Online research in philosophy

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. (shrink)

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. (shrink)

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. (shrink)

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. (shrink)

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? (shrink)

Bechtel and Mundale (1999) argue that multiple realizability is not plausible. They point out that neuroscientists assume that psychological traits are realized similarly in homologous brain structures and contend that a biological aspect of the brain that is relevant to neuropsychological state individuation provides evidence against multiple realizability. I argue that Bechtel and Mundale adduce the wrong sort of evidence against multiple realizability. Homologous traits do not provide relevant evidence. It is homoplasious traits of brains that can provide evidence for (...) or against multiple realizability. (shrink)

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. (shrink)

Confirmation theory is the study of the logic by which scientific hypotheses may be confirmed or disconfirmed, or even refuted by evidence. A specific theory of confirmation is a proposal for such a logic. Presumably the epistemic evaluation of scientific hypotheses should largely depend on their empirical content – on what they say the evidentially accessible parts of the world are like, and on the extent to which they turn out to be right about that. Thus, all theories of confirmation (...) rely on measures of how well various alternative hypotheses account for the evidence.1 Most contemporary confirmation theories employ probability functions to provide such a measure. They measure how well the evidence fits what the hypothesis says about the world in terms of how likely it is that the evidence should occur were the hypothesis true. Such hypothesis-based probabilities of evidence claims are called likelihoods. Clearly, when the evidence is more likely according to one hypothesis than according to an alternative, that should redound to the credit of the former hypothesis and the discredit of the later. But various theories of confirmation diverge on precisely how this credit is to be measured? (shrink)

In Bayesian epistemology, the concept of one proposition’s being evidence for another is explained along the following lines. Given a measure of degrees of confidence, con(...), that conforms to standard probability axioms: (EV) a proposition e is evidence for a proposition h iff con(h|e) is greater than con(h). (Con(h|e) is the degree of confidence in h given e, and is defined as con(h and e)/con(e).) Proposals along these lines, however, have been dogged by what Clark Glymour called the Problem of (...) Old Evidence.[i] (EV) apparently precludes a theory being confirmed by evidence that is already in. For if a potentially evidential proposition, e, is already known, then con(e)=1. One can be subjectively certain of propositions already known to be true. But by definition of con(h|e), where con(e)=1, con(h|e) will always be equal to, and hence never greater than, con(h). Not only does (EV) preclude one from confirming new theories on the basis of information already gathered. Suppose Q is some proposition of which we are now uncertain, but which is evidence for a scientific hypothesis P. That is, con(P|Q) is greater than con(P). If we now devise an experiment to test whether Q, perform the experiment, and become certain that Q, it will no longer count as evidence for P. Thus, if we accept (EV), gathering new evidence to support a theory actually has quite the opposite effect. Gathering the evidence destroys its quality as evidence. (shrink)