Mauricio Suárez

Se distinguen dos acepciones del término “contexto de descubrimiento”: La acepción tradicional, que lo contrasta con el contexto de la justificación, y otra, más reciente, que lo relaciona con la metodología de inferencia causal. Curiosamente, el propio Reichenbach suscribió la segunda acepción, y no es coincidencia que su aportación al desarrollo del campo del descubrimiento causal haya sido capital. Se defiende la vigencia de esta metodología en todas las ciencias empíricas, incluidas las ciencias físicas

This Element has two main aims. The first one 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 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'.

This paper is divided in two parts. In part I, I argue against two attempts to naturalise the notion of scientific representation, by reducing it to isomorphism and similarity. I distinguish between the means and the constituents of representation, and I argue that isomorphism and similarity are common means of representation; but that they are not constituents of scientific representation. I look at the prospects for weakened versions of these theories, and I argue that only those that abandon the aim to naturalise scientific representation are likely to be successful. In part II of the paper, I present a deflationary conception of scientific representation, which minimally characterises it by means of two necessary conditions: representation is essentially intentional and it has the capacity to allow surrogate reasoning and inference. I then defend this conception by showing that it successfully meets the objections and difficulties that make its competitors, such as isomorphism and similarity, untenable. In addition the inferential conception explains the success of various means of representation in their appropriate domains, and it sheds light on the truth and accuracy of scientific representations.

Thomas Kuhn’s work, particularly his famous book Structure of Scientific Revolutions, is often interpreted as a failed attempt to defend four radical thesis about science: epistemic pessimism, semantic relativism, methodological irrationalism and metaphysical idealism. In this paper I argue that such interpretation depends essentially on a false model of scientific knowledge, according to which the objects of scientific belief are always explanatory scientific theories, which are in turn empirically confirmed by means of a direct comparison with observable data and facts. This model has been importantly criticised by Ian Hacking and other defenders of the new experimentalism movement in philosophy of science, who have shown it to be untenable. I then argue that there is textual evidence in Kuhn’s own work in favour of new experimentalism; this shows that Kuhn’s work is more varied and less coherent than is supposed by his critics. I finish by questioning the need or desirability for a unique and coherent interpretation of Kuhn’s whole ouvre, and its historical impact

This paper advances further an ongoing project to understand the history of stellar structure modelling and its inferential practice. It does so by taking a harder look at the data: how it is collected, analysed statistically, and represented in HR diagrams and stellar structure models alike. The focus is ultimately on the sorts of strong observational constraints revealed in the last two decades within the new and expanding field of asteroseismology. It is argued that the typical inferential practices in asteroseismology, while richly loaded with modelling assumptions of their own, do not raise any circularity worries that may compromise the quality or value of the data.

This paper is divided in two parts. In part I, I argue against two attempts to naturalise the notion of scientific representation, by reducing it to isomorphism and similarity. I distinguish between the means and the constituents of representation, and I argue that isomorphism and similarity are common (although not universal) means of representation; but that they are not constituents of scientific representation. I look at the prospects for weakened versions of these theories, and I argue that only those that abandon the aim to naturalise scientific representation are likely to be successful. In part II of the paper, I present a deflationary conception of scientific representation, which minimally characterises it by means of two necessary conditions: representation is essentially intentional and it has the capacity to allow surrogate reasoning and inference. I then defend this conception by showing that it successfully meets the objections and difficulties that make its competitors, such as isomorphism and similarity, untenable. In addition the inferential conception explains the success of various means of representation in their appropriate domains, and it sheds light on the truth and accuracy of scientific representations.

It is still a matter of controversy whether the Principle of the Common Cause can be used as a basis for sound causal inference. It is thus to be expected that its application to quantum mechanics should be a correspondingly controversial issue. Indeed the early 90’s saw a flurry of papers addressing just this issue in connection with the EPR correlations. Yet, that debate does not seem to have caught up with the most recent literature on causal inference generally, which has moved on to consider the virtues of a generalised PCC inspired condition, the so called Causal Markov Condition. In this paper we argue that the CMC is an appropriate benchmark for debating possible causal explanations of the EPR correlations. But we go on to take issue with some pronouncements on EPR by defenders of the CMC.

We argue for an account of chemical reactivities as chancy propensities, in accordance with the ‘complex nexus of chance’ defended by one of us in the past (Suárez, 2017, 2020). Reactivities are typically quantified as proportions, and an expression such as “A + B → C” does not entail that under the right conditions some amounts of A and B react to give the amount of C that theoretically would correspond to the stoichiometry of the reaction. Instead, what is produced is a fraction α < 1 of this theoretical amount, and the corresponding percentage is usually known as the yield, which expresses the relative preponderance of its reaction. This is then routinely tested in a laboratory against the observed actual yields for the different reactions. Thus, on our account, reactivities ambiguously refer to three quantities at once. They first refer to the underlying propensities effectively acting in the reaction mechanisms, and which in ‘chemical chemistry’ (Schummer, 1998) are commonly represented by means of Lewis structures. Besides, reactivities represent the probabilities that these propensities give rise to, for any amount of the reactants to combine as prescribed. This last notion is hence best understood as a single case chance and corresponds to a theoretical stoichiometric yield. Finally, reactivities represent the actual yields observed in experimental runs, which account for and provide the requisite evidence for / against both the mechanisms and single case chances ascribed.

This paper expands on, and provides a qualified defence of, Arthur Fine’s selective interactions solution to the measurement problem. Fine’s approach must be understood against the background of the insolubility proof of the quantum measurement. I first defend the proof as an appropriate formal representation of the quantum measurement problem. Then I clarify the nature of selective interactions, and more generally selections, and I go on to offer three arguments in their favour. First, selections provide the only known solution to the measurement problem that does not relinquish any of the premises of the insolubility proofs. Second, unlike some no-collapse interpretations of quantum mechanics selections suffer no difficulties with non-ideal measurements. Third, unlike most collapse-interpretations selections can be independently motivated by an appeal to quantum dispositions.

This volume defends a novel approach to the philosophy of physics: it is the first book devoted to a comparative study of probability, causality, and propensity, and their various interrelations, within the context of contemporary physics -- particularly quantum and statistical physics. The philosophical debates and distinctions are firmly grounded upon examples from actual physics, thus exemplifying a robustly empiricist approach. The essays, by both prominent scholars in the field and promising young researchers, constitute a pioneer effort in bringing out the connections between probabilistic, causal and dispositional aspects of the quantum domain. The book will appeal to specialists in philosophy and foundations of physics, philosophy of science in general, metaphysics, ontology of physics theories, and philosophy of probability.

This article provides a state-of-the-art review of the philosophical literature on scientific representation. It first argues that the topic emerges historically mainly out of what may be called the modelling tradition. It then introduces a number of helpful analytical distinctions and goes on to divide contemporary approaches to scientific representation into two distinct kinds, substantive and deflationary. Analogies with related discussions of artistic representation in aesthetics and the nature of truth in metaphysics are pursued. It is finally urged that the most promising approaches—and the ones most likely to feature prominently in future developments—are deflationary. In particular, a defense is provided of a genuinely inferential conception of representation.

I defend a three-fold form of pluralism about chance, involving a tripartite distinction between propensities, probabilities, and frequencies. The argument has a negative and a positive part. Negatively, I argue against the identity thesis that informs current propensity theories, which already suggests the need for a tripartite distinction. Positively, I argue that that a tripartite distinction is implicit in much statistical practice. Finally, I apply a well-known framework in the modelling literature in order to characterize these three separate concepts functionally in terms of their roles in modelling practice.

James Maffie claims that weak continuity reliabilism is compatible with the principles, as well as the insights, of the Strong Programme in the Sociology of Knowledge (SPSK). There are three possible readings of weak continuity reliabilism: I argue that the first two are unsound, while the third is actually inconsistent with the principles of SPSK. SPSK is instead compatible with an identicist epistemology, one that does not aim to distinguish scientific epistemology from our everyday epistemic practice

This chapter defends a deflationary, or ‘quietist’ account of causation in science. It begins by laying out the elements of four central philosophical theories of causation, namely the regularity, counterfactual, probabilistic and process accounts. It then proceeds to briefly criticise them. While the criticisms are essentially renditions of arguments that are well-known in the literature, the conclusion that is derived from these is new. It is argued that the limitations of each of the theories point to a deflationary or quietist approach to causation in science. The practical focus is on interventionist methods for causal inference in physics and biology, and on the extant debates within the philosophy of each discipline as to how best to approach such methods. It is then argued that none of the four central theories proposed can completely explain or reduce the methods of causal inference that appear in each science. Yet, each theory provides partial insights into some of the grounds of causal inference and causal discovery. It is consequently suggested that we should retain the various methodological lessons without committing expressly to any metaphysics of causation.

We offer a review of some of the most influential views on the status of Reichenbach’s Principle of the Common Cause (PCC) for genuinely indeterministic systems. We first argue that the PCC is properly a conjunction of two distinct claims, one metaphysical and another methodological. Both claims can and have been contested in the literature, but here we simply assume that the metaphysical claim is correct, in order to focus our analysis on the status of the methodological claim. We briefly review the most entrenched or classical positions, including Salmon’s ‘interactive forks’, van Fraassen’s scepticism, and Cartwright’s generalisation of the fork criterion. We then go on to review the results of the ‘Budapest school’ on the existence of formally defined screening-off events for any correlation —by means of the ideas of probability space extensibility and (Reichenbachian common cause) completability. We distinguish the Budapest doctrine clearly from any of the classical conceptions, and thus present an overall framework for discussions of causal inference in quantum mechanics. The framework, however preliminary, is essential work for a thorough assessment of the conditions under which PCC may be a reliable tool for causal inference in a genuinely probabilistic (indeterministic) context.