How are fictions given? Conjoining the ‘artifactual theory’ and the ‘imaginary-object theory’

According to the so-called ‘artifactual theory’ of fiction, fictional objects are to be considered as abstract artifacts. Within this framework, fictional objects are defined on the basis of their complex dependence on literary works, authors, and readership. This theory is explicitly distinguished from other approaches to fictions, notably from the imaginary-object theory. In this article, I argue that the two approaches are not mutually exclusive but can and should be integrated. In particular, the ontology of fiction can be fruitfully supplemented by a phenomenological analysis, which allows us to clarify the defining modes of givenness of fictional objects. Likewise, based on the results of the artifactual theory, some assumptions in the imaginary-object theory, which are liable to be interpreted as laying the ground to phenomenalism, can be corrected.

If Models Were Fictions, Then What Would They Be?

There has been growing interest in the idea that model descriptions should be thought of as similar to stories, and model systems should be thought of as akin to fictional characters. But if model systems were (like) fictional characters, what would they be? Two prominent approaches to fictional discourse have been pursued in the literature on models: realist approaches, which take models to be abstract objects that (in some sense) fit the model descriptions, and anti-realist approaches, which typically hold that the relevant discourse involves pretense in a way that enables us to deny that we ever refer to models. Both of these views have problems well known in the literature on fiction. These problems have motivated a third, increasingly popular approach to the ontology of fiction: an artifactual approach, according to which our (external) discourse about fiction refers to abstract artifacts. This approach has been little considered in the literature on scientific models—but this chapter argues that it has important advantages over the familiar alternatives. Most notably, an artifactualist approach can retain the advantages of the pretense view while giving a far more straightforward account of external historical, theoretical, and critical discourse about models. In short, bearing in mind the full range of discourse about models gives us reason to accept that there are model systems, where these are considered as a kind of abstract artifact. The main perceived drawback to artifactualist views is their supposed “ontological costs.” In closing, the chapter suggests why ontological qualms of this sort should be discounted.

Realism About Missing Systems

It is by now a familiar fact about scientific practice that scientists of many stripes devote considerable time and energy to describing and imagining systems that cannot be found in the world around us—the simple pendulum in classical mechanics, say. Missing-systems modeling is scientific modeling that involves this sort of imagining. Missing-systems modeling is puzzling in a number of respects, and some philosophers have pursued the fiction approach to understanding it. The fiction approach seeks to construct an account of missing-systems modeling by drawing parallels between the relevant modeling discourse and ordinary discourse about novels, short stories, plays, fiction films, and the like. This chapter develops a new version of the fiction approach that draws on Amie Thomasson’s work on the semantics and ontology of fiction, the abstract artifacts account of missing-systems modeling. On this account, simple pendula (say) are abstract artifacts created by physicists over a certain period in the history of classical mechanics. This chapter shows how the abstract artifact account makes sense of the puzzling features of missing-systems modeling, presents and responds to three objections to the account, and discusses some advantages of drawing on the de re version of Thomasson’s account of fiction, in particular, when developing an account of missing-systems modeling.

Singular Terms, Identity, and the Creation of Fictional Characters

How to interpret singular terms in fiction? In this paper, we address this semantic question from the perspective of the Artifactual Theory of Fiction (ATF). According to the ATF, fictional characters exist as abstract artifacts created by their author, and preserved through the existence of copies of an original work and a competent readership. We pretend that a well-suited semantics for the ATF can be defined with respect to a modal framework by means of Hintikka’s world lines semantics. The question of the interpretation of proper names is asked in relation to two inference rules, problematic when applied in intensional contexts: the Substitution of Identicals and Existential Generalization. The former fails because identity is contingent. The latter because proper names are not necessarily linked to well-identified individuals. This motivates a non-rigid interpretation of proper names in fiction, although cross-fictional reference (e.g. to real entities) is made possible by the interpretative efforts of the reader.

3. Algorithmic thinking

Algorithms are at the epicentre of computer science—thinking computationally is forming the habit of algorithmic thinking. In order for a procedure to qualify as an algorithm, it must possess the following attributes: finiteness, definiteness, effectiveness, and having one or more inputs and one or more outputs. Algorithms are determinate, abstract artifacts, and procedural knowledge. ‘Algorithmic thinking’ explains the process of designing algorithms, the ‘goodness’ of algorithms as utilitarian artefacts, and why the aesthetics of algorithms matter. The performance of algorithms can be estimated in terms of time (or space) complexity. A computational problem is intractable if all known algorithms to solve the problem are of at least exponential time complexity.

Language Games

It must have been entirely coincidental that two remarkable linguistic movements both occurred during the mid 1950s—one in the realm of natural language, the other in the domain of the artificial; the one brought about largely by a young linguist named Noam Chomsky (1928–), the other initiated by a new breed of scientists whom we may call language designers; the one affecting linguistics so strongly that it would be deemed a scientific revolution, the other creating a class of abstract artifacts called programming languages and also enlarging quite dramatically the emerging paradigm that would later be called computer science. As we will see, these two linguistic movements intersected in a curious sort of way. In particular, we will see how an aspect of Chomskyan linguistics influenced computer scientists far more profoundly than it influenced linguists. But first things first: concerning the nature of the class of abstract artifacts called programming languages. There is no doubt that those who were embroiled in the design of the earliest programmable computers also meditated on a certain goal: to make the task of programming a computer as natural as possible from the human point of view. Stepping back a century, we recall that Ada, Countess of Lovelace specified the computation of Bernoulli numbers in an abstract notation far removed from the gears, levers, ratchets, and cams of the Analytical Engine (see Chapter 2, Section VIII ). We have seen in the works of Herman Goldstine and John von Neumann in the United States, and David Wheeler in England that, even as the first stored-program computers were coming into being, eff orts were being made to achieve the goal just mentioned. Indeed, a more precise statement of this goal was in evidence: to compose computer programs in a more abstract form than in the machine’s “native” language. The challenge here was twofold: to describe the program (or algorithm) in such a language that other humans could comprehend, without knowing much about the computer for which the program was written—in other words, a language that allowed communication between the writer of the program and other (human) readers—and also to communicate the program to the machine in such fashion that the latter could execute the program with minimal human intervention.