What Foundations for Statistical Modeling and Inference?

The primary aim of this article is to review the above books in a comparative way from the standpoint of my perspective on empirical modeling and inference. 1 Hacking (1965). Logic of Statistical Inference 2. Mayo (2018). Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars 3. Conclusion

Philosophy of Probability and Statistical Modeling

This book has two main aims. The first one (chapters 1-7) is an historically informed review of the philosophy of probability. It describes recent historiography, lays out the distinction between subjective and objective notions, and concludes by applying the historical lessons to the main interpretations of probability. The second aim (chapters 8-13) focuses entirely on objective probability, and advances a number of novel theses regarding its role in scientific practice. A distinction is drawn between traditional attempts to interpret chance, and a novel methodological study of its application. A radical form of pluralism is then introduced, advocating a tripartite distinction between propensities, probabilities and frequencies. Finally, a distinction is drawn between two different applications of chance in statistical modelling which, it is argued, vindicates the overall methodological approach. The ensuing conception of objective probability in practice is the ‘complex nexus of chance’

Confirmation, Decision, and Evidential Probability

Henry Kyburg’s theory of Evidential Probability offers a neglected tool for approaching problems in confirmation theory and decision theory. I use Evidential Probability to examine some persistent problems within these areas of the philosophy of science. Formal tools in general and probability theory in particular have great promise for conceptual analysis in confirmation theory and decision theory, but they face many challenges. In each chapter, I apply Evidential Probability to a specific issue in confirmation theory or decision theory. In Chapter 1, I challenge the notion that Bayesian probability offers the best basis for a probabilistic theory of evidence. In Chapter 2, I criticise the conventional measures of quantities of evidence that use the degree of imprecision of imprecise probabilities. In Chapter 3, I develop an alternative to orthodox utility-maximizing decision theory using Kyburg’s system. In Chapter 4, I confront the orthodox notion that Nelson Goodman’s New Riddle of Induction makes purely formal theories of induction untenable. Finally, in Chapter 5, I defend probabilistic theories of inductive reasoning against John D. Norton’s recent collection of criticisms. My aim is the development of fresh perspectives on classic problems and contemporary debates. I both defend and exemplify a formal approach to the philosophy of science. I argue that Evidential Probability has great potential for clarifying our concepts of evidence and rationality

Arguing for wisdom in the university: an intellectual autobiography

For forty years I have argued that we urgently need to bring about a revolution in academia so that the basic task becomes to seek and promote wisdom. How did I come to argue for such a preposterously gigantic intellectual revolution? It goes back to my childhood. From an early age, I desired passionately to understand the physical universe. Then, around adolescence, my passion became to understand the heart and soul of people via the novel. But I never discovered how to tell stories in order to tell the truth. So, having failed to become a physicist, and failed to become a novelist, I studied philosophy at Manchester University and then, in six weeks of inspiration, discovered that the riddle of the universe is the riddle of our desires. Philosophy should be about how to live, and should not just do conceptual analysis. I struggled to reconcile the two worlds of my childhood ambitions, the physical universe and the human world. I decided they could be reconciled with one another if one regarded the two accounts of them, physics and common sense, as myths, and not as literal truths. But then I discovered Karl Popper: truth is too important to be discarded. I revised my ideas: physics seeks to depict truly only an aspect of all that there is; in addition, there is the aspect of the experiential features of the world as we experience it. I was immensely impressed with Popper’s view that science makes progress, not by verification, but by ferocious attempted falsification of theories. I was impressed, too, with his generalization of this view to form critical rationalism. Then it dawned on me: Popper’s view of science is untenable because it misrepresents the basic aim of science. This is not truth as such; rather it is explanatory truth – truth presupposed to be unified or physically comprehensible. We need, I realized, a new conception of science, called by me aim-oriented empiricism, which acknowledges the real, problematic aims of science, and seeks to improve them. Then, treading along a path parallel to Popper’s, I realized that aim-oriented empiricism can be generalized to form a new conception of rationality, aim-oriented rationality, with implications for all that we do. This led on to a new conception of academic inquiry. From the Enlightenment we have inherited the view that academia, in order to help promote human welfare, must first acquire knowledge. But this is profoundly and damagingly irrational. If academia really does seek to help promote human welfare, then its primary tasks must be to articulate problems of living, and propose and critically assess possible solutions – possible actions, policies, political programmes, philosophies of life. The pursuit of knowledge is secondary. Academia needs to promote cooperatively rational problem solving in the social world, and needs to help humanity improve individual and institutional aims by exploiting aim-oriented rationality, arrived at by generalizing the real progress-achieving methods of science. We might, as a result, get into life some of the progressive success that is such a marked feature of science. Thus began my campaign to promote awareness of the urgent need for a new kind of academic inquiry rationally devoted to helping humanity create a wiser world

Michael Polanyi's theory of tacit knowledge: An epistemology of skill in science.

How can we claim to know and even tenaciously hold in science what we might possibly doubt. Standard methodologies of science have not answered this question persuasively. They either propose an answer that misrepresents science or they propose an irrational approach to science. The reason for these two extreme positions is that the accounts of science in these methodologies are based on a false ideal of objectivism - an assumption that the success of science as a branch of human knowledge is based on it being objective in the sense of being impersonal. Michael Polanyi propounds a theory of tacit knowledge, and I claim that this theory provides the best answer to the above question in that it represents scientific activity accurately and rationally. Polanyi rebuttals the false ideal of objectivism/impersonalism in scientific knowledge with a richer account of actual scientific practice. I show that he restores heuristics, and accounts for the role of skill without thereby succumbing to psychologism/subjectivism. I explore Collins and Pinch's claim that controversy is central to scientific progress, and critically examine Mwamba's book length study of Polanyi. I tackle the objections made by the Popperians (notably Alan Musgrave) to Polanyi's theory and the alternative methodology provided by Imre Lakatos/Elie Zahar. I argue that Popperianistic methodologies present incomplete accounts of science. Instead, understanding the nature and functions of tacit knowledge provides a richer epistemology of science. Further, the theory provides grounds for re-tackling the perennial problem of skepticism. In the theory, every act of knowledge is a skilful act and whenever we can point out that we know, we affirm our ways of knowing. Thus removed from the false ideal of objectivism, we are closer to resolving skepticism. The thesis is also an introduction to the still nascent philosophy of Michael Polanyi to analytic philosophy. It is akin to but not identical with Thomas Kuhn's philosophy of science

PSA 2016

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2016

Destructive realism: Metaphysics as the foundation of natural science

This thesis has two philosophical positions as its targets. The first is 'scientific realism' of the form defended by Boyd, (the early) Putnam, and most recently Psillos. The second is empiricism in the vein of Mill, Mach, Ayer, Carnap, and Van Fraassen. My objections to both have a rather Popperian flavour. For I argue that 'confirmation' is a misnomer, that so-called 'ampliative inferences' are heuristics at best, and that naturalism and subjectivism are regressive doctrines. At the heart of genuine realism, I argue, is a stance on the issues of perception and conception. In particular, I hold that to be a realist is to reject the notion that there are representations which have some sort of epistemic priority. And along related lines, I maintain that the closely aligned doctrine of physicalism cannot simply be presupposed. What this amounts to is that the search for some sort of 'solid foundation' for knowledge' is a futile enterprise. Such a foundation would be unimportant, even if there were to be one, and we ought to be free to critically examine any claim we like. So rather than sapere aude, I would have 'dare to err', and place an intersubjective emphasis on inquiry. And this goes for metaphysics, logic, and mathematics, as well as for natural science. Yet I also advocate the view that we ought to be optimistic about our ability to find the truth, ceteris paribus. And to this end, I argue that we should accept that our faculty of conception is sufficient to allow us to connect with the possibilities of being, whereas our faculty of sense is sufficient to allow us to connect with that which is actual; this, given considerable critical struggle on our parts, both individually and collectively. I urge that it is methodologically advisable to behave as if this is so, if we are not to асһieve only the self-paralysis of the Pyrrhonist. In a nutshell, destructive realism says that natural science progresses by ruling out possibilities, in particular by ruling out possible worlds as candidates for the actual world, but that this is a two-stage process, involving both an a priori (metaphysical) and an a posteriori (observational) component. The aim of natural science is to eliminate false theories. Its aspiration is truth