., Redmond, J. (eds) Models and Idealizations in Science. Logic, Epistemology, and the Unity of Science, vol 50. Springer, Cham. https://doi.org/10.1007/978-3-030-65802-1_6
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