European Journal for Philosophy of Science最新文献

I argue that dimensional analysis provides an answer to a skeptical challenge to the theory of model mediated measurement. The problem arises when considering the task of calibrating a novel measurement procedure, with greater range, to the results of a prior measurement procedure. The skeptical worry is that the agreement of the novel and prior measurement procedures in their shared range may only be apparent due to the emergence of systematic error in the exclusive range of the novel measurement procedure. Alternatively: what if the two measurement procedures are not in fact measuring the same quantity? The theory of model mediated measurement can only say that we assume that there is a common quantity. In contrast, I show that the satisfaction of dimensional homogeneity across the metrological extension is independent evidence for the so-called assumption. This is illustrated by the use of dimensional analysis in high pressure experiments. This results in an extension of the theory of model mediated measurement, in which a common quantity in metrological extension is no longer assumed, but hypothesized.

The social epistemology of science has adopted agent-based computer simulations as one of its core methods for investigating the dynamics of scientific inquiry. The epistemic status of these highly idealized models is currently under active debate in which they are often associated either with predictive or the argumentative functions. These two functions roughly correspond to interpreting simulations as virtual experiments or formalized thought experiments, respectively. This paper advances the argumentative account of modeling by proposing that models serve as a means to (re)conceptualize the macro-level dynamics of complex social epistemic interactions. I apply results from the epistemology of scientific modeling and the psychology of mental simulation to the ongoing debate in the social epistemology of science. Instead of considering simulation models as predictive devices, I view them as artifacts that exemplify abstract hypothetical properties of complex social epistemic processes in order to advance scientific understanding, hypothesis formation, and communication. Models need not be accurate representations to serve these purposes. They should be regarded as pragmatic cognitive tools that engender rather than replace intuitions in philosophical reasoning and argumentation. Furthermore, I aim to explain why the community tends to converge around few model templates: Since models have the potential to transform our intuitive comprehension of the subject of inquiry, successful models may literally capture the imagination of the modeling community.

Quantum mechanics is arguably our most successful physical theory, yet the nature of the quantum state still constitutes an ongoing controversy. This paper proposes, articulates, and defends a metaphysical interpretation of the quantum state that is fictionalist in spirit since it regards quantum states as representing a fictional ontology. Such an ontology is therefore not physical, and yet it provides a reference for the language used in quantum mechanics and has explanatory power. In this sense, this view, akin to Allori’s recent account of wavefunctionalism, combines elements of the representationalist and anti-representationalist camps and aims to be the best of both worlds.

The tradition of natural kinds has shaped philosophical debates about scientific classification but has come under growing criticism. Responding to this criticism, Reydon and Ereshefsky present their grounded functionality account as a strategy for updating and defending the tradition of natural kinds. This article argues that grounded functionality does indeed provide a fruitful philosophical approach to scientific classification but does not convince as a general theory of natural kinds. Instead, the strengths and limitations of Reydon and Ereshefsky’s account illustrate why it is time to move beyond general definitions of “natural kind” and experiment with new philosophical frameworks.

The general study of the ontology of quantum field theories (QFTs) concerns whether particles or fields are more fundamental. Both views are well-motivated, although each is subject to some serious criticism. Given that the current versions of the particle interpretation and the field interpretation are not satisfying, I propose a mixed ontology of particles and fields in the framework of QFT. I argue that the ontological question should focus on how to view particles and fields consistently in QFT, provided that they are the natural candidates for the ontology of QFT. In particular, based on this reading, I adopt a functionalist reading of ontology and defend a mixed ontology of QFT. I address a paradigmatic case of the mixed ontology approach: a particle/field duality defined in terms of functional equivalence between particles and fields. Functionalism about ontology provides new insight into resolving the problem of unitarily inequivalent representations, which is one of the major interpretational issues of QFT.

Different species of realism have been proposed in the scientific and philosophical literature. Two of these species are direct realism and causal pattern realism. Direct realism is a form of perceptual realism proposed by ecological psychologists within cognitive science. Causal pattern realism has been proposed within the philosophy of model-based science. Both species are able to accommodate some of the main tenets and motivations of instrumentalism. The main aim of this paper is to explore the conceptual moves that make both direct realism and causal pattern realism tenable realist positions able to accommodate an instrumentalist stance. Such conceptual moves are (i) the rejection of veritism and (ii) the re-structuring of the phenomena of interest. We will then show that these conceptual moves are instances of the ones of a common realist genus we name pragmatist realism.

This article provides an epistemological assessment of climate analogue methods, with specific reference to the use of spatial analogues in the study of the future climate of target locations. Our contention is that, due to formal and conceptual inadequacies of geometrical dissimilarity metrics and the loss of relevant information, especially when reasoning from the physical to the socio-economical level, purported inferences from climate analogues of the spatial kind we consider here prove limited in a number of ways. Indeed, we formulate five outstanding problems concerning the search for best analogues, which we call the problem of non-uniqueness of the source, problem of non-uniqueness of the target, problem of average, problem of non-causal correlations and problem of inferred properties, respectively. In the face of such problems, we then offer two positive recommendations for a fruitful application of this methodology to the assessment of impact, adaptation and vulnerability studies of climate change, especially in the context of what we may prosaically dub “twin cities”. Arguably, such recommendations help decision-makers constrain the set of plausible climate analogues by integrating local knowledge relevant to the locations of interest.

This paper attempts to revive the epistemological discussion of scientific articles. What are their epistemic aims, and how are they achieved? We argue that scientific experimental articles are best understood as a particular kind of narrative: i.e., modernist narratives (think: Woolf, Joyce), at least in the sense that they employ many of the same techniques, including colligation and the juxtaposition of multiple perspectives. We suggest that this way of writing is necessary given the nature of modern science, but it also has specific epistemic benefits: it provides readers with an effective way to grasp the content of scientific articles which increases their understanding. On the other hand, modernist writing is vulnerable to certain kinds of epistemic abuses, which can be found instantiated in modern scientific writing as well.

Among the various proposals for quantum ontology, both wavefunction realists and the primitive ontologists have argued that their approach is to be preferred because it relies on intuitive notions: locality, separability and spatiotemporality. As such, these proposals should be seen as normative frameworks asserting that one should choose the fundamental ontology which preserves these intuitions, even if they disagree about their relative importance: wavefunction realists favor preserving locality and separability, while primitive ontologists advocate for spatiotemporality. In this paper, first I clarify the main tenets of wavefunction realism and the primitive ontology approach, arguing that seeing the latter as favoring constructive explanation makes sense of their requirement of a spatiotemporal ontology. Then I show how the aforementioned intuitive notions cannot all be kept in the quantum domain. Consequently, wavefunction realists rank locality and separability higher than spatiotemporality, while primitive ontologists do the opposite. I conclude that however, the choice of which notions to favor is not as arbitrary as it might seem. In fact, they are not independent: requiring locality and separability can soundly be justified by requiring spatiotemporality, and not the other way around. If so, the primitive ontology approach has a better justification of its intuitions than its rival wavefunction realist framework.

Interpretation plays a central role in using scientific models to explain natural phenomena: Meaning must be bestowed upon a model in terms of what it is and what it represents to be used for model explanations. However, it remains unclear how capacious and complex interpretation in models can be, particularly when conducted by the same group of scientists in the context of one explanatory project. This paper sheds light upon this question by examining modelling and explanatory practices related to the Olami-Feder-Christensen model of earthquakes. This case study shows that various interpretations are intricately connected in the overall meaning of a model used for model explanations. This leads to a manifold picture of interpretation, according to which scientific models are construed as networks of interconnected meanings. As scientists ponder and integrate these various interpretations, guided by locally attended epistemic interests, they achieve model explanations with layers of content, both in their explanantia and explananda.