Online research in philosophy

While epistemic justification is a central concern for both contemporary epistemology and philosophy of science, debates in contemporary epistemology about the nature of epistemic justification have not been discussed extensively by philosophers of science. As a step toward a coherent account of scientific justification that is informed by, and sheds light on, justificatory practices in the sciences, this paper examines one of these debates—the internalist–externalist debate—from the perspective of objective accounts of scientific evidence. In particular, we focus on Deborah Mayo’s error-statistical theory of evidence because it is a paradigmatically objective theory of evidence that is strongly informed by methodological practice. We contend that from the standpoint of such an objective theory of evidence, justification in science has both externalist and internalist characteristics. In reaching this conclusion, however, we find that the terms of the contemporary debate between internalists and externalists have to be redefined to be applicable to scientific contexts.

Recent work in cognitive neuroscience on the child's Theory of Mind (ToM) has pursued the idea that the ability to metarepresent mental states depends on a domain-specific cognitive subystem implemented in specific neural circuitry: a Theory of Mind Module. We argue that the interaction of several domain-general mechanisms and lower-level domain-specific mechanisms accounts for the flexibility and sophistication of behavior, which has been taken to be evidence for a domain-specific ToM module. This finding is of more general interest since it suggests a parsimonious cognitive architecture can account for apparent domain specificity. We argue for such an architecture in two stages. First, on conceptual grounds, contrasting the case of language with ToM, and second, by showing that recent evidence in the form of fMRI and lesion studies supports the more parsimonious hypothesis. Theory of Mind, Metarepresentation, and Modularity Developmental Components of ToM The Analogy with Modularity of Language Dissociations without Modules The Evidence from Neuroscience Conclusion CiteULike Connotea Del.icio.us What's this?

This book develops an explanation for the roles of observation and theory in scientific endeavor that occupies the middle ground between empiricism and rationalism, and captures the strengths of both approaches. Brown argues that philosophical theories have the same epistemological status as scientific theories and constructs an epistemological theory that provides an account of the role that theory and instruments play in scientific observation. His theory of perception yields a new analysis of objectivity that combines the traditional view of observation as the foundation of scientific objectivity with the contemporary recognition that observation is theory-dependent.

Evidence is an objective matter. This is the prevailing view within science, and confirmation theory should aim to capture the objective nature of scientific evidence. Modeling an objective evidence relation in a probabilistic framework faces two challenges: the probabilities must have the right epistemic foundation, and they must be specifiable given the hypotheses and data under consideration. Here I will explore how Sober's (2008, 2009) approach to confirmation handles these challenges of foundation and specification. In particular, I will argue that the specification problem proves especially difficult, and undermines the law of likelihood as an adequate representation of the objective nature of scientific evidence.

This paper argues that our current best cosmological theories, according to which cosmos is very big are compatible with all possible evidence. The problem is unrelated to the Quine-Duhem underdetermination thesis. The compatibility to which this paper draws attention is much more radical: it appears as if all of our best cosmological theories are perfectly probabilistically compatible with all possible evidence and that no empirical discovery could give us any reason whatever to favor one such theory over another. This consequence is absurd. In order to create an evidential link between cosmological theory and observation, a new methodological principle is needed. A candidate for such a principle is proposed, using a Bayesian framework that takes account of observation selection effects. Various applications in other scientific fields are considered.

Cognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories expressed as computer programs. Up to now, computational theories have been formulated by neuroscientists. In this paper, we present a new approach to theory development in neuroscience: the automatic generation and testing of cognitive theories using genetic programming (GP). Our approach evolves from experimental data cognitive theories that explain “the mental program” that subjects use to solve a specific task. As an example, we have focused on a typical neuroscience experiment, the delayed-match-to-sample (DMTS) task. The main goal of our approach is to develop a tool that neuroscientists can use to develop better cognitive theories.

How are reasons and evidence interrelated? According to one prevalent view, reasons and evidence are equivalent: evidence is a reason, and a reason is evidence. On another view reasons and evidence are conditionally related: if there is evidence, then there is a reason. On a different view reasons and evidence are disjunctively related: reasons or evidence can be substituted for each other. In this paper, I argue against these common views, and I defend the view that reasons and evidence are conjunctively related: evidence and reasons are distinguishable yet inseparable. I argue reasons and evidence are distinct because they come apart in certain cases, and I argue reasons and evidence are inseparable because only when properly conjoined are they capable of yielding correct verdicts on important cases in epistemology.

This paper attempts to argue for the theory-ladenness of evidence. It does so by employing and analysing an episode from the history of eighteenth century chemistry. It delineates attempts by Joseph Priestley and Antoine Lavoisier to construct entirely different kinds of evidence for and against a particular hypothesis from a set of agreed upon observations or (raw) data. Based on an augmented version of a distinction, drawn by J. Bogen and J. Woodward, between data and phenomena it is shown that the role of theoretical auxiliary assumptions is very important in constructing evidence for (or against) a theory from observation or (raw) data. In revolutionary situations, rival groups hold radically different theories and theoretical auxiliary assumptions. These are employed to construct very different evidence from the agreed upon set of observations or (raw) data. Hence, theory resolution becomes difficult. It is argued that evidence construction is a multi-layered exercise and can be disputed at any level. What counts as unproblematic observation or (raw) data at one level may become problematic at another level. The contingency of these constructions and the (un)problematic nature of evidence are shown to be partially dependent upon the scientific knowledge that the scientific community possesses.

How are reasons and evidence interrelated? According to one prevalent view, reasons and evidence are equivalent: evidence is a reason, and a reason is evidence. On another view reasons and evidence are conditionally related: if there is evidence, then there is a reason. On a different view reasons and evidence are disjunctively related: reasons or evidence can be substituted for each other. In this paper, I argue against these common views, and I defend the view that reasons and evidence are conjunctively related: evidence and reasons are distinguishable yet inseparable. I argue reasons and evidence are distinct because they come apart in certain cases, and I argue reasons and evidence are inseparable because only when properly conjoined are they capable of yielding correct verdicts on important cases in epistemology.

We use evidence from cognitive psychology and the history of science to examine the issue of the theory-ladenness of perceptual observation. This evidence shows that perception is theory-laden, but that it is only strongly theory-laden when the perceptual evidence is ambiguous or degraded, or when it requires a difficult perceptual judgment. We argue that debates about the theory-ladenness issue have focused too narrowly on the issue of perceptual experience, and that a full account of the scientific process requires an examination of theory-ladenness in attention, perception, data interpretation, data production, memory, and scientific communication. We conclude that the evidence for theory-ladenness does not lead to a relativist account of scientific knowledge.