Online research in philosophy

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.

In this note, I consider various precisifications of the slogan ‘evidence of evidence is evidence’. I provide counter-examples to each of these precisifications (assuming an epistemic probabilistic relevance notion of ‘evidential support’).

A theory of evidential probability is developed from two assumptions:(1) the evidential probability of a proposition is its probability conditional on the total evidence;(2) one's total evidence is one's total knowledge. Evidential probability is distinguished from both subjective and objective probability. Loss as well as gain of evidence is permitted. Evidential probability is embedded within epistemic logic by means of possible worlds semantics for modal logic; this allows a natural theory of higher-order probability to be developed. In particular, it is emphasized that it is sometimes uncertain which propositions are part of one's total evidence; some surprising implications of this fact are drawn out.

The question of whether or not to partition data for the purposes of inferring phylogenetic hypotheses remains controversial. Opinions have been especially divided since Kluge's (1989, Systematic Zoology 38, 7–25) claim that data partitioning violates the requirement of total evidence (RTE). Unfortunately, advocacy for or against the RTE has not been based on accurate portrayals of the requirement. The RTE is a basic maxim for non-deductive inference, stipulating that evidence must be considered if it has relevance to an inference. Evidence is relevant if it has a positive or negative effect on a given conclusion. In the case of ℈partitioned’ phylogenetic inferences, the RTE is violated, and the basis for rational belief in any conclusion is compromised, unless it is shown that the partitions are evidentially irrelevant to one another. The goal of phylogenetic systematics is to hypothesize past causal conditions to account for observed shared similarities among two or more species. Such inferences are non-deductive, necessitating consideration of the RTE. Some phylogeneticists claim the parsimony criterion as justification for the RTE. There is no relation between the two – parsimony is a relation between a hypothesis and causal question(s). Parsimony does not dictate the content of premises prior to an inference. ℈Taxonomic congruence,’ ℈supertrees,’ and ℈conditional combination’ methods violate the RTE. Taxonomic congruence and supertree methods also fail to achieve the intended goal of phylogenetic inference, such that ℈consensus trees’ and ℈supertrees’ lack an empirical basis. ℈Conditional combination’ is problematic because hypotheses derived from partitioned data cannot be compared – a causal hypothesis inferred to account for a set of effects only has relevance to those effects, not any comparative relevance to other causal hypotheses. A similar problem arises in the comparisons of hypotheses derived from different causal 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.

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.

Some prominent accounts of scientific evidence treat evidence as an unrelativized concept. But whether belief in a hypothesis is justified seems relative to the epistemic situation of the believer. The issue becomes yet more complicated in the context of group epistemic agents, for then one confronts the problem of relativizing to an epistemic situation that may include conflicting beliefs. As a step toward resolution of these difficulties, an ideal of justification is here proposed that incorporates both an unrelativized evidence requirement and the requirement of the security of the evidence on which a conclusion from data is based. The latter requirement incorporates the consideration of epistemic modal statements.

In this paper I argue for a version of the Total Evidence view according to which the rational response to disagreement depends upon one's total evidence. I argue that perceptual evidence of a certain kind is significantly weightier than many other types of evidence, including testimonial. Furthermore, what is generally called "The Uniqueness Thesis" is actually a conflation of two distinct principles that I dub "Evidential Uniqueness" and "Rationality Uniqueness." The former principle is likely true but the latter almost certainly false. Seeing why the Rationality Uniqueness fails opens the door to seeing how mutual reasonable disagreement is possible even among those who share the same evidence.

Your evidence constrains your rational degrees of confidence both locally and globally. On the one hand, particular bits of evidence can boost or diminish your rational degree of confidence in various hypotheses, relative to your background information. On the other hand, epistemic rationality requires that, for any hypothesis h, your confidence in h is proportional to the support that h receives from your total evidence. Why is it that your evidence has these two epistemic powers? I argue that various proposed accounts of what it is for something to be an element of your evidence set cannot answer this question. I then propose an alternative account of what it is for something to be an element of your evidence set. 1 Introduction 2 The elements of one's evidence set are propositions 3 Which kinds of propositions are in one's evidence set? 3.1 Doxastic accounts of evidence 3.2 Non-doxastic accounts of evidence 4 Elaborating and defending the LIE CiteULike    Connotea    Del.icio.us    What's this?

The meaning and justification of the requirement of total evidence are examined. It is argued that there are several significantly different interpretations of the requirement, but each interpretation makes the requirement highly suspect. For any of the usual interpretations of the requirement, it would be quite unreasonable to conduct inquiry in such a way as to fulfill it. It is then suggested that the rational inquirer should seek the optimal amount of evidence, rather than all the evidence. This raises the problems surrounding the idea of scientific or epistemic utility.