Online research in philosophy

The scarcity of resources required to produce justice is manifested in the relation between the accuracy, depth, and scope of materially possible forms of justice. Ceteris paribus , increases in the accuracy of justice must come at the expense of its depth and scope, and vice versa, though they are not linearly proportioned. The accuracy of justice is the degree of agreement between the possible results of attempts to implement a theory or principles of justice and the desired result according to that theory or those principles of justice. The scope of justice measures how broadly the principle or theory of justice is intended to apply. The depth of justice measures the gap between existing social norms and the theory or principles of justice we examine within the specified scope. This three-dimensional model explains public policies, laws, and regulations that increase the scope or depth of justice at the cost of a decrease in its accuracy – rough forms of justice such as measures of transitional justice, affirmative action, mandatory sentencing, simplified tax codes, collective guilt and victimhood, and general amnesties. The scarcity of resources necessary for justice can contract or expand. The normative choice between principles of justice that prefer accuracy and those that favor scope or depth usually corresponds, respectively, with rights-based deontological theories and consequentialist ethics.

The nature of the connection between theory and observation has been a major source of difficulty for philosophers of science. It is most vexing for those who would reduce the terms of a theory to those of an observation language, e.g. Carnap, Braithwaite, and Nagel. Carnap's work, particularly his treatment of physical theories as partially interpreted formalisms, forms the point of focus of this paper. Carnap attempted to make the connection between theory and observation through correspondence postulates. It is pointed out that such postulates depend in critical ways upon theoretical truths. This particular type of theoretical dependence produces serious trouble for Carnap's approach. For reasons given it may make it untenable. Furthermore, this problem when generalized creates difficulty for any similar reductionist program. Not only is this kind of theoretical dependence pointed out, but more important, the logical conditions which produce it are revealed. In this way light is shed upon the formal characteristics of the notion of theory dependence, especially upon the way in which observation terms depend upon theories for their meaning.

Learners are able to use 2 different types of knowledge to perform a skill. One type is a conscious mental model, and the other is based on memories of instances. The authors conducted 3 experiments that manipulated training conditions designed to affect the availability of 1 or both types of knowledge about an artificial grammar. Participants were tested for both speed and accuracy of their ability to generate letter sequences. Results indicate that model-based training leads to slow accurate responding. Memorybased training leads to fast, less accurate responding and highest achievement when perfect accuracy was not required. Evidence supports participants’ preference for using the memory-based mode when exposed to both types of training. Finally, the accuracy contributed by model-based training declined over a retention interval.

This paper describes a theory of accuracy or approximate truth and applies it to problems in the realist interpretation of scientific theories. It argues not only that realism requires approximate truth, but that an adequate theory of approximation also presupposes some elements of a realist interpretation of theories. The paper distinguishes approximate truth from vagueness, probability and verisimilitude, and applies it to problems of confirmation and deduction from inaccurate premises. Basic results are cited, but details appear elsewhere. Objections are surveyed, including arguments by Miller, Laymon, and Laudan. Comparison is made with Niiniluoto's theory of verisimilitude, and the utility of his theory for realism assessed.

The paper gives an overview of key themes of twentieth century philosophical treatment of the language of science, with special emphasis on the meaning variance of scientific terms and the comparison of alternative theories. These themes are dealt with via discussion of the topics of: (a) the logical positivist principle of verifiability and the problem of the meaning of theoretical terms, (b) the postpositivist thesis of semantic incommensurability, and (c) the scientific realist response to incommensurability based on the causal theory of reference.

I shall specify about what we are thinking when we are talking about regulating something by specifying accuracy conditions. The main thesis is that we couldn’t describe representational relations as perceptual relationships if we lack a normative conception of relationships between representing and represented. Hence, searching for what it is assessable for accuracy depends on specifying the kind of intentional content which is normatively individuated and attributed.

This paper makes a modest point. Suppose one wants to evaluate alternative policies, institutions or even constitutions on the basis of their consequences. To do so, one needs to evaluate their consequences and one needs to know what their consequences are. Let us suppose that the role of economic theories and game theory in particular is mainly to help us to use information we already possess or that we can acquire at a reasonable cost to judge what the consequences will be. We do not necessarily need true theories or theories that provide perfectly precise predictions. What sort of accuracy and precision we need depends on how the consequences of alternative policies are evaluated. The worth of an economic theory in this context of policy assessment depends on the accuracy of the predictions the theory permits, the costs of gathering the needed information, and the costs of learning and using the theory. My only excuse for uttering these truisms is that well known economists and philosophers have denied them.

D. Miller's demonstrations of the language dependence of truthlikeness raise a profound problem for the claim that scientific progress is objective. In two recent papers (Barnes 1990, 1991) I argue that the objectivity of progress may be grounded on the claim that the aim of science is not merely truth but knowledge; progress thus construed is objective in an epistemic sense. In this paper I construct a new solution to Miller's problem grounded on the notion of "approximate causal explanation" which allows for linguistically invariant progress outside an epistemic context. I suggest that the notion of "approximate causal explanation" provides the resources for a more robust theory of progress than that provided by the notion of "approximate truth.".

In this talk, I will explain why only one of Miller’s two types of language-dependence-of-verisimilitude problems is a (potential) threat to the sorts of accuracy-dominance approaches to coherence that I’ve been discussing.

This paper proposes a solution to David Miller's Minnesotan-Arizonan demonstration of the language dependence of truthlikeness (Miller 1974), along with Miller's first-order demonstration of the same (Miller 1978). It is assumed, with Peter Urbach, that the implication of these demonstrations is that the very notion of truthlikeness is intrinsically language dependent and thus non-objective. As such, truthlikeness cannot supply a basis for an objective account of scientific progress. I argue that, while Miller is correct in arguing that the number of true atomic sentences of a false theory is language dependent, the number of known sentences (under certain straightforward assumptions) is conserved by translation; degree of knowledge, unlike truthlikeness, is thus a linguistically invariant notion. It is concluded that the objectivity of scientific progress must be grounded on the fact (noted in Cohen 1980) that knowledge, not mere truth, is the aim of science.