Many philosophers take mind-independence to be criterial for realism about kinds. This is problematic when it comes to psychological and social kinds, which are unavoidably mind-dependent. But reflection on the case of artificial or synthetic kinds shows that the criterion of mind-independence needs to be qualified in certain ways. However, I argue that none of the usual variants on the criterion of mind-dependence is capable of distinguishing real or natural kinds from non-real kinds. Although there is a way of modifying (...) the criterion of mind-independence in such a way as to rule in artificial kinds but rule out psychological and social kinds, this does not make the latter non-real. I conclude by proposing a different way of distinguishing real from non-real kinds, which does not involve mind-independence and does not necessarily exclude psychological and social kinds. (shrink)

Perhaps there has been no greater opportunity than in this “VOLUME FIFTEEN of our Death And Anti-Death set of anthologies” to write about how might think about life and how to avoid death. There are two reasons to discuss “life”, the first being enhancing our understanding of who we are and why we may be here in the Universe. The second is more practical: how humans meet the physical challenges brought about by the way they have interacted with their environment. (...) Many persons discussing “life” beg the question about what “life” is. Surely, when one discusses how to overcome its opposite, death, they are not referring to another “living” thing such as a plant. There seems to be a commonality, though, and it is this commonality is one needing elaboration. It ostensibly seems to be the boundary condition separating what is completely passive (inert) from what attempts to maintain its integrity, as well as fulfilling other conditions we think “life” has. In our present discussion, there will be a reminder that it by no means has been unequivocally established what life really is by placing quotes around the word, namely, “life”. Consider it a tag representing a bundle of philosophical ideas that will be unpacked in this paper. (shrink)

The most immediate reason why chemists are unenthusiastic about the philosophy of science is the historic hostility of important philosophers, to the concept of atoms. (Without atoms, discovery in chemistry would have proceeded with glacial slowness, if at all, in the last 200 years.) Other important reasons include the anti-realist influence of the philosophical dogmas of logical positivism, instrumentalism, of strict empiricism. Though (as has been said) these doctrines have recently gone out of fashion, they are still very influential.A diagram (...) of the methodology of experimental research is proposed, in the form of a flow sheet, with feedback. The model is developed as a multi-level expansion of a diagram of the hypothetico-deductive model. It recognizes that strong mutual support, or interlocking, of research endeavors is important, at the underlying level or levels where explanatory causation contributes to scientific understanding. (Mutual support at the laboratory level is generally weak or trivial.) The multiplicity of explanatory levels, and the interlocking, point to solutions to some well-known problems, such as the origin of the hypotheses, and even a resolution to the underdetermination problem. (shrink)

This paper aims to reassess the philosophical puzzle of the “applicability of mathematics to physical sciences” as a misunderstood disciplinary interplay. If the border isolating mathematics from the empirical world is based on appropriate criteria, how does one explain the fruitfulness of its systematic crossings in recent centuries? An analysis of the evolution of the criteria used to separate mathematics from experimental sciences will shed some light on this question. In this respect, we will highlight the historical influence of three (...) major disciplinary paradigms. According to the Aristotelian classification of the sciences, the separation of mathematics from physics is based on their respective objects of study. The Baconian system distinguishes these sciences by the type of knowledge involved in each field. Finally, the Whewellian disciplinary layout categorises these disciplines by their respective methods. In this paper, we argue that the cascading effect of such disciplinary categorisations—based successively on ontological, epistemological, and heuristic criteria—resulted in a profound redefinition of the border between mathematics and physics, with the consequence of obscuring the foundations of the interplay between these fields. Our approach intends to put forward such a mechanism as a constitutive piece of the puzzle of the applicability of mathematics. (shrink)

First published in 2002. Routledge is an imprint of Taylor & Francis, an informa company.

In this paper I offer a unified causal account of natural kinds. Using as a starting point the widely held view that natural kind terms or predicates are projectible, I argue that the ontological bases of their projectibility are the causal properties and relations associated with the natural kinds themselves. Natural kinds are not just concatenations of properties but ordered hierarchies of properties, whose instances are related to one another as causes and effects in recurrent causal processes. The resulting account (...) of natural kinds as clusters of core causal properties that give rise to clusters of derivative properties enables us to distinguish genuine natural kinds from non-natural kinds. For instance, it enables us to say why some of the purely conventional categories derived from the social domain do not correspond to natural kinds, though other social categories may. (shrink)

Biological taxonomists rely on the so-called ‘type method’ to regulate taxonomic nomenclature. For each newfound taxon, they lay down a ‘type specimen’ that carries with it the name of the taxon it belongs to. Even if a taxon’s circumscription is unknown and/or subject to change, it remains a necessary truth that the taxon’s type specimen falls within its boundaries. Philosophers have noted some time ago that this naming practice is in line with the causal theory of reference and its central (...) notion of rigid designation: a type specimen fixes the reference of a taxon name without defining it. Recently, however, this consensus has come under pressure in the pages of this journal. In a series of articles by Alex Levine, Joseph LaPorte, and Matthew Haber, it has been argued that type specimens belong only contingently to their species, and that this may bode problems for the relation between type method and causal theory. I will argue that this ‘contingency debate’ is a debate gone wrong, and that none of the arguments in defense of contingency withstand scrutiny. Taxonomic naming is not out of step with the causal theory, but conforms to it. However, I will also argue that this observation is itself in need of further explanation, since application of the type method in taxonomic practice is plagued by errors and ambiguities that threaten it with breaking down. Thus, the real question becomes why taxonomic naming conforms to the causal theory in the first place. I will show that the answer lies in the embedding of the type method into elaborate codes of nomenclature. (shrink)

Philosophers have long been interested in a series of interrelated questions about natural kinds. What are they? What role do they play in science and metaphysics? How do they contribute to our epistemic projects? What categories count as natural kinds? And so on. Owing, perhaps, to different starting points and emphases, we now have at hand a variety of conceptions of natural kinds—some apparently better suited than others to accommodate a particular sort of inquiry. Even if coherent, this situation isn’t (...) ideal. My goal in this article is to begin to articulate a more general account of ‘natural kind phenomena’. While I do not claim that this account should satisfy everyone—it is built around a certain conception of the epistemic role of kinds and has an obvious pragmatic flavour—I believe that it has the resources to go further than extant alternatives, in particular the homeostatic property cluster view of kinds. (shrink)

The “demarcation problem,” the issue of how to separate science from pseu- doscience, has been around since fall 1919—at least according to Karl Pop- per’s (1957) recollection of when he first started thinking about it. In Popper’s mind, the demarcation problem was intimately linked with one of the most vexing issues in philosophy of science, David Hume’s problem of induction (Vickers 2010) and, in particular, Hume’s contention that induction cannot be logically justified by appealing to the fact that “it works,” (...) as that in itself is an inductive argument, thereby potentially plunging the philosopher straight into the abyss of a viciously circular argument. (shrink)

In The Inference That Makes Science, Ernan McMullin recounts the clear historical progress he saw toward a vision of the sciences as conclusions reached rationally on the basis of empirical evidence. Distinctive of this vision was his view of science as driven by a specific form of inference, retroduction. To understand this properly, we need to disentangle the description of retroductive inference from the claims made on its behalf. To end I will suggest that the real rival to McMullin's vision (...) of science is not the methodologies he criticizes so successfully but a more radical empiricist alternative in epistemology. (shrink)

This target article presents a new computational theory of explanatory coherence that applies to the acceptance and rejection of scientific hypotheses as well as to reasoning in everyday life, The theory consists of seven principles that establish relations of local coherence between a hypothesis and other propositions. A hypothesis coheres with propositions that it explains, or that explain it, or that participate with it in explaining other propositions, or that offer analogous explanations. Propositions are incoherent with each other if they (...) are contradictory, Propositions that describe the results of observation have a degree of acceptability on their own. An explanatory hypothesis is acccpted if it coheres better overall than its competitors. The power of the seven principles is shown by their implementation in a connectionist program called ECHO, which treats hypothesis evaluation as a constraint satisfaction problem. Inputs about the explanatory relations are used to create a network of units representing propositions, while coherende and incoherence relations are encoded by excitatory and inbihitory links. ECHO provides an algorithm for smoothly integrating theory evaluation based on considerations of explanatory breadth, simplicity, and analogy. It has been applied to such important scientific cases as Lovoisier's argument for oxygen against the phlogiston theory and Darwin's argument for evolution against creationism, and also to cases of legal reasoning. The theory of explanatory coherence has implications for artificial intelligence, psychology, and philosophy. (shrink)

The aim of this article is to elucidate the notions of explanation and mechanism, in particular of the social kind. A mechanism is defined as what makes a concrete system tick, and it is argued that to propose an explanation proper is to exhibit a lawful mechanism. The so-called covering law model is shown to exhibit only the logical aspect of explanation: it just subsumes particulars under universals. A full or mechanismic explanation involves mechanismic law statements, not purely descriptive ones (...) such as functional relations and rate equations. Many examples from the natural, biosocial, and social sciences are examined. In particular, macro-micro-micro-macro social relations are shown to explain other wise puzzling macro-macro links. The last part of the article relates the author's progress, over half a century, toward understanding mechanism and explanation. (shrink)

This paper puts together an ancientand a recent approach to classificatory language, thought, and ontology.It includes on the one hand an interpretation of Aristotle's ten categories,with remarks on his first category, called (or translated as) substancein the Categories or What a thing is in the Topics. On the other hand is the ideaof domain-specific cognitive abilities urged in contemporary developmentalpsychology. Each family of ideas can be used to understand the other. Neitherthe metaphysical nor the psychological approach is intrinsically morefundamental; they (...) complement each other. The paper incidentally clarifies distinct uses of the word category in different disciplines, and also attempts to make explicit several notions of domain. It also examines Aristotle's most exotic and least discussed categories, being-in-a-position (e.g., sitting) and having-(on) (e.g., armour). Finally the paper suggests a tentative connectionbetween Fred Sommers' theory of types and Aristotle's first category. (shrink)

This paper describes the development of theories of scientific explanation since Hempel's earliest models in the 1940ies. It focuses on deductive and probabilistic whyexplanations and their main problems: lawlikeness, explanation-prediction asymmetries, causality, deductive and probabilistic relevance, maximal specifity and homogenity, the height of the probability value. For all of these topic the paper explains the most important approaches as well as their criticism, including the author's own accounts. Three main theses of this paper are: (1) Both deductive and probabilistic explanations (...) are important in science, not reducible to each other. (2) One must distinguish between (cause giving) explanations and (reason giving) justifications and predictions. (3) The adequacy of deductive as well as probabilistic explanations is relative to a pragmatically given background knowledge-which does not exclude, however, the possibility of purely semantic models. (shrink)

The paper offers a new understanding of induction in the empirical sciences, one which assimilates it to induction in geometry rather than to statistical inference. To make the point a system of notions, essential to logically sound induction, is defined. Notable among them are arbitrary object and particular property. A second aim of the paper is to bring to light a largely neglected set of assumptions shared by both induction and deduction in the empirical sciences. This is made possible by (...) appealing to the logic of common nouns and applying it to the logic of natural-kind terms.This strategy yields a new insight into the concept of natural kinds. While the strategy reveals deep affinity between empirical induction and deduction it also reveals two problems peculiar to induction. This helps to explain the intuition that induction is the more problematic of the two. The paper does not set out ‘to solve the problem of induction’. 1The paper has benefited from the support and critical comments of several friends: Steven Davis, Kevin Dunbar, Anil Gupta, Michael Hallett, Ray Jackendoff and Storrs McCall. Two friends, however, deserve special thanks, Michael Makkai and Gonzalo Reyes. Many of the points made in the paper, otherwise unacknowledged, are due to their generosity and patience. In fact, the paper can be seen as an application of the logic of kinds on which Gonzalo Reyes has been working for several years. (shrink)

Methodological dualism in linguistics occurs when its theories are subjected to standards that are inappropriate for them qua scientific theories. Despite much opposition, methodological dualism abounds in contemporary thinking. In this paper, I treat linguistics as a scientific activity and explore some instances of dualism. By extracting some ubiquitous aspects of scientific methodology from its typically quantitative expression, I show that two recent instances of methodologically dualistic critiques of linguistics are ill-founded. I then show that there are nonetheless some divergences (...) between linguistic and other ordinary scientific methods, reflecting yet a third instance of methodological dualism. (shrink)

Scientists cannot devise theories, construct models, propose explanations, make predictions, or even carry out observations, without first classifying their subject matter. The goal of scientific taxonomy is to come up with classification schemes that conform to nature's own. Another way of putting this is that science aims to devise categories that correspond to 'natural kinds.' The interest in ascertaining the real kinds of things in nature is as old as philosophy itself, but it takes on a different guise when one (...) adopts a naturalist stance in philosophy, that is when one looks closely at scientific practice and takes it as a guide for identifying natural kinds and investigating their general features. This Element surveys existing philosophical accounts of natural kinds, defends a naturalist alternative, and applies it to case studies in a diverse set of sciences. This title is also available as Open Access on Cambridge Core. (shrink)

In the last half century we have gone from storing data on 5-1/4 inch floppy diskettes to cloud and now fog computing. But one should ask why so much data is being collected. Part of the answer is simple in light of scientific projects but why is there so much data on us? Then, we ask about its “interface” through fog computing. Such questions prompt this chapter on the philosophy of big data and fog computing. After some background on definitions, (...) origins and contemporary applications, the main discussion begins with thinking about modern data collection, management, and applications from a complexity standpoint. Big data is turned into knowledge but knowledge is extrapolated from the past and used to manage the future. Yet it is questionable whether humans have the capacity to manage contemporary technological and social complexity evidenced by our world in crisis and possibly on the brink of extinction. Such calls for a new way of studying societies from a scientific point of view. We are at the center of the observation from which big data emerge and are manipulated, the overall human project being not only to create an artificial brain with an attendant mind but a society that might be able to survive what “natural” humans cannot. (shrink)

I show how Sir William Rowan Hamilton’s philosophical commitments led him to a causal interpretation of classical mechanics. I argue that Hamilton’s metaphysics of causation was injected into his dynamics by way of a causal interpretation of force. I then detail how forces are indispensable to both Hamilton’s formulation of classical mechanics and what we now call Hamiltonian mechanics (i.e., the modern formulation). On this point, my efforts primarily consist of showing that the contemporary orthodox interpretation of potential energy is (...) the interpretation found in Hamilton’s work. Hamilton called the potential energy function the “force-function” because he believed that it represents forces at work in the world. Various non-historical arguments for this orthodox interpretation of potential energy are provided, and matters are concluded by showing that in classical Hamiltonian mechanics, facts about the potential energies of systems are grounded in facts about forces. Thus, if one can tolerate the view that forces are causes of motion, then Hamilton provides one with a road map for transporting causation into one of the most mathematically sophisticated formulations of classical mechanics, viz., Hamiltonian mechanics. (shrink)

How good is an explanation and when is one explanation better than another? In this paper, I address these questions by exploring probabilistic measures of explanatory power in order to defend a particular Bayesian account of explanatory goodness. Critical to this discussion is a distinction between weak and strong measures of explanatory power due to Good (Br J Philos Sci 19:123–143, 1968). In particular, I argue that if one is interested in the overall goodness of an explanation, an appropriate balance (...) needs to be struck between the weak explanatory power and the complexity of a hypothesis. In light of this, I provide a new defence of a strong measure proposed by Good by providing new derivations of it, comparing it with other measures and exploring its connection with information, confirmation and explanatory virtues. Furthermore, Good really presented a family of strong measures, whereas I draw on a complexity criterion that favours a specific measure and hence provides a more precise way to quantify explanatory goodness. (shrink)

The inaugural title in the new, Open Access series BSPS Open, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. The fundamental burden of a theory of inductive inference is to determine which are the good inductive inferences or relations of inductive support and why it is that they are so. The traditional approach is modeled on that taken in accounts of deductive inference. It seeks universally applicable schemas or rules or a single (...) formal device, such as the probability calculus. After millennia of halting efforts, none of these approaches has been unequivocally successful and debates between approaches persist. The Material Theory of Induction identifies the source of these enduring problems in the assumption taken at the outset: that inductive inference can be accommodated by a single formal account with universal applicability. Instead, it argues that that there is no single, universally applicable formal account. Rather, each domain has an inductive logic native to it. Which that is, and its extent, is determined by the facts prevailing in that domain. Paying close attention to how inductive inference is conducted in science and copiously illustrated with real-world examples, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. (shrink)

Scientific revolution has been one of the most controversial topics in the history and philosophy of science. Yet it has been no consensus on what is the best unit of analysis in the historiography of scientific revolutions. Nor is there a consensus on what best explains the nature of scientific revolutions. This chapter provides a critical examination of the historiography of scientific revolutions. It begins with a brief introduction to the historical development of the concept of scientific revolution, followed by (...) an overview of the five main philosophical accounts of scientific revolutions. It then challenges two historiographical assumptions of the philosophical analyses of scientific revolutions. (shrink)

In the 1940s, the ‘modern synthesis’ (MS) of Darwinism and genetics cast genetic mutation and recombination as the source of variability from which environmental events naturally select the fittest, such ‘natural selection’ constituting the cause of evolution. Recent biology increasingly challenges this view by casting genes as followers and awarding the leading role in the genesis of adaptations to the agency and plasticity of developing phenotypes—making natural selection a consequence of other causal processes. Both views of natural selection claim to (...) capture the core of Darwin’s arguments in On the Origin of Species. Today, historians largely concur with the MS’s reading of Origin as a book aimed to prove natural selection the cause (vera causa) of adaptive change. This paper finds the evidence for that conclusion wanting. I undertake to examine the context and meaning of all Darwin’s known uses of the phrase vera causa, documenting in particular Darwin’s resistance to the pressure to prove natural selection a vera causa in letters written early in 1860. His resistance underlines the logical dependence of natural selection, an unobservable phenomenon, on the causal processes producing the observable events captured by the laws of inheritance, variation, and the struggle for existence, established in Chapters 1–3 of Origin. (shrink)

In this article, I argue that there is philosophy of science since philosophy existed. Thus, the idea that the philosophy of science was born with neopositivism is historically wrong and detrimental to the development of the philosophy of science itself. Neopositivism tried to found the philosophy of science as an anti-philosophical discipline, as a field of study that came to replace simple philosophy. The attempt was maintained for thirty years, but failed. Now, this does not mean that we cannot make (...) good philosophy of science today, but that the philosophy of science has returned to the common house of philosophy, it is gradually recovering the connection that it should never have lost with the main philosophical traditions and disciplines. (shrink)

Advanced technologies such as drones, intelligent algorithms and androids have grave implications for human existence. With the purpose of exploring their basis for doing so, the paper proposes a framework for investigating the complex relationship between such devices and human practices and language-mediated cognition. Specifically, it centers on the importance of the typically neglected intermediate layer of culture which not only drives both technophobia and philia but also, more fundamentally, connects pre-reflective experience and socio-material practices by placing advanced technologies in (...) the loop. Theoretically, the paper draws on contributions from performativist Science and Technology Studies and Radically Embodied Cognitive Science and pushes new grounds by stressing their compatibility. Yet, it also emphasizes the importance of the enlanguaged side of cognition which is a requirement for human-style socio-material practices and, hence, the emergence of cultures that fetishizes certain technologies. (shrink)

There is a perennial philosophical dream of a certain natural order for the natural kinds. The name of this dream is ‘the hierarchy requirement’. According to this postulate, proper natural kinds form a taxonomy which is both unique and traditional. Here I demonstrate that complex scientific objects exist: objects which generate different systems of scientific classification, produce myriad legitimate alternatives amongst the nonetheless still natural kinds, and make the hierarchical dream impossible to realize, except at absurdly great cost. Philosophical hopes (...) for a certain order in nature cannot be fulfilled. Natural kinds crosscut one another, ubiquitously so, and this crosscutting spells the end of the hierarchical dream. (shrink)

In this paper, I offer an analysis of the radical disagreement over the adequacy of string theory. The prominence of string theory despite its notorious lack of empirical support is sometimes explained as a troubling case of science gone awry, driven largely by sociological mechanisms such as groupthink (e.g. Smolin 2006). Others, such as Dawid (2013), explain the controversy by positing a methodological revolution of sorts, according to which string theorists have quietly turned to nonempirical methods of theory assessment given (...) the technological inability to directly test the theory. The appropriate response, according to Dawid, is to acknowledge this development and widen the canons of acceptable scientific methods. As I’ll argue, however, the current situation in fundamental physics does not require either of these responses. Rather, as I’ll suggest, much of the controversy stems from a failure to properly distinguish the “context of justification” from the “context of pursuit”. Both those who accuse string theorists of betraying the scientific method and those who advocate an enlarged conception of scientific methodology objectionably conflate epistemic justification with judgements of pursuit-worthiness. Once we get clear about this distinction and about the different norms governing the two contexts, the current situation in fundamental physics becomes much less puzzling. After defending this diagnosis of the controversy, I’ll show how the argument patterns that have been posited by Dawid as constituting an emergent methodological revolution in science are better off if reworked as arguments belonging to the context of pursuit. (shrink)

In the first half of this dissertation, I develop a heuristic methodology for analyzing scientific solutions to the problem of underdetermination. Heuristics are rough-and-ready procedures used by scientists to construct models, design experiments, interpret evidence, etc. But as powerful as they are, heuristics are also error-prone. Therefore, I argue that they key to prudently using a heuristic is the articulation of meta-heuristics---guidelines to the kinds of problems for which a heuristic is well- or ill-suited. Given that heuristics will introduce certain (...) errors into our scientific investigations, I emphasize the importance of a particular category of meta-heuristics involving the search for robust evidence. Robustness is understood to be the epistemic virtue bestowed by agreement amongst multiple modes of determination. The more modes we have at our disposal, and the more these confirm the same result, the more confident can we be that a result is not a mere artifact of some heuristic simplification. Through an analysis of case-studies in the philosophy of biology and clinical trials, I develop a principled method for modeling and evaluating heuristics and robustness claims in a qualitative problem space. The second half of the dissertation deploys the heuristic methodology to address ethical and epistemological issues in the science of clinical trials. To that end, I develop a network model for the problem space of clinical research, capable of representing the various kinds of experiments, epistemic relationships, and ethical justifications intrinsic to the domain. I then apply this model to ongoing research with the antibacterial agent, moxifloxacin, for the treatment of tuberculosis, tracking its development from initially successful and promising in vitro and animal studies to its disappointing and discordant performance across five human efficacy trials. Given this failure to find a robust result with moxifloxacin across animal and human studies, what should researchers now do? While my final analysis of this case does not definitively answer that question, I demonstrate how my methodology, unlike a statistical meta-analysis, helps to clarify the directions for further research. (shrink)

To better understand the work of pre-Darwinian British life researchers in their own right, this paper discusses two different styles of reasoning. On the one hand there was analysis:synthesis, where an organism was disintegrated into its constituent parts and then reintegrated into a whole; on the other hand there was palaetiology, the historicist depiction of the progressive specialization of an organism. This paper shows how each style allowed for development, but showed it as moving in opposite directions. In analysis:synthesis, development (...) proceeded centripetally, through the fusion of parts. In palaetiology, development moved centrifugally, through the ramifying specialization of an initially simple substance. I first examine a community of analytically oriented British life researchers, exemplified by Richard Owen, and certain technical questions they considered important. These involved the neurosciences, embryology, and reproduction and regeneration. The paper then looks at a new generation of British palaetiologists, exemplified by W.B. Carpenter and T.H. Huxley, who succeeded at portraying analysts' questions as irrelevant. The link between styles of reasoning and physical sites is also explored. Analysts favored museums, which facilitated the examination and display of unchanging marine organisms while providing a power base for analysts. I suggest that palaetiologists were helped by vivaria, which included marine aquaria and Wardian cases. As they became popular in the early 1850s, vivaria provided palaetiologists with a different kind of living and changing evidence. Forms of evidence, how they were preserved and examined, and career options all reinforced each other: social and epistemic factors thus merged. (shrink)

The purpose of this study is to gain a better understanding of the role of abstraction and idealization in Galileo’s scientific inquiries into the law of free falling motion, and their importance in the history of science. Because there is no consensus on the use of the terms “abstraction” and “idealization” in the literature, it is necessary to distinguish between them at the outset. This paper will argue for the importance of abstraction and idealization in physics and the theories and (...) laws of physics constructed with abduction from observations and that these theoretical laws of physics should be tested with deduction and induction thorough quasi-idealized entities rather than empirical results in the everyday world. Galileo’s work is linked to thought experiments in natural science. Galileo, using thought experiments based on idealization, persuaded others that what had been proven true for a ball on an inclined plane would be equally true for a ball falling through a vacuum. (shrink)

In a previous essay we demonstrated that quantum mechanical formalism is incompatible with some necessary principles of the mechanism conception still dominant in the physicist’s community. In this paper we show, based on recent empirical evidence in quantum physics, the inevitability of abandoning the old mechanism conception and to construct a new one in which physical reality is seen as a representation which refers to relations established through operations made by us in a world that we are determining. This change (...) is profound and radical, with immediate consequences on both Ontology and Epistemology. This work is our contribution to try to make more concrete how this new conception of the world might be. (shrink)