The paper assumes that to be of practical interest process must be understood as physical action that takes place in the world rather than being an idea in the mind. It argues that if an ontology of process is to accommodate actuality, it must be represented in terms of relative probabilities. Folk physics cannot accommodate this, and so the paper appeals to scientific culture because it is an emergent knowledge of the world derived from action in it. Process is represented (...) as a contradictory probability distribution that does not depend on a spatio-temporal frame. An actuality is a probability density that grounds the values of probabilities to constitute their distributions. Because probability is a conserved value, probability distributions are subject to the constraint of symmetry and must be zero-sum. An actuality is locked-in by other actualities to become a zero-sum symmetry of probability values. It is shown that the locking-in of actualities constructs spatio-temporal locality, lends actualities specificity, and makes them a contradiction. Localization is the basis for understanding empirical observation. Because becoming depends on its construction of being, processes exist as trajectories. The historical trajectories of evolution and revolution as well as the non-historical trajectory of strong emergence are how processes are observed to exist. (shrink)

We argue that quantum theory does not allow for a generalization of the notion of classical conditional probability by showing that the probability defined by the Lüders rule, standardly interpreted in the literature as the quantum-mechanical conditionalization rule, cannot be interpreted as such.

The Indifference Principle, its Paradoxes and Kolmogorov's Probability Space.

Epistemic modal operators give rise to something very like, but also very unlike, Moore's paradox. I set out the puzzling phenomena, explain why a standard relational semantics for these operators cannot handle them, and recommend an alternative semantics. A pragmatics appropriate to the semantics is developed and interactions between the semantics, the pragmatics, and the definition of consequence are investigated. The semantics is then extended to probability operators. Some problems and prospects for probabilistic representations of content and context are explored.

This paper develops a critical response to John Beatty’s recent (2006) engagement with Stephen Jay Gould’s claim that evolutionary history is contingent. Beatty identifies two senses of contingency in Gould’s work: an unpredictability sense and a causal dependence sense. He denies that Gould associates contingency with stochastic phenomena, such as drift. In reply to Beatty, this paper develops two main claims. The first is an interpretive claim: Gould really thinks of contingency has having to do with stochastic effects at the (...) level of macroevolution, and in particular with unbiased species sorting. This notion of contingency as macro-level stochasticity incorporates both the causal dependence and the unpredictability senses of contingency. The second claim is more substantive: Recent attempts by other scientists to put Gould’s claim to the test fail to engage with the hypothesis that species sorting sometimes resembles a lottery. Gould’s claim that random sorting is a significant macroevolutionary phenomenon remains an intriguing and largely untested live hypothesis about evolution. (shrink)

Precautionary Principles are often said to be appropriate for decision-making in contexts of uncertainty such as climate policy. Contexts of uncertainty are contrasted to contexts of risk depending on whether we have probabilities or not. Against this view, I argue that the risk-uncertainty distinction is practically irrelevant. I start by noting that the history of the distinction between risk and uncertainty is more varied than is sometimes assumed. In order to examine the distinction, I unpack the idea of having probabilities, (...) in particular by distinguishing three interpretations of probability: objective, epistemic, and subjective probability. I then claim that if we are concerned with whether we have probabilities at all—regardless of how low their epistemic credentials are—then we almost always have probabilities for policy-making. The reason is that subjective and epistemic probability are the relevant interpretations of probability and we almost always have subjective and epistemic probabilities. In contrast, if we are only concerned with probabilities that have sufficiently high epistemic credentials, then we obviously do not always have probabilities. Climate policy, for example, would then be a case of decision-making under uncertainty. But, so I argue, we should not dismiss probabilities with low epistemic credentials. Rather, when they are the best available probabilities our decision principles should make use of them. And, since they are almost always available, the risk-uncertainty distinction remains irrelevant. (shrink)

We claim that if a complete philosophy of evidence-based practice is intended, then attention to the nature of causation in health science is necessary. We identify how health science currently conceptualises causation by the way it prioritises some research methods over others. We then show how the current understanding of what causation is serves to constrain scientific progress. An alternative account of causation is offered. This is one of dispositionalism. We claim that by understanding causation from a dispositionalist stance, many (...) of the processes within an evidence-based practice framework are better accounted for. Further, some of the problems associated with the health research, e.g. external validity of causal findings, dissolve. (shrink)

A common objection to the Molinist account of divine providence states that counterfactuals of creaturely freedom lack grounds. Some Molinists appeal to brute counterfactual facts about the subject of the CCF in order to ground CCFs. Others argue that CCFs are grounded by the subject's actions in nearby worlds. In this article, I argue that Open Theism's account of divine providence employs would-probably conditionals that are most plausibly grounded by either brute facts about the subject of these conditionals or non-actual (...) entities. As a result, Open Theism's revision of the traditional notion of divine providence is unmotivated. The Molinist can ground CCFs just as easily as the Openist can ground would-probably conditionals but the Molinist has the advantage of maintaining a robust account of divine providence.Send article to KindleTo send this article to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle. Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply. Find out more about the Kindle Personal Document Service.On grounding God's knowledge of the probableVolume 49, Issue 1JENNIFER JENSEN DOI: https://doi.org/10.1017/S0034412512000182Your Kindle email address Please provide your Kindle [email protected]@kindle.com Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Dropbox To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Dropbox. On grounding God's knowledge of the probableVolume 49, Issue 1JENNIFER JENSEN DOI: https://doi.org/10.1017/S0034412512000182Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Google Drive To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Google Drive. On grounding God's knowledge of the probableVolume 49, Issue 1JENNIFER JENSEN DOI: https://doi.org/10.1017/S0034412512000182Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Export citation Request permission. (shrink)

We argue that quantum theory does not allow for a generalization of the notion of classical conditional probability by showing that the probability defined by the Lüders rule, standardly interpreted in the literature as the quantum-mechanical conditionalization rule, cannot be interpreted as such.Argumentamos que la teoría cuántica no admite una generalización de la noción clásica de probabilidad condicionada. Mostramos que la probabilidad definida por la regla de Lüders, interpretada generalmente como la regla de condicionalización mecánico-cuántica, no puede ser interpretada como (...) tal. (shrink)

GRW Theory postulates a stochastic mechanism assuring that every so often the wave function of a quantum system is `hit', which leaves it in a localised state. How are we to interpret the probabilities built into this mechanism? GRW theory is a firmly realist proposal and it is therefore clear that these probabilities are objective probabilities (i.e. chances). A discussion of the major theories of chance leads us to the conclusion that GRW probabilities can be understood only as either single (...) case propensities or Humean objective chances. Although single case propensities have some intuitive appeal in the context of GRW theory, on balance it seems that Humean objective chances are preferable on conceptual grounds because single case propensities suffer from various well know problems such as unlimited frequency tolerance and lack of a rationalisation of the principal principle. (shrink)

The Razor says: do not multiply entities without necessity! The Laser says: do not multiply fundamental entities without necessity! Behind the Laser lies a deep insight. This is a distinction between the costs and the commitments of a theory. According to the Razor, every commitment is a cost. Not so according to the Laser. According to the Laser, derivative entities are an ontological free lunch: that is, they are a commitment without a cost. Jonathan Schaffer (2015) has argued that the (...) Laser should replace the Razor. In Sections 2-4 we shall discuss and argue against Schaffer’s arguments for replacing the Razor with the Laser. Schaffer considers several objections to his views, and in Sections 5-7 we shall argue that Schaffer does not deal successfully with two of them. In Section 8 we shall present a probabilistic argument for the Laser. However, the argument has a limitation and does not support the replacement of the Razor with the Laser. Indeed, it supports only the claim that, given certain assumptions, the multiplication of explanatorily relevant derivative entities does not matter; but, as we argue in the same section, there is an argument that multiplying explanatorily superfluous derivative entities does makes a theory less rationally acceptable. Our conclusion is that the Laser cannot replace the Razor and that derivative entities are not an ontological free lunch. (shrink)

A widespread assumption in the contemporary discussion of probabilistic models of cognition, often attributed to the Bayesian program, is that inference is optimal when the observer's priors match the true priors in the world—the actual “statistics of the environment.” But in fact the idea of a “true” prior plays no role in traditional Bayesian philosophy, which regards probability as a quantification of belief, not an objective characteristic of the world. In this paper I discuss the significance of the traditional Bayesian (...) epistemic view of probability and its mismatch with the more objectivist assumptions about probability that are widely held in contemporary cognitive science. I then introduce a novel mathematical framework, the observer lattice, that aims to clarify this issue while avoiding philosophically tendentious assumptions. The mathematical argument shows that even if we assume that “ground truth” probabilities actually do exist, there is no objective way to tell what they are. Different observers, conditioning on different information, will inevitably have different probability estimates, and there is no general procedure to determine which one is right. The argument sheds light on the use of probabilistic models in cognitive science, and in particular on what exactly it means for the mind to be “tuned” to its environment. (shrink)

The idea that perceptual and cognitive systems must incorporate knowledge about the structure of the environment has become a central dogma of cognitive theory. In a Bayesian context, this idea is often realized in terms of “tuning the prior”—widely assumed to mean adjusting prior probabilities so that they match the frequencies of events in the world. This kind of “ecological” tuning has often been held up as an ideal of inference, in fact defining an “ideal observer.” But widespread as this (...) viewpoint is, it directly contradicts Bayesian philosophy of probability, which views probabilities as degrees of belief rather than relative frequencies, and explicitly denies that they are objective characteristics of the world. Moreover, tuning the prior to observed environmental frequencies is subject to overfitting, meaning in this context overtuning to the environment, which leads (ironically) to poor performance in future encounters with the same environment. Whenever there is uncertainty about the environment—which there almost always is—an agent's prior should be biased away from ecological relative frequencies and toward simpler and more entropic priors. (shrink)

In the contemporary philosophical debate about probability, one of the main problems con‐ cerns the relation between objective probability and determinism. Is it possible for objective probability and determinism to co‐exist? this is one of the questions this dispute tries to answer. the scope of discussion is conducted between advocates of a positive answer (com‐ patibilist) and co‐existence opponents (incompatibilist). In the early twentieth century, many logicians also developed topics regarding probability and determinism. One of them was the outstanding Polish (...) logician and philosopher — Jan Łukasiewicz. the general purpose of this paper is to analyse and implement Łukasiewicz’s views regarding determinism and probability in the contemporary eld of this problem. I will try to show the relation between his interpre‐ tations of these concepts and in consequence his attempt to con ont them. As a result of the above analysis, I present some di erent positions (located in the elds of logic and semantics) in the contemporary discourse about the relation between objective probability and determi‐ nism. moreover, I will present Łukasiewicz’s views about this relation and the consequence of these solutions in the eld of logic. (shrink)

Proponents of Bayesian confirmation theory believe that they have the solution to a significant, recalcitrant problem in philosophy of science. It is the identification of the logic that governs evidence and its inductive bearing in science. That is the logic that lets us say that our catalog of planetary observations strongly confirms Copernicus’ heliocentric hypothesis; or that the fossil record is good evidence for the theory of evolution; or that the 3oK cosmic background radiation supports big bang cosmology. The definitive (...) solution to this problem would be a significant achievement. The problem is of central importance to philosophy of science, for, in the end, what distinguishes science from myth making is that we have good evidence for the content of science, or at least of mature sciences, whereas myths are evidentially ungrounded fictions. The core ideas shared by all versions of Bayesian confirmation theory are, at a good first approximation, that a scientist’s beliefs are or should conform to a probability measure; and that the incorporation of new evidence is through conditionalization using Bayes’ theorem. While the burden of this chapter will be to inventory why critics believe this theory may not be the solution after all, it is worthwhile first to summarize here the most appealing virtues of this simple account. There are three. First, the theory reduces the often nebulous notion of a logic of.. (shrink)

This is an extensive review of recent work on the foundations of statistical mechanics.

The idea that probability is a degree of rational belief seemed too vague for a foundation of a mathematical theory. It was certainly not obvious that degrees of rational belief had to be governed by the probability axioms as used by Laplace and other prestatistical probabilityst. The axioms seemed arbitrary in their interpretation. To eliminate the arbitrariness, the stat- isticians of the early 20th century drastically restricted the possible applications of the probability theory, by insisting that probabilities had to be (...) interpreted as relative frequencies, which obviously satisfied the probability axioms, and so the arbitrariness was removed. But the frequentist approach turned more subjective than the prestatistical approach, because the identifications of outcome spaces, the choices of test statistics, the declarations of what rejection regions are, the choices of null-hypothesis among alternatives, the contradictory choices between sizes and powers etc., depend on thoughts or even whims of the experimenter. Frequentists thus failed to solve the problems that motivated their approach, they even exacerbated them. The subjective Bayesianism of Ramsey and de Finetti did not solve the problems either. Finally Cox provided the missing foundation for probability as a degree of rational belief, which makes the Bayesian probability theory (which is based on this foundation) the best theory of probable inference we have. Hence, it is quite unbelievable that it is not even mentioned in recent philosophy textbooks devoted to the probable inference. The reason could be that it requires fairly sophisticated mathematics. But not even to mention it? We explain the history and prove Cox theorem in a novel way. (shrink)

A common view among nontheists combines the de jure objection that theism is epistemically unacceptable with agnosticism about the de facto objection that theism is false. Following Plantinga, we can call this a “proper” de jure objection—a de jure objection that does not depend on any de facto objection. In his Warranted Christian Belief, Plantinga has produced a general argument against all proper de jure objections. Here I first show that this argument is logically fallacious (it makes subtle probabilistic fallacies (...) disguised by scope ambiguities), and proceed to lay the groundwork for the construction of actual proper de jure objections. (shrink)

The history of the mathematical probability includes two phases: 1) From Pascal and Fermat to Laplace, the theory gained in application fields; 2) In the first half of the 20th Century, two competing axiomatic systems were respectively proposed by von Mises in 1919 and Kolmogorov in 1933. This paper places this historical sketch in the context of the philosophical complexity of the probability concept and explains the resounding success of Kolmogorov’s theory through its ability to avoid direct interpretation. Indeed, unlike (...) experimental sciences, and despite its numerous applications, probability theory cannot be tested per se. Rather it relates to practical matters by means of transition hypotheses or bridging principles that match the structure of practical problems with abstract theory. In this respect probability theory has a very special status among scientific disciplines. (shrink)