We consider some nonprincipal filters of the Medvedev lattice. We prove that the filter generated by the nonzero closed degrees of difficulty is not principal and we compare this filter, with respect to inclusion, with some other filters of the lattice. All the filters considered in this paper are disjoint from the prime ideal generated by the dense degrees of difficulty.

BackgroundResearch has been an essential part of the COVID-19 pandemic response, including in Latin American (LA) countries. However, implementing research in emergency settings poses the challenge of producing valuable knowledge rapidly while upholding research ethical standards. Research ethics committees (RECs) therefore must conduct timely and rigorous ethics reviews and oversight of COVID-19 research. In the LA region, there is limited knowledge on how countries have responded to this need. To address this gap, the objective of our project is to explore (...) if LA countries developed policies to streamline ethics review and oversight of research in response to the pandemic while ensuring its adherence to ethical standards, and to analyze to what extent these governance frameworks are in accordance with international guidance.MethodsWe conducted a descriptive and exploratory study assessing the COVID-19 research ethics governance frameworks of 19 LA countries, considering 4 dimensions based on international COVID-19 ethics guidance documents: (i) ethics review organizational model adopted, (ii) measures to coordinate between RECs and other research stakeholders, (iii) operational guidance for RECs, and (iv) key ethical issues for review and oversight of COVID-19 research.Results10 out of 19 LA countries have some policy to streamline ethics review of COVID-19 research. Of these countries only 6 issued comprehensive documents following international guidance that contemplate strategies with recommendations for concrete actions for a timely and rigorous review.ConclusionLA countries adopted partial strategies and operational guidance that may demonstrate a lack of a comprehensive view of research ethics for the review and oversight of COVID-19 research. Continuing efforts should be directed to strengthen LA countries' research capacity to respond timely and ethically to future health emergencies. Past lessons and the ones from this pandemic should be the basis to develop international standards and operational guidelines for ethics review and oversight of any research for public health emergencies. (shrink)

In this article, I deal with a conceptual issue concerning the framework of two special sciences: artificial intelligence and synthetic biology, i.e. the distinction between the natural and the artificial (a long-lasting topic of history of scientific though since the ancient philosophy). My claim is that the standard definition of the “artificial” is no longer useful to describe some present-day artificial sciences, as the boundary between the natural and the artificial is not so sharp and clear-cut as it was in (...) the past. Artificial intelligence and synthetic biology, two disciplines with new technologies, new experimental methods, and new theoretical frameworks, all need a new, more specific, and refined definition of (the) “artificial”, which is also related to the use of the synthetic method to build real world entities and in open-ended (real or virtual) environments. The necessity of a new definition of the artificial is due to the close relationship of AI and synthetic biology with biology itself. They both are engineering sciences that are moving closer and closer, at least apparently, towards (natural) biology, although from different and opposite directions. I show how the new concept of the artificial is, therefore, the result of a new view on biology from an engineering and synthetic point of view, where the boundary between the natural and the artificial is far more blurred. From this, I try to formulate a brand-new, more useful definition for future understanding, practical, and epistemological purposes of these two artificial sciences. (shrink)

Les langues des signes sont des langues qui n’ont pas un système d’écriture qui leur est propre et qui, par leur nature visuo-gestuelle, ne peuvent pas être écrites phonographiquement. Les conséquences de cette « non‑scriptibilité » sont au centre des travaux menés à partir de 2000 par Elena Antinoro Pizzuto. EAP, décédée en 2011, mettait en évidence les biais que l’utilisation des « gloses », employées comme substituts de la transcription, induisent dans l’analyse linguistique des LS. Ces 10 dernières années, (...) les avancées technologiques et méthodologiques ont rendu plus aisée la saisie automatique des données corporelles, l’annotation multilinéaire de corpus multimodaux et le maintien des liens entre les annotations et les vidéos, ainsi que la diffusion des vidéos sur lesquelles se basent les analyses. Toutefois, ces technologies et bonnes pratiques — bien que fondamentales — ne font pas office de système de transcription : ce sont des solutions qui suppriment une partie des symptômes liés à la non‑scriptibilité des LS, mais ne comblent pas l’absence d’un système de représentation graphique de ces langues. Les questions soulevées par EAP sont donc encore d’actualité. Si différentes tentatives pour transcrire les LS ont vu le jour, leur utilisation pour exploiter de vastes corpus de LS s’est souvent heurtée à leur faible lisibilité et/ou requêtabilité. En comparant les avantages et les inconvénients de ces systèmes, il est possible d’établir une liste des caractéristiques que devrait posséder un système de transcription des LS. Mais développer un système qui réunit toutes ces spécificités est un défi que les linguistes ne peuvent pas relever seuls : c’est dans la pluridisciplinarité, et en particulier dans le travail conjoint avec les spécialistes des aspects graphiques de l’écriture, que semble résider la solution. Cette approche, dite « grapholinguistique », est suivie par l’équipe GestualScript pour développer Typannot, un système de transcription typographique des LS et de la gestualité co-verbale. (shrink)

Most social scientists and philosophers claim that sociology and philosophy are disjoint fields of inquiry. Some have wondered how to trace the precise boundary between them. Mario Bunge argues that the two fields are so entangled with one another that no demarcation is possible or, indeed, desirable. In fact, sociological research has demonstrably philosophical pre-suppositions. In turn, some findings of sociology are bound to correct or enrich the philosophical theories that deal with the world, our knowledge of it, or (...) the ways of acting upon it. While Bunge's thesis would hardly have shocked Mill, Marx, Durkheim, or Weber, it is alien to the current sociological mainstream and dominant philosophical schools. Bunge demonstrates that philosophical problematics arise in social science research. A fertile philosophy of social science unearths critical presuppositions, analyzes key concepts, refines effective research strategies, crafts coherent and realistic syntheses, and identifies important new problems. Bunge examines Marx's and Durkheim's thesis that social facts are as objective as physical facts; the so-called Thomas theorem that refutes the behaviorist thesis that social agents react to social stimuli rather than to the way we perceive them; and Merton's thesis on the ethos of basic science which shows that science and morality are intertwined. He considers selected philosophical problems raised by contemporary social studies and argues forcefully against tolerance of shabby work in academic social science and philosophy alike. (shrink)

It is generally argued that if the wave-function in the de Broglie–Bohm theory is a physical field, it must be a field in configuration space. Nevertheless, it is possible to interpret the wave-function as a multi-field in three-dimensional space. This approach hasn’t received the attention yet it really deserves. The aim of this paper is threefold: first, we show that the wave-function is naturally and straightforwardly construed as a multi-field; second, we show why this interpretation is superior to other interpretations (...) discussed in the literature; third, we clarify common misconceptions. (shrink)

Predictivists use the no miracle argument to argue that “novel” predictions are decisive evidence for theories, while mere accommodation of “old” data cannot confirm to a significant degree. But deductivists claim that since confirmation is a logical theory-data relationship, predicted data cannot confirm more than merely deduced data, and cite historical cases in which known data confirmed theories quite strongly. On the other hand, the advantage of prediction over accommodation is needed by scientific realists to resist Laudan’s criticisms of the (...) no miracle argument. So, if the deductivists are right, the most powerful argument for realism collapses. There seems to be an inescapable contradiction between these prima facie plausible arguments of predictivists and deductivists; but this puzzle can be solved by understanding what exactly counts as novelty, if novel predictions must support the no miracle argument, i.e., if they must be explainable only by the truth of theories. Taking my cues from the use-novelty tradition, I argue that (1) the predicted data must not be used essentially in building the theory or choosing the auxiliary assumptions. This is possible if the theory and its auxiliary assumptions are plausible independently of the predicted data, and I analyze the consequences of this requirement in terms of best explanation of diverse bodies of data. Moreover, the predicted data must be (2) a priori improbable, and (3) heterogeneous to the essentially used data. My proposed notion of novelty, therefore, is not historical, but functional. Hence, deductivists are right that confirmation is independent of time and of historical contingencies such as if the theorist knew a datum, used it, or intended to accommodate it. Predictivists, however, are right that not all consequences confirm equally, and confirmation is not purely a logical theory-data relation, as it crucially involves background epistemic conditions and the notion of best explanation. Conditions (1)–(3) make the difference between prediction and accommodation, and account for the confirming power of theoretical virtues such as non ad-hocness, non-fudging, non-overfitting, independence and consilience. I thus show that functional novelty (a) avoids the deductivist objections to predictivism, (b) is a gradual notion, in accordance with the common intuition that confirmation comes in degrees, and (c) supports the no miracle argument, so vindicating scientific realism. (shrink)

We show that every nonzero Δ20\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\Delta^{0}_{2}}$$\end{document} enumeration degree bounds the enumeration degree of a 1-generic set. We also point out that the enumeration degrees of 1-generic sets, below the first jump, are not downwards closed, thus answering a question of Cooper.

There are two possible realist defense strategies against the pessimistic meta-induction and Laudan’s meta-modus tollens: the selective strategy, claiming that discarded theories are partially true, and the discontinuity strategy, denying that pessimism about past theories can be extended to current ones. A radical version of discontinuity realism is proposed by Gerald Doppelt: rather than discriminating between true and false components within theories, he holds that superseded theories cannot be shown to be even partially true, while present best theories are demonstrably (...) completely true. I argue that this position, running counter both the cumulativity of science and fallibilism, is untenable; it cannot account for the success of past theories, nor for the failures of current theories, and rather than shutting the door to the pessimistic historical objections it opens it wide. The best strategy, instead, joins the selective idea there was both some truth and some falsity in discarded theories, like in current ones, with the moderate discontinuity idea that the truth rate in present best theories is much greater than in past ones. (shrink)

Machine generated contents note: I. METAPHYSICS -- 1. How Do Realism, Materialism, and Dialectics Fare in Contemporary Science? -- 2. New Dialogues between Hylas and Philonous -- 3. Energy: Between Physics and Metaphysics -- 4. The Revival of Causality -- 5. Emergence and the Mind -- 6 SCIENTIFIC REALISM -- 6. The Status of Concepts -- 7. Popper's Unworldly World 3 --II. METHODOLOGY AND PHILOSOPHY OF SCIENCE -- 8. On Method in the Philosophy of Science -- 9. Induction in Science (...) -- 10. The GST Challenge to the Classical Philosophies of Science -- 11. The Power and Limits of Reduction -- 12. Thinking in Metaphors --III. PHILOSOPHY OF MATHEMATICS -- 13. Moderate Mathematical Fictionism -- 14. The Gap between Mathematics and Reality -- 15. Two Faces and Three Masks of Probability --IV. PHILOSOPHY OF PHYSICS -- 16. Physical Relativity and Philosophy -- 17. Hidden Variables, Separability, and Realism -- 18. Schrodinger's Cat Is Dead --V. PHILOSOPHY OF PSYCHOLOGY -- 19. From Mindless Neuroscience and Brainless Psychology to Neuropsychology -- 20. Explaining Creativity -- VI. PHILOSOPHY OF SOCIAL SCIENCE -- 21. Analytic Philosophy of Society and Social Science: -- The Systemic Approach as an Alternative to Holism and Individualism -- 22. Rational Choice Theory: A Critical Look at Its Foundations -- 23. Realism and Antirealism in Social Science --VII. PHILOSOPHY OF TECHNOLOGY -- 24. The Nature of Applied Science and Technology -- 25. The Technology-Science-Philosophy Triangle in Its Social Context -- 26. The Technologies in Philosophy --VIII. MORAL PHILOSOPHY -- 27. A New Look at Moral Realism -- 28. Rights Imply Duties --IX. SOCIAL AND POLITICAL PHILOSOPHY -- 29. Morality Is the Basis of Legal and Political Legitimacy -- 30. Technoholodemocracy: An Alternative to -- Capitalism and Socialism -- Bibliography -- Index of Names -- Index of Subjects. (shrink)

I want to combine two hitherto largely independent research projects, scientific understanding and mechanistic explanations. Understanding is not only achieved by answering why-questions, that is, by providing scientific explanations, but also by answering what-questions, that is, by providing what I call scientific descriptions. Based on this distinction, I develop three forms of understanding: understanding-what, understanding-why, and understanding-how. I argue that understanding-how is a particularly deep form of understanding, because it is based on mechanistic explanations, which answer why something happens in (...) virtue of what it is made of. I apply the three forms of understanding to two case studies: first, to the historical development of thermodynamics and, second, to the differences between the Clausius and the Boltzmann entropy in explaining thermodynamic processes. (shrink)

Deployment Realism resists Laudan’s and Lyons’ objections to the “No Miracle Argument” by arguing that a hypothesis is most probably true when it is deployed essentially in a novel prediction. However, Lyons criticized Psillos’ criterion of essentiality, maintaining that Deployment Realism should be committed to all the actually deployed assumptions. But since many actually deployed assumptions proved false, he concludes that the No Miracle Argument and Deployment Realism fail. I reply that the essentiality condition is required by Occam’s razor. In (...) fact, there is a simpler formulation of essentiality which escapes Lyons’ criticisms and rescues the No Miracle Argument and Deployment Realism from their purported historical counterexamples: a hypothesis is essential when it has no proper parts (in Yablo’s sense) sufficient to derive the same prediction. Although essentiality so conceived cannot be detected prospectively, this is just natural, and it is not a problem but an advantage for Deployment Realism. (shrink)

The ontological models framework distinguishes ψ-ontic from ψ-epistemic wave- functions. It is, in general, quite straightforward to categorize the wave-function of a certain quantum theory. Nevertheless, there has been a debate about the ontological status of the wave-function in the statistical interpretation of quantum mechanics: is it ψ-epistemic and incomplete or ψ-ontic and complete? I will argue that the wave- function in this interpretation is best regarded as ψ-ontic and incomplete.

What does it take to understand a phenomenon ideally, or to the highest conceivable extent? In this paper, we answer this question by arguing for five necessary conditions for ideal understanding: (i) representational accuracy, (ii) intelligibility, (iii) truth, (iv) reasonable endorsement, and (v) fitting. Even if one disagrees that there is some form of ideal understanding, these five conditions can be regarded as sufficient conditions for a particularly deep level of understanding. We then argue that grasping, novel predictions, and transparency (...) are not reasonable conditions for ideal understanding. (shrink)

Chasing Reality deals with the controversies over the reality of the external world. Distinguished philosopher Mario Bunge offers an extended defence of realism, a critique of various forms of contemporary anti-realism, and a sketch of his own version of realism, namely hylorealism. Bunge examines the main varieties of antirealism - Berkeley's, Hume's, and Kant's; positivism, phenomenology, and constructivism - and argues that all of these in fact hinder scientific research. Bunge's realist contention is that genuine explanations in the sciences (...) appeal to causal laws and mechanisms that are not directly observable, rather than simply to empirical generalisations. Genuine science, in his view, is objective even when it deals with subjective phenomena such as feelings of fear. This work defends a realist view of universals, kinds, possibilities, and dispositions, while rejecting contemporary accounts of these that are couched in terms of modal logic and 'possible worlds.'. (shrink)

Philosophers now seem to agree that frequentism is an untenable strategy to explain the meaning of probabilities. Nevertheless, I want to revive frequentism, and I will do so by grounding probabilities on typicality in the same way as the thermodynamic arrow of time can be grounded on typicality within statistical mechanics. This account, which I will call typicality frequentism, will evade the major criticisms raised against previous forms of frequentism. In this theory, probabilities arise within a physical theory from statistical (...) behavior of almost all initial conditions. The main advantage of typicality frequentism is that it shows which kinds of probabilities (that also have empirical relevance) can be derived from physics. Although one cannot recover all probability talk in this account, this is rather a virtue than a vice, because it shows which types of probabilities can in fact arise from physics and which types need to be explained in different ways, thereby opening the path for a pluralistic account of probabilities. (shrink)

Me propongo aquí una reflexión sobre la crisis del humanismo que afecta profundamente a la sociedad y la cultura contemporáneas en todas sus dimensiones. De un modo falsamente optimista, se ha opuesto a esta crisis la figura de un post humanismo triunfante, resultado de los desarrollos de la tecnología contemporánea y sus posibilidades de intervención en el cuerpo y el alma del hombre. Haré aquí una evaluación crítica de ese optimismo, sin por ello reivindicar el viejo humanismo y su razón (...) colonizadora. Trataré de plantear a través de Heidegger y Agamben la condición post humanista y post histórica –en el sentido moderno– en la que nos encontramos. Pero luego intentaré pensar junto a Nietzsche y Bataille una figura del hombre que no es nueva, sino una figura más antigua y creo más profunda, que quedó sepultada bajo la irrupción tectónica del humanismo y su empresa civilizatoria. (shrink)

This volume has 41 chapters written to honor the 100th birthday of Mario Bunge. It celebrates the work of this influential Argentine/Canadian physicist and philosopher. Contributions show the value of Bunge’s science-informed philosophy and his systematic approach to philosophical problems. The chapters explore the exceptionally wide spectrum of Bunge’s contributions to: metaphysics, methodology and philosophy of science, philosophy of mathematics, philosophy of physics, philosophy of psychology, philosophy of social science, philosophy of biology, philosophy of technology, moral philosophy, social and (...) political philosophy, medical philosophy, and education. The contributors include scholars from 16 countries. Bunge combines ontological realism with epistemological fallibilism. He believes that science provides the best and most warranted knowledge of the natural and social world, and that such knowledge is the only sound basis for moral decision making and social and political reform. Bunge argues for the unity of knowledge. In his eyes, science and philosophy constitute a fruitful and necessary partnership. Readers will discover the wisdom of this approach and will gain insight into the utility of cross-disciplinary scholarship. This anthology will appeal to researchers, students, and teachers in philosophy of science, social science, and liberal education programmes. 1. Introduction Section I. An Academic Vocation Section II. Philosophy Section III. Physics and Philosophy of Physics Section IV. Cognitive Science and Philosophy of Mind Section V. Sociology and Social Theory Section VI. Ethics and Political Philosophy Section VII. Biology and Philosophy of Biology Section VIII. Mathematics Section IX. Education Section X. Varia Section XI. Bibliography. (shrink)

The book brings into relief the variety of approaches and disciplines that have informed the quest for a theory of cognition. The center of interest are the historical, geographical, and theoretical peripheries of classic AI's mainstream research program. The twelve chapters bring back into focus the variety of strategies and theoretical questions that researchers explored while working toward a scientific theory of cognition and pre-cognition. The volume is organized in four parts, each one including three essays. The first one deals (...) with cybernetics, the approach that may be considered as the most important periphery of classic AI research. The second part focuses on the geographical periphery of AI research. It examines how the theories and techniques developed on AI's home ground were translated into countries with different cultures and traditions: Italy, France, and the Soviet Union. The third part focuses on AI's periphery understood in the cultural and historical meaning of the term. It contains essays that locate some of the central concepts of AI, like representation and computability, within a broader philosophical (Descartes, Aristotle, Leibniz) and technical background (programming theory and practice). The fourth and final part of the volume is focused directly on the limitation of Turing's classic computability theory and its possible alternatives, some of which were studied in the early years of AI's research (e.g. Ashby's re-entrant information model), while others have been intensely studied in recent times (quantum automata). (shrink)

A Neuroscientist Offers Evidence of Where the Brain Ends and Consciousness Begins.

A powerful critique of nudge theory and the paternalist policies of behavioral economics, and an argument for a more inclusive form of rationality.

This paper investigates the historical origin and ancestors of typicality, which is now a central concept in Boltzmannian Statistical Mechanics and Bohmian Mechanics. Although Ludwig Boltzmann did not use the word typicality, its main idea, namely, that something happens almost always or is valid for almost all cases, plays a crucial role for his explanation of how thermodynamic systems approach equilibrium. At the beginning of the 20th century, the focus on almost always or almost everywhere was fruitful for developing measure (...) theory and probability theory. It was apparently Hugh Everett III who first mentioned typicality in physics in 1957 while searching for a justification of the Born rule in his interpretation of quantum mechanics. The historically closest concept before these developments is moral certainty, which was invented by the medieval French theologian Jean Gerson, and it became a standard concept at least until the Age of Enlightenment, when Jakob Bernoulli proved the Law of Large numbers. (shrink)

This fascinating exploration of the great discoveries of history's most important mathematicians seeks an answer to the eternal question: Does mathematics hold the key to understanding the mysteries of the physical world?