The formal sciences - mathematical as opposed to natural sciences, such as operations research, statistics, theoretical computer science, systems engineering - appear to have achieved mathematically provable knowledge directly about the real world. It is argued that this appearance is correct.

The formal sciences, particularly mathematics, have had a profound influence on the development of linguistics. This insightful overview looks at techniques that were introduced in the fields of mathematics, logic and philosophy during the twentieth century, and explores their effect on the work of various linguists. In particular, it discusses the 'foundations crisis' that destabilised mathematics at the start of the twentieth century, the numerous related movements which sought to respond to this crisis, and how they influenced the (...) development of syntactic theory in the 1950s. The book concludes by discussing the resulting major consequences for syntactic theory, and provides a detailed reassessment of Chomsky's early work at the advent of Generative Grammar. Informative and revealing, this book will be invaluable to all those working in formal linguistics, in particular those interested in its history and development. (shrink)

The perception of separation between school and home/community is related to diminished achievement in school and lack of motivation to learn STEM subjects. The National Council of Educational Research and Training is among many research organisations that have strongly recommended that schools bridge the disconnect between school-based knowledge and learners’ everyday knowledge. We designed the SPIRALS curriculum to bridge this gap between formal science and students’ everyday lives. SPIRALS helps students explore community-based practices to learn about science, environmental sustainability (...) and systems thinking. We implemented the SPIRALS curriculum in a private, urban, English medium school in Western India with approximately 315 students and their four teachers, 214 of whom also participated in the research from which our conclusions are drawn. Our findings about program impacts rely upon analysis of interviews with teachers and students, as well as student work, and conference participation assessment surveys distributed after a capstone experience at which students present their work. This chapter describes our findings about how students learned science, environmental sustainability, and systems thinking through engagement with community-based practices. We also discuss the process of how the SPIRALS approach worked in India and how it could be expanded into a broader learning model across different socio-cultural contexts within India. (shrink)

Scientific research in the formal sciences comes in multiple degrees of formality: fully formal work; rigorous proofs that practitioners know to be formalizable in principle; and informal work like rough proof sketches and considerations about the advantages and disadvantages of various formal systems. This informal work includes informal and semi-formal debates between formal scientists, e.g. about the acceptability of foundational principles and proposed axiomatizations. In this paper, we propose to use the methodology of structured (...) argumentation theory to produce a formal model of such informal and semi-formal debates in the formal sciences. For this purpose, we propose ASPIC-END, an adaptation of the structured argumentation framework ASPIC+ which can incorporate natural deduction style arguments and explanations. We illustrate the applicability of the framework to debates in the formal sciences by presenting a simple model of some arguments about proposed solutions to the Liar paradox, and by discussing a more extensive—but still preliminary—model of parts of the debate that mathematicians had about the Axiom of Choice in the early twentieth century. (shrink)

Thomas A. Fay Heidegger and the Formalization of Thought 1 Dagfinn F011esdal The Justification of Logic and Mathematics in Husserl's Phenomenology 25 Guillermo E. Rosado Haddock On Husserl's Distinction between State of Affairs and Situation of Affairs.... 35 David Woodruff Smith On Situations and States of Affairs 49 Charles W. Harvey, Jaakko Hintikka Modalization and Modalities................... 59 Gilbert T. Null Remarks on Modalization and Modalities 79 J. N. Mohanty Husserl's Formalism 93 Carl J. Posy Mathematics as a Transcendental Science 107 (...) vi Gian-carlo Rota Mathematics and the Task of Phenomenology 133 John Scalon "Tertium Non Datur: " Husserl's Conception of a Definite Multiplicity..... 139 Thomas M. Seebohm Psychologism Revisited 149 Gerald J. Massey Some Reflections on Psychologism 183 Robert S. Tragesser How Mathematical Foundation all but come about: A Report on Studies Toward a Phenomenological Critique of Godel's Views on Mathematical Intuition.. 195 Kenneth L. Manders On Geometric Intentionality 215 Dallas Willard Sentences which are True in Virtue of their Color... 225 John J. Drummond Willard and Husserl on Logical Form 243 Index of Names 257 Index of Subjects 259 PREFACE The phenomenology of logic and ideal objects is the topic of Husserl's Logical Investigations. This book determined the early development of the so called phenomenological movement. It is still the main source for many phenomenologists, even if they disagree with Husserl's transcendental turn and developed other phenomenological positions or positions beyond phenomenology he early sense. (shrink)

"Foundations of the Formal Sciences" is a series of interdisciplinary conferences in mathematics, philosophy, computer science and linguistics. The main goal is to reestablish the traditionally strong links between these areas of research that have been lost in the past decades. The second conference in the series had the subtitle "Applications of Mathematical Logic in Philosophy and Linguistics" and brought speakers from all parts of the Formal Sciences together to give a holistic view of how mathematical (...) methods can improve our philosophical and technical understanding of language and scientific discourse, ranging from the theoretical level up to applications in language recognition software. Audience: This volume is of interest to all formal philosophers and theoretical linguists. In addition to that, logicians interested in the applications of their field and logic students in mathematics, computer science, philosophy and linguistics can use the volume to broaden their knowledge of applications of logic. (shrink)

Discussion on the methodological status of theology is an attempt to answer whether theology can be considered a science, i.e., a source of knowledge. This debate has resulted in the formulation of three main positions. The first position argues that theology does not qualify as a science due to its failure to meet the strict criteria of demarcation. The second position asserts that theology is indeed a science, similar to any other discipline, and this perspective is endorsed by theologians themselves. (...) The third position treats theology as a science, but one of a unique nature (_sui generis_). Furthermore, an idea has emerged suggesting that theology could be regarded as a formal science. Several arguments support this notion, including the operational rather than eidetic nature of the terms of theological discourse, the employment of assumptions and the drawing of conclusions within theology, the exclusive focus on textual analysis, and the application of a coherence theory of truth. This paper engages in a discussion with the presented arguments and endeavours to demonstrate their incorrectness. The purpose of positioning theology among the formal sciences is to defend its scientific status against scholars who hold atheistic or anti-theological world views. However, this “defence” comes at a high price, as it entails depriving theology of its fundamental aim, which is to formulate statements about reality. (shrink)

The paper discusses in how far medieval logic can appropriately be characterized as a formal science. In this respect, the special mediecal approach to logic as a scientia sermocinalis is examined as well as its main doctrines, namely the theories of supposition and of consequences, and the famous characterization of logic as an ars artium or scientia scientiarum. It is pointed out that medieval logic is not devoted to the setting up of formal systems or any metalogical analysis (...) of formal structures. Logic in the medieval sense of the discipline is necessarily connected with semantical aspects of natural language. Accordingly, we are confronted with a discipline going far beyond the formal structures of discourse. The classification of medieval logic as a formal science is appropriate only under selected perspectives. (shrink)

Mathematics, and mechanics conceived as a formal science, have their own proper subject matters, their own proper unities, which ground the characteristic way of constituting problems and solutions in each domain, the discoveries that expand and integrate domains with each other, and so in particular allow them, in the end, to be connected in a partial way with empirical fact. Criticizing both empiricist and structuralist accounts of mathematics, I argue that only an account of the formal sciences (...) which attributes to them objects as well as structure, proper semantics as well as syntax, can do justice to their intelligibility, heuristic force and explanatory power. (shrink)

Any discussion of the concept of “formal science” must acknowledge that the term is used in different ways, for different purposes, by different people. For some, the formal sciences are defined by the exclusive use of deductive methods for discovering, or reasoning about, the properties of formal, abstract systems. On this view, the formal sciences are synonymous with mathematics, formal logic, and certain branches of linguistics and computer science that emphasize the study of (...) formal languages. For others, “formal science” means something like “exact science”, or “formalized science”. On this view, any scientific discipline that places heavy emphasis on mathematical or logical formalization of key theoretical concepts and theories, could be described as a formal science. This latter conception of formal science is much more liberal than the former, and would include all of physics, much of chemistry, and some parts of biology, ecology, psychology and economics, as well as newer computationoriented disciplines like artificial life and artificial intelligence that do not fit easily within the traditional classification of the sciences. (shrink)

Este artigo procura mostrar que as idéias filosóficas de Husserl não apenas influenciaram o trabalho de alguns dos maiores matemáticos do século XX, mas foram decisivas para aproximarem uma epistemologia das ciências formais de uma fenomenologia do significado.

James Franklin has argued that the formal, mathematical sciences of complexity — network theory, information theory, game theory, control theory, etc. — have a methodology that is different from the methodology of the natural sciences, and which can result in a knowledge of physical systems that has the epistemic character of deductive mathematical knowledge. I evaluate Franklin’s arguments in light of realistic examples of mathematical modelling and conclude that, in general, the formal sciences are no (...) more able to guarantee certainty than the natural sciences. Yet the formal sciences are characterized by a ‘domain-independence’ that is philosophically interesting, and I argue that it is this property that Franklin actually employs to distinguish the formal from the natural sciences. I use Einstein’s ‘principle’/‘constructive’ theory distinction to contrast the domain-independence of physical theories with the domain-independence of formal mathematical theories, and show how both kinds of domain-independence function to generate the domain-independence that is observed in the complex systems sciences. © 1999 Elsevier Science Ltd. All rights reserved. (shrink)

I. The function of models in the empirical sciencesII. Structure and purpose: conditions of a structural nature which models should satisfy in order to accomplish their function.III. Generalisation and specialisation of the classical definition of model, in view of the above requirements:the algebraic model conceptthe semantic model conceptthe syntactical model conceptIV. Attempt towards reunification: the concept of model on a pragmatic basis.

Replies to Kevin de Laplante’s ‘Certainty and Domain-Independence in the Sciences of Complexity’ (de Laplante, 1999), defending the thesis of J. Franklin, ‘The formal sciences discover the philosophers’ stone’, Studies in History and Philosophy of Science, 25 (1994), 513-33, that the sciences of complexity can combine certain knowledge with direct applicability to reality.

What exactly is so appealing in formal science, such that its influence can be seen in numerous disciplines? This contemporary addiction to practical convenience in formal science has turned a blind eye to its other side. This book provides a way to understand the nature of formal science, in relation to systems theory for practical convenience.

Exact sciences are described as sciences whose theories are formalized. These are contrasted to inexact sciences, whose theories are not formalized. Formalization is described as a broader category than mathematization, involving any form/content distinction allowing forms, e.g., as represented in theoretical models, to be studied independently of the empirical content of a subject-matter domain. Exactness is a practice depending on the use of theories to control subject-matter domains and to align theoretical with empirical models and not merely (...) a state of a science. Inexact biological sciences tolerate a degree of “mismatch” between theoretical and empirical models and concepts. Three illustrations from biological sciences are discussed in which formalization is achieved by various means: Mendelism, Weismannism, and Darwinism. Frege’s idea of a “conceptual notation” is used to further characterize the notion of a form/content distinction. (shrink)

This paper presents an account of how to evaluate formal models of science: models and simulations in social epistemology designed to draw normative conclusions about the social structure of scientific research. I argue that such models should be evaluated according to their representational and predictive accuracy. Using these criteria and comparisons with familiar models from science, I argue that most formal models of science are incapable of supporting normative conclusions.

This article discusses a relation between the formal science of logical semantics and some monotheistic, polytheistic and Trinitarian Christian notions. This relation appears in the use of the existential quantifier and of logical-modal notions when some monotheistic and polytheistic concepts and, principally, the concept of Trinity Dogma are analyzed. Thus, some presupposed modal notions will appear in some monotheistic propositions, such as the notion of “logically necessary”. From this, it will be shown how the term “God” is a polysemic (...) term and is often treated as both subject and predicate. This will make it clear that there is no plausible intellectual justification for believing that the term “God” can only be used as a name and never as a predicate, and vice versa. After that analysis, I will show that the conjunction of the “Trinity Dogma” with some type of “monotheistic position” would necessarily imply some class of absurdity and/or semantic “oddity”. (shrink)

In this article, we reflect on the use of formal methods in the philosophy of science. These are taken to comprise not just methods from logic broadly conceived, but also from other formal disciplines such as probability theory, game theory, and graph theory. We explain how formal modelling in the philosophy of science can shed light on difficult problems in this domain.

I critically review Raymond Turner’s Computational Artifacts – Towards a Philosophy of Computer Science by placing beside his position a rather different one, according to which computer science is a branch of, and is therefore subsumed by, immaterial formal logic.

Formal learning theory is an approach to the study of inductive inference that has been developed by computer scientists. In this paper, I discuss the relevance of formal learning theory to such standard topics in the philosophy of science as underdetermination, realism, scientific progress, methodology, bounded rationality, the problem of induction, the logic of discovery, the theory of knowledge, the philosophy of artificial intelligence, and the philosophy of psychology.

This article is composed of three sections that investigate the epistemological foundations of Husserl’s idea of logic from the Logical Investigations . First, it shows the general structure of this logic. Husserl conceives of logic as a comprehensive, multi-layered theory of possible theories that has its most fundamental level in a doctrine of meaning. This doctrine aims to determine the elementary categories that constitute every possible meaning (meaning-categories). The second section presents the main idea of Husserl’s search for an epistemological (...) foundation for knowledge, science and logic. Their epistemological clarification can only be reached through a detailed analysis of the structure of those intentions that give us what is meant in our intentions. To reveal the intuitive giveness of logical forms is the ultimate aim of Husserl’s epistemology of logic. Logical forms and meaning-categories can only be given in a certain higher-order intuition that Husserl calls categorical intuition. The third section of this article distinguishes different kinds of categorical intuition and shows how the most basic logical categories and concepts are given to us in a categorical abstraction. (shrink)

This essay addresses the methodology of philosophy of science and illustrates how formal and empirical methods can be fruitfully combined. Special emphasis is given to the application of experimental methods to confirmation theory and to recent work on the conjunction fallacy, a key topic in the rationality debate arising from research in cognitive psychology. Several other issue can be studied in this way. In the concluding section, a brief outline is provided of three further examples.

John Norton’s argument that all formal theories of induction fail raises substantive questions about the philosophical analysis of scientific reasoning. What are the criteria of adequacy for philosophical theories of induction, explanation, or theory structure? Is more than one adequate theory possible? Using a generalized version of Norton’s argument, I demonstrate that the competition between formal and material theories in philosophy of science results from adhering to different criteria of adequacy. This situation encourages an interpretation of “formal” (...) and “material” as indicators of divergent criteria that accompany different philosophical methodologies. I characterize another criterion of adequacy associated with material theories, the avoidance of imported problems, and conclude that one way to negotiate between conflicting criteria is to adopt a pluralist stance toward philosophical theories of scientific reasoning. (shrink)

Various errors can affect scientific code and detecting them is a central concern within computational science. Could formal verification methods, which are now available tools, be widely adopted to guarantee the general reliability of scientific code? After discussing their benefits and drawbacks, we claim that, absent significant changes as regards features like their user-friendliness and versatility, these methods are unlikely to be adopted throughout computational science, beyond certain specific contexts for which they are well-suited. This issue exemplifies the epistemological (...) heterogeneity of computational science: profoundly different practices can be appropriate to meet the reliability challenge that rises for scientific code. (shrink)

Wilfried Sieg. Formal Systems, Church Turing Thesis, and Gödel's Theorems: Three Contributions to The MIT Encyclopedias of Cognitive Science.