The Philosophical Foundations of Chapter 24 of The General Theory of Employment, Interest and Money (1936) (GT); The Envisagement of Human Destiny as the Essence of Keynes’s Evolutionary Vision

Physical Probability

Nomic Probability and the Foundations of Induction ◽

10.1093/oso/9780195060133.003.0005 ◽

1990 ◽

Author(s):

John L. Pollock

Keyword(s):

General Theory ◽

Decision Theory ◽

Everyday Life ◽

Subjective Probability ◽

Relative Frequency ◽

Probabilistic Reasoning ◽

Objective Probability ◽

Problem Of Induction ◽

Philosophical Foundations ◽

Statistical Induction

Probability theorists divide into two camps-the proponents of subjective probability and the proponents of objective probability. Opinion has it that subjective probability has carried the day, but I think that such a judgment is premature. I have argued elsewhere that there are deep incoherencies in the notion of subjective probability. Accordingly, I find myself in the camp of objective probability. The consensus is, however, that the armies of objective probability are in even worse disarray. The purpose of this book is to construct a theory of objective probability that rectifies that. Such a theory must explain the meaning of objective probability, show how we can discover the values of objective probabilities, clarify their use in decision theory, and demonstrate how they can be used for epistemological purposes. The theory of nomic probability aims to do all that. This book has two main objectives. First, it will propose a general theory of objective probability. Second, it will, in a sense to be explained, propose a solution to the problem of induction. These two goals are intimately connected. I will argue that a solution to the problem of induction is forthcoming, ultimately, from an analysis of probabilistic reasoning. Under some circumstances, probabilistic reasoning justifies us in drawing non-probabilistic conclusions, and this kind of reasoning underlies induction. Conversely, an essential part of understanding probability consists of providing an account of how we can ascertain the values of probabilities, and the most fundamental way of doing that is by using a species of induction. In statistical induction we observe the relative frequency (the proportion) of A's in a limited sample of B's, and then infer that the probability of a B being an A is approximately the same as that relative frequency. To provide philosophical foundations for probability we must, among other things, explain precisely how statistical induction works and what justifies it. Probability is important both in and out of philosophy. Much of the reasoning of everyday life is probabilistic. We look at the clouds and judge whether it is going to rain by considering how often clouds like that have spawned rain in the past.

Download Full-text

General theory of topological explanations and explanatory asymmetry

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2019.0321 ◽

2020 ◽

Vol 375 (1796) ◽

pp. 20190321 ◽

Cited By ~ 3

Author(s):

Daniel Kostić

Keyword(s):

Biological Sciences ◽

General Theory ◽

Biological Networks ◽

Topological Property ◽

Dynamical Property ◽

Second Step ◽

Theme Issue ◽

Philosophical Foundations ◽

The Third ◽

System A

In this paper, I present a general theory of topological explanations, and illustrate its fruitfulness by showing how it accounts for explanatory asymmetry. My argument is developed in three steps. In the first step, I show what it is for some topological property A to explain some physical or dynamical property B . Based on that, I derive three key criteria of successful topological explanations: a criterion concerning the facticity of topological explanations, i.e. what makes it true of a particular system; a criterion for describing counterfactual dependencies in two explanatory modes, i.e. the vertical and the horizontal and, finally, a third perspectival one that tells us when to use the vertical and when to use the horizontal mode. In the second step, I show how this general theory of topological explanations accounts for explanatory asymmetry in both the vertical and horizontal explanatory modes. Finally, in the third step, I argue that this theory is universally applicable across biological sciences, which helps in unifying essential concepts of biological networks. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.

Download Full-text

Extreme self-sacrifice beyond fusion: Moral expansiveness and the special case of allyship

Behavioral and Brain Sciences ◽

10.1017/s0140525x18001620 ◽

2018 ◽

Vol 41 ◽

Cited By ~ 2

Author(s):

Daniel Crimston ◽

Matthew J. Hornsey

Keyword(s):

General Theory ◽

Biological Markers ◽

Natural Environment ◽

Relevant Dimension ◽

Special Case

AbstractAs a general theory of extreme self-sacrifice, Whitehouse's article misses one relevant dimension: people's willingness to fight and die in support of entities not bound by biological markers or ancestral kinship (allyship). We discuss research on moral expansiveness, which highlights individuals’ capacity to self-sacrifice for targets that lie outside traditional in-group markers, including racial out-groups, animals, and the natural environment.

Download Full-text