The notion of truthlikeness or verisimilitude has been a topic of intensive discussion ever since the definition proposed by Karl Popper was refuted in 1974. This paper gives an analysis of old and new debates about this notion. There is a fairly large agreement about the truthlikeness ordering of conjunctive theories, but the main rival approaches differ especially about false disjunctive theories. Continuing the debate between Niiniluoto’s min-sum measure and Schurz’s relevant consequence measure, the paper also gives a critical assessment (...) of Oddie’s new defense of the average measure and Kuipers’ refined definition of truth approximation. (shrink)

Focusing on computational studies of pericyclic reactions from the late twentieth century into the twenty-first century, this paper argues that computational diagnostics is a key methodological development that characterize the management and coordination of plural approximation methods in computational organic chemistry. Predictive divergence between semi-empirical and ab initio approximation methods in the study of pericyclic reactions has issued in epistemic dissent. This has resulted in the use of diagnostics to unpack computational greyboxes in order to critically assess the effect of (...) specific misrepresentations on predictive accuracy given that approximations and idealizations must be made to render computational models tractable. Furthermore, benchmarking is used to determine the applicability of approximation methods depending on how accurate the results need to be in a given research context. The epistemology of benchmarking consists of the co-generation of data sets in a hybrid computational–experimental form used to standardize computational methods but does not determine a unique quantitative method to be used across computational organic chemistry. (shrink)

The modern history of verisimilitude can be divided into three periods. The first began in 1960, when Karl Popper proposed his qualitative definition of what it is for one theory to be more truthlike than another theory, and lasted until 1974, when David Miller and Pavel Trichý published their refutation of Popper's definition. The second period started immediately with the attempt to explicate truthlikeness by means of relations of similarity or resemblance between states of affairs (or their linguistic representations); the (...) work within this similarity approach was summarized in the books of Graham Oddie [1986] and Ilkka Niiniluoto [1987]. During the subsequent third period, studies in verisimilitude have been actively continued, and interesting results and applications have been achieved, but not many dramatic novelties. While it is now obsolete to claim that truthlikeness with reasonable properties cannot be defined at all, there is still a lot of controversy about the best and least arbitrary approach to doing this. (shrink)

The modern history of verisimilitude can be divided into three periods. The first began in 1960, when Karl Popper proposed his qualitative definition of what it is for one theory to be more truthlike than another theory, and lasted until 1974, when David Miller and Pavel Trich published their refutation of Popper's definition. The second period started immediately with the attempt to explicate truthlikeness by means of relations of similarity or resemblance between states of affairs (or their linguistic representations); the (...) work within this similarity approach was summarized in the books of Graham Oddie [1986] and Ilkka Niiniluoto [1987]. During the subsequent third period, studies in verisimilitude have been actively continued, and interesting results and applications have been achieved, but not many dramatic novelties. While it is now obsolete to claim that truthlikeness with reasonable properties cannot be defined at all, there is still a lot of controversy about the best and least arbitrary approach to doing this. (shrink)

"Semantic dispositionalism" is the theory that a speaker's meaning something by a given linguistic symbol is determined by her dispositions to use the symbol in a certain way. According to an objection by Kripke, further elaborated in Kusch :156–163, 2005), semantic dispositionalism involves ceteris paribus-clauses and idealisations, such as unbounded memory, that deviate from standard scientific methodology. I argue that Kusch misrepresents both ceteris paribus-laws and idealisation, neither of which factually "approximate" the behaviour of agents or the course of events, (...) but, rather, identify and isolate nature's component parts and processes. An analysis of current results in cognitive psychology vindicates the idealisations involved and certain counterfactual assumptions in science generally. In particular, results suggest that there can be causal continuity between the dispositional structure of actual objects and that of highly idealised objects. I conclude by suggesting that we can assimilate ceteris paribus-laws with disposition ascriptions insofar as they involve identical idealising assumptions. (shrink)

It’s uncontroversial that notions of idealization and approximation are central to understanding computer simulations and their rationale. So, for example, one common form of computer simulation is to abandon a realistic approach that is computationally non-tractable for a more idealized but computationally tractable approach. Many simulations of systems of interacting members can be understood this way. In such simulations, realistic descriptions of individual members are replaced with less realistic descriptions which have the virtue of making interactions computationally tractable. Such simulations (...) can be supplemented with empirically determined correction factors which render the output produced by means of the idealizations more in accord, one hopes, with what the more realistic approach would have produced had it been computationally tractable. Another way to utilize computers is to replace an idealized but analytically tractable account of some phenomenon with a less idealized account which has no closed form or analytical solutions but where the computer can be used generate approximations to the desired solutions. (shrink)

A tacit assumption in the field of consciousness studies is that the more empirical evidence a theory can explain, the better it fares when weighed against competitors. If one wants to take seriously the potential for empirical evidence to move forward debates in consciousness studies, there is a need to gather, organize, validate, and compare evidence. We present an inference to the best explanation (IBE) process on the basis of empirical support that is applicable in debates between competing theories of (...) consciousness. Our proposed IBE process consists in four steps: Assimilate, Compile, Validate, and Compare. Until now, the vast majority of the work in the field has consisted in gathering empirical evidence for theories i.e., the assimilation step. To illustrate the feasibility of our proposed IBE process, and what it may look like when applied in practice, we deliver a complete collection (the compilation step) of empirical support for the distinction between A-Consciousness and P-Consciousness and the overflow hypothesis. Finally, we offer an example of the validation step, by scrutinizing the interpretation of aphantasics’ performance on retro-cue paradigms offered in the literature in support of the overflow hypothesis. The compilation we deliver here is the first effort in the IBE process, the end result of which — hopefully — will be the ability of the research community to carry out side-by-side comparisons of theories and the empirical phenomena they claim to explain, i.e., the comparison step. (shrink)

In a previous article, I argued that some recent philosophical work on the use of fictions in science is, while illuminating about some aspects of current scientific practice, unduly limited to cases of well-established fictions. In other words, this earlier work contended, a philosophical account of scientific fictions can do more than merely describe scientific practices, but can aid in the resolution of disputes about the proper interpretation of scientific theories and the epistemic status of some scientific models. In the (...) present paper, I expand upon the variational account of fictions and idealizations... (shrink)

The notion of truthlikeness or verisimilitude has been a topic of intensive discussion ever since the definition proposed by Karl Popper was refuted in 1974. This paper gives an analysis of old and new debates about this notion. There is a fairly large agreement about the truthlikeness ordering of conjunctive theories, but the main rival approaches differ especially about false disjunctive theories. Continuing the debate between Niiniluoto’s min-sum measure and Schurz’s relevant consequence measure, the paper also gives a critical assessment (...) of Oddie’s new defense of the average measure and Kuipers’ refined definition of truth approximation. (shrink)

Traditional theories construe approximate truth or truthlikeness as a measure of closeness to facts, singular facts, and idealization as an act of either assuming zero of otherwise very small differences from facts or imagining ideal conditions under which scientific laws are either approximately true or will be so when the conditions are relaxed. I first explain the serious but not insurmountable difficulties for the theories of approximation, and then argue that more serious and perhaps insurmountable difficulties for the theory of (...) idealization force us to sever its close tie to approximation. This leads to an appreciation of lawlikeness as a measure of closeness to laws, which I argue is the real measure of idealization whose main purpose is to carve nature at its joints. (shrink)

This paper argues that a significant focus in computational organic chemistry, alongside the construction and deployment of models, is the “deconstruction” of computational models. This practice has arisen in response to difficulties and controversies resulting from the use of plural methods and computational models to study organic reaction mechanisms. Diagnostic controllability is the capacity of cognitive agents to gain epistemic access to grey-boxed computational models, to identify and explain the impact of specific idealizations on results, and to demonstrate the applicability (...) of computational methods to target systems. (shrink)

Because they contain idealizations, scientific models are often considered to be misrepresentations of their target systems. An important question is therefore how models can explain the behaviours of these systems. Most of the answers to this question are representationalist in nature. Proponents of this view are generally committed to the claim that models are explanatory if they represent their target systems to some degree of accuracy; in other words, they try to determine the conditions under which idealizations can be made (...) without jeopardizing the representational function of models. In this article, we first outline several forms of this representationalist view. We then argue that this view, in each of these forms, omits an important role of idealizations: that of facilitating the identification of the explanatory components within a model. Via examination of a case study from contemporary astrophysics, we show that one way in which idealizations can do this is by creating a comparison case that s... (shrink)

The ArgumentIdealizations and approximations are an indispensable tool for the scientist. This paper argues that idealizations and approximations are equally indispensable for the philosopher of science. In particular, it is shown that the deductive model of scientific theories is an idealization in precisely the same sense that frictionless motion is an idealization in mechanics. By its very nature, an idealization cannot be criticized as not being absolutely true to the facts, for it need not be. Thus, the usual type of (...) criticism levelled against the deductive model is shown to be irrelevant. The main step in the argument consists in using a logic of approximation to clarify the notions of approximate implication and approximate entailment, which are usually rejected as hopelessly vague. More generally, the conception underlying the paper is that the desiderata of science should be formulated in such a way that complying with them could be a matter of degree, and that pragmatic considerations could be taken into account. This conception is motivated by the wish to introduce some quantitative concepts in the philosophy of science, thereby bringing the philosopher's perspective closer to that of the scientist. (shrink)

I critically examine some recent work on the philosophy of scientific fictions, focusing on the work of Winsberg. By considering two case studies in fracture mechanics, the strip yield model and the imaginary crack method, I argue that his reliance upon the social norms associated with an element of a model forces him to remain silent whenever those norms fail to clearly match the characteristic of fictions or non-fictions. In its place, I propose a normative epistemology of fictions which clarifies (...) a model's ontological commitments when the community of scientists lack any clear, shared norms of use. Specifically, I will introduce a variational account of fictions as an extension of Laymon's monotonic improvability account of idealizations. I will conclude by connecting this variational account of fictions to didactic fictions in general. (shrink)

The problem for the scientist created by using idealizations is to determine whether failures to achieve experimental fit are attributable to experimental error, falsity of theory, or of idealization. Even in the rare case when experimental fit within experimental error is achieved, the scientist must determine whether this is so because of a true theory and fortuitously canceling idealizations, or due to a fortuitous combination of false theory and false idealizations. For the engineer, the problem seems rather different. Experiment for (...) the engineer reveals the closeness of predictive fit that can be achieved by theory and idealization for a particular case. If the closeness of fit is good enough for some practical purpose, the job is done. If not, or there are reasons to consider variation, then the engineer needs to know how well the experimentally determined closeness of fit will extrapolate to new cases. This paper focuses on engineering measures of closeness of fit and the projectibility of those measures to new cases. (shrink)