Foundations of Science最新文献

What is post-normal science? What are the reasons for, and consequences of, encountering it in one’s professional life? Here I share my own experience of readings, practices and discussions with the fathers, supporters and detractors of PNS. After a short description of PNS and of my own experience with it, I review some common criticism levelled to PNS from different authors and conclude reflecting on how PNS—difficult to explain and translate into formulae or checklists—provides its practitioners with useful keys to open relevant doors to understanding, and might be especially suited to face the present intersecting crises befalling the use of science for policy.

I offer a variant of Putnam’s “permutation argument,” originally an argument against metaphysical realism. This variant is called the “natural permutation argument.” I explain how the natural permutation argument generates a form of referential inscrutability which is not resolvable by consideration of “natural properties” in the sense of Lewis’s response to Putnam. However, unlike the classical permutation argument (which is applicable to nearly all interpretations of all first-order theories), the natural permutation argument only applies to interpretations which have some special symmetries. I give an analysis of the interpretations to which the natural permutation argument does apply, and I explain how, when it fails to apply, the referential inscrutability generated by permutation arguments is resolvable by a Lewisian strategy. In order to demonstrate how these problems of referential inscrutability play out in an a priori setting relevant to philosophy, I discuss the applicability of the natural permutation argument in set-theoretic reasoning. I use the well-known Kunen inconsistency theorem to show that, in Zermelo–Fraenkel set theory, the Axiom of Choice is sufficient to resolve referential inscrutability. I then explain how, as a result of a recent theorem of Daghighi–Golshani–Hamkins–Jeřábek, in certain non-well-founded set theories the natural permutation argument does yield an intractable inscrutability of reference.

Perhaps the most influential historian of science of the last century, Alexandre Koyré, famously argued that the icon of modern science, Galileo Galilei, was a Platonist who had hardly performed experiments. Koyré has been followed by other historians and philosophers of science. In addition, it is not difficult to find examples of Platonists in contemporary science, in particular in the physical sciences. A famous example is the icon of twenty century physics, Albert Einstein. This paper addresses two questions related to the Platonism of modern physical science. The first is: How is Galileo’s Platonism compatible with the fact that he did perform experiments? The solution to this apparent paradox can be found in Plato’s late dialogue Timaeus. In the dialogue the world has been created by a divine craftsman according to an original plan. The task of the scientist is not primarily to describe the material world, but to reconstruct the original plan. This view has later been known as “God’s Eye View”. The second question is: If a God’s Eye View is unattainable, how is it possible to give a “rational reconstruction” of Galileo’s Platonism? The key-word is idealisation. It is further argued that idealisation is intimately related to technology. Technology is required to realize ideal experimental conditions, and the results are in its turn implemented in technology. The implication is that the quest for unity in science, based on physics as the basic science, should be replaced by the recognition of the diversity of the sciences.

I show how Sir William Rowan Hamilton’s philosophical commitments led him to a causal interpretation of classical mechanics. I argue that Hamilton’s metaphysics of causation was injected into his dynamics by way of a causal interpretation of force. I then detail how forces are indispensable to both Hamilton’s formulation of classical mechanics and what we now call Hamiltonian mechanics (i.e., the modern formulation). On this point, my efforts primarily consist of showing that the contemporary orthodox interpretation of potential energy is the interpretation found in Hamilton’s work. Hamilton called the potential energy function the “force-function” because he believed that it represents forces at work in the world. Various non-historical arguments for this orthodox interpretation of potential energy are provided, and matters are concluded by showing that in classical Hamiltonian mechanics, facts about the potential energies of systems are grounded in facts about forces. Thus, if one can tolerate the view that forces are causes of motion, then Hamilton provides one with a road map for transporting causation into one of the most mathematically sophisticated formulations of classical mechanics, viz., Hamiltonian mechanics.

This paper provides the first systematic epistemological account of simulated data in empirical science. We focus on the epistemic issues modelers face when they generate simulated data to solve problems with empirical datasets, research tools, or experiments. We argue that for simulated data to count as epistemically reliable, a simulation model does not have to mimic its target. Instead, some models take empirical data as a target, and simulated data may successfully mimic such a target even if the model does not. We show how to distinguish between simulated and empirical data, and we also offer a definition of simulation that can accommodate Monte Carlo models. We shed light on the epistemology of simulated data by providing a taxonomy of four different mimicking relations that differ concerning the nature of the relation or relata. We illustrate mimicking relations with examples from different sciences. Our main claim is that the epistemic evaluation of simulated data should start with recognizing the diversity of mimicking relations rather than presuming that only one relation existed.

By justification we understand what makes a belief epistemologically viable: generally this is considered knowledge that is true. The problem is defining this with a higher degree of precision because this is where different conflicting conceptions appear. On the one hand, we can understand justification as what makes it reasonable to acquire or maintain a belief; on the other, it is what increases the probability that the belief is true. This work tries to prove that beliefs depend on other beliefs that are epistemically justified and that such beliefs are the result of (i.e., they arise from) our privileged intuition of reality. For this, we examine the concept of epistemic regress. Epistemic reasons authorize a proposition P to be the conclusion of an argument in which such reasons function as premises and are vulnerable to epistemic regress. The three most important approaches to epistemic regress are Infinitism, Coherentism and Foundationalism.

In recent years, much research has been devoted to exploring contextuality in systems that are not strictly quantum, like classical light, and many theory-independent frameworks for contextuality analysis have been developed. It has raised the debate on the meaning of contextuality outside the quantum realm, and also on whether—and, if so, when—it can be regarded as a signature of non-classicality. In this paper, we try to contribute to this debate by showing a very simple “thought experiment” or “toy mechanism” where a classical object (i.e., an object obeying the laws of classical physics) is used to generate experimental data violating the KCBS inequality. As with most thought experiments, the idea is to simplify the discussion and to shed light on issues that in real experiments, or from a purely theoretical perspective, may be cumbersome. We give special attention to the distinction between classical realism and classicality, and to the contrast between contextuality within and beyond quantum theory.

The function of concepts must be taken seriously to understand the scientific practices of developing and working with concepts. Despite its significance, little philosophical attention has been paid to the function of concepts. A notable exception is Brigandt (2010), who suggests incorporating the epistemic goal pursued with the concept’s use as an additional semantic property along with the reference and inferential role. The suggestion, however, has at least two limitations. First, his proposal to introduce epistemic goals as the third component of concepts lacks independent grounding, except to account for the rationality of semantic change (the Grounding Problem). Second, it is hardly justified to consider epistemic goals as a semantic property (the Misplacement Problem). To remedy these predicaments, we suggest a new perspective that takes concepts as cognitive entities with a 2-layered structure rather than as merely linguistic entities and develop an account of the function of concepts. We provide empirical evidence showing that functional information affects our cognitive processes. It is claimed that the function of concepts is not a semantic property but a type of meta-information regulating a body of concept-constitutive information.

This paper explores the relationship between informal reasoning, creativity in mathematics, and problem solving. It underscores the importance of environments that promote interaction, hypothesis generation, examination, refutation, derivation of new solutions, drawing conclusions, and reasoning with others, as key factors in enhancing mathematical creativity. Drawing on argumentation logic, the paper proposes a novel approach to uncover specific characteristics in the development of formalized proving using “proof-events.” Argumentation logic can offer reasoning mechanisms that facilitate these environments. This paper proposes how argumentation can be implemented to discover certain characteristics in the development of formalized proving with “proof-events”. The concept of a proof-event was introduced by Goguen who described mathematical proof as a multi-agent social event involving not only “classical” formal proofs, but also other informal proving actions such as deficient or alleged proofs. Argumentation is an integral component of the discovery process for a mathematical proof since a proof necessitates a dialogue between provers and interpreters to clarify and resolve gaps or assumptions. By formalizing proof-events through argumentation, this paper demonstrates how informal reasoning and conflicts arising during the proving process can be effectively simulated. The paper presents an extended version of the proof-events calculus, rooted in argumentation theories, and highlights the intricate relationships among proof, human reasoning, cognitive processes, creativity, and mathematical arguments.