Scientific Method, Misc

Scientists often diverge widely when choosing between research programs. This can seem to be rooted in disagreements about which of several theories, competing to address shared questions or phenomena, is currently the most epistemically or explanatorily valuable—i.e. most successful. But many such cases are actually more directly rooted in differing judgments of pursuit-worthiness, concerning which theory will be best down the line, or which addresses the most significant data or questions. Using case studies from 16th-century astronomy and 20th-century geology and (...) biology, I argue that divergent theory choice is thus often driven by considerations of scientific process, even where direct epistemic or explanatory evaluation of its final products appears more relevant. Broadly following Kuhn’s analysis of theoretical virtues, I suggest that widely shared criteria for pursuit-worthiness function as imprecise, mutually-conflicting values. However, even Kuhn and others sensitive to pragmatic dimensions of theory ‘acceptance’, including the virtue of fruitfulness, still commonly understate the role of pursuit-worthiness—especially by exaggerating the impact of more present-oriented virtues, or failing to stress how ‘competing’ theories excel at addressing different questions or data. This framework clarifies the nature of the choice and competition involved in theory choice, and the role of alternative theoretical virtues. (shrink)

In the recent well-being literature, various theory-free accounts of well-being have been proposed to ground informative evaluations of policies’ welfare implications without relying on any specifi...

This paper presents Christian Wolff’s claim that philosophy, undertaken on the basis of a proper method, cannot contradict revealed religion. The paper first provides a context of Wolff’s banishment from Halle for holding views in conflict with religious doctrines. Next, it proceeds, on the basis of Wolff’s Discursus præliminaris de philosophia in genere prefixed to his 1728 Latin Logic, to explain the principles of Wolff’s method, and to show how his conception of method enables him to disallow the possibility of (...) a genuine conflict between philosophical and religious dogmas. For Wolff, doctrinal conflicts between philosophy and revealed religion can only occur as a result of terminological disagreements, disagreements between dogmas and hypotheses, or disagreements between dogmas and theological misinterpretations. The actual conflict of dogmas, understood as religious or philosophical truths, Wolff holds to be impossible. (shrink)

Scientism has more notoriety than history proper for it has been identified with “positivism”, “reductionism”, “materialism” or “Marxism”, or even held responsible for the enforcement of science at the expense of other human affairs. The idea that scientific research yields the best possible knowledge lies at the very definition of “scientism”. However, even when science has shown a considerable amount of theoretical and practical successes, a rational confidence put on it as a mean for solving any factual problem has been (...) denounced as illegitimate, defective, or dogmatic. Thereby, after revisiting the varieties of the meaning of scientism, I argue for a reasonable defense of scientism against some of its prevailing criticisms. Hence, it will be sustained that science is the most reliable approach for attaining knowledge without detriment of other valuable human activities insofar these do not address factual or cognitive questions nor are at odds with a scientific worldview. (shrink)

What is reality? How do we know? Answers to these fundamental questions of ontology and epistemology, based on Mahatma Gandhi's "experiments with truth", are: reality is nonviolent (in the sense of not-inconsistent), and nonviolence (in the sense of respecting-meaning) is the only means of knowing (Gandhi, 1940). Be that as it may, science is what we think of when we think of reality and knowing. How does Gandhi's nonviolence, discovered in his spiritual quest for Truth, relate to the scientific pursuit (...) of truth? Here we show that Gandhian nonviolent knowing of nonviolent reality is an abstraction of both individual knowing (looking, reasoning) and collective scientific knowing (measurements, calculations). Specifically, Gandhi's truth-through-nonviolence is a law-like summation of the methods of physics ("do not disturb" of measurements) and of mathematics ("do not tear" of calculations) that are used to know. Moreover, physics (with its lawful behaviour of bodies) and biology (in preserving the meaning of genetic code) do affirm that the defining attribute of reality is nonviolence. In light of these correspondences, the Mahatma's derivation of a universal method of knowing (nonviolence of preserving-structure) from a universal truth (nonviolence of consistent-becoming) constitutes a science-supported general theory of reality and knowing. (shrink)

Entende-se que os experimentos mentais são dispositivos da imaginação que podem nos fornecer crenças que constituem conhecimento. John D. Norton apresentou uma abordagem que se tornou influente para explicar como os experimentos mentais científicos podem produzir novos conhecimentos so- bre o mundo. Ele afirma que não há nada distintivo nos experimentos men- tais, uma vez que sustenta que eles funcionam exatamente como argumen- tos. Neste artigo, contestamos sua abordagem. Examinamos aspectos essen- ciais de sua abordagem, que envolvem as noções de (...) “argumento” e “inferên- cia” para mostrar que um sujeito que chega a saber algo através da execução ou condução de um experimento mental dificilmente será considerado como tendo efetivamente executado um argumento ou um processo de raciocínio inferencial. (shrink)

In bringing together a global community of philosophers, Global Epistemologies and Philosophies of Science develops novel perspectives on epistemology and philosophy of science by demonstrating how frameworks from academic philosophy (e.g. standpoint theory, social epistemology, feminist philosophy of science) and related fields (e.g. decolonial studies, transdisciplinarity, global history of science) can contribute to critical engagement with global dimensions of knowledge and science. -/- Global challenges such as climate change, food production, and infectious diseases raise complex questions about scientific knowledge production (...) and its interactions with local knowledge systems and social realities. As academic philosophy provides relatively little reflection on global negotiations of knowledge, many pressing scientific and societal issues remain disconnected from core debates in epistemology and philosophy of science. -/- This book is an invitation to broaden agendas of academic philosophy by presenting epistemology and philosophy of science as globally engaged fields that address heterogeneous forms of knowledge production and their interactions with local livelihoods, practices, and worldviews. This integrative ambition makes the book equally relevant for philosophers and interdisciplinary scholars who are concerned with methodological and political challenges at the intersection of science and society. (shrink)

I defend an interpretation of Aristotle’s Posterior Analytics Book I which distinguishes between two projects in different passages of that work: (i) to explain what a given science is and (ii) to explain what properly scientific knowledge is. I present Aristotle’s theory in answer to ii, with special attention to his definition of scientific knowledge in 71b9-12 and showing how this is developed on chapters I.2-9 and I.13 into a solid Theory of Scientific Demonstration. The main point of this theory (...) is that demonstrations need to capture relevant explanations. Some formal requirements of the demonstration (as the syllogistic structure and coextension between terms) are unfoldings of the main project, i.e., to capture and present properly relevant causal-explanatory relations. (shrink)

The enduring replication crisis in many scientific disciplines casts doubt on the ability of science to estimate effect sizes accurately, and in a wider sense, to self-correct its findings and to produce reliable knowledge. We investigate the merits of a particular countermeasure—replacing null hypothesis significance testing with Bayesian inference—in the context of the meta-analytic aggregation of effect sizes. In particular, we elaborate on the advantages of this Bayesian reform proposal under conditions of publication bias and other methodological imperfections that are (...) typical of experimental research in the behavioral sciences. Moving to Bayesian statistics would not solve the replication crisis single-handedly. However, the move would eliminate important sources of effect size overestimation for the conditions we study. (shrink)

The demarcation between science and non-science seems to play an important role in the process of scientific change, as theories regularly transition from being considered scientific to being considered unscientific and vice versa. However, theoretical scientonomy is yet to shed light on this process. The goal of this paper is to tackle the problem of demarcation from the scientonomic perspective. Specifically, we introduce scientificity as a distinct epistemic stance that an agent can take towards a theory. We contend that changes (...) in this stance are to be traced and explained by scientonomy. Thus, we formulate a new law of theory demarcation to account for changes in scientificity within the scientonomic framework. (shrink)

Avicenna, beside his theoretical discussions about experimentation, practically applied his experimental method to natural sciences studies such as medicine, biology, and meteorology. His theoretical discussions subsume propositions concerning the conditions under which experimental knowledge is attained, the components of this knowledge and its functions. Some of these propositions are as follows: necessity of recurrent observations for acquiring experimental knowledge, certainty plus conditional universality of such knowledge, and its role as demonstrative premises. Investigating the application of his theory in natural sciences (...) propound two new features which were not elaborated in the theoretical discussions: fallibility of experimental knowledge and necessity of systematic observation. This research, using the analytic method and referring to both philosophical and scientific works of Avicenna, clarifies that a comprehensive definition of experimentation is dependent on considering extracted points from practical application of experimental knowledge, beside its theoretical components. (shrink)

The production of scientific instruments in America was neither a postwar phenomenon nor dramatically different from that of several other developed countries. It did, however, undergo a step-change in direction, size and style during and after the war. The American scientific instrument industry after 1945 was intimately dependent on, and shaped by, prior American and European experience. This was true of the specific genres of instrument produced commercially; to links between industry and science; and, just as importantly, to manufacturing practices (...) and cultures. I will argue that, despite the new types of instrument commercialized after the war, this historical continuity of links with science and scientists guided and constrained the design and manufacture of these products. Nevertheless, new designers, manufacturers and customers gradually transformed the culture of scientific instruments in the second half of the century. -/- This chapter deals with a subset of the American instrument industry, namely the measuring and monitoring instruments manufactured for scientific use. Even with the specification of ‘scientific’ instruments, however, these borders are rather artificial and unclear: instrument making from the seventeenth through the twentieth century has generally involved the fabrication of both standard products and custom-made devices for scientific use.2 In this context of sales quantities, ‘scientific’ instruments have often been defined as low-volume, special-order or custom devices. In a similar vein, ‘scientific’ instruments were commonly distinguished from ‘production’ instruments by context of usage, namely their very absence from – and indeed irrelevance to – production environments. This demarcation according to customer and environment was mirrored in at least one furth er respect: the training of their users. The classification into ‘scientific’ and ‘engineering’ applications was as fluid as the relationship between American universities and technical industries themselves.Despite these complementary definitions, the notion of the ‘scientific instrument’ was beginning to prove inadequate even at the turn of the twentieth century, and dramatically so when discussing the post-Second World War period. Definitions altered qualitatively after the Second World War in at least three further ways: (a) new genres of device altered the scope of the scientific instrument; (b) the contribution of State and military sponsorship of new forms of instrument became significant; and, (c) the postwar demand for specialist instruments increased rapidly, owing to wartime innovation, new applications and new customers. I will explore the evolution of instrument manufacturing in this changing context of new technology, funding, development and markets. (shrink)

This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, (...) and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. -/- This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text. (shrink)

We raise a problem of applicability of RCTs to validate nuclear diagnostic imaging tests. In spite of the wide application of PET and other similar techniques that use radiopharmaceuticals for diagnostic purposes, RCT-based evidence on their validity is sparse. We claim that this is due to a general conceptual problem that we call Prevalence of Treatment, which arises in connection with designing RCTs for testing any diagnostic procedure in the present context of medical research, and is particularly apparent in this (...) case. We also identify three practical reasons why RCTs do not qualify as the best option for PET validation, which have to do with specific characteristics of nuclear diagnostic imaging, and of radiopharmaceuticals. The paper is meant to contribute both to the philosophical discussion on the EBM hierarchy of evidence, and on the specific debate on radiopharmaceuticals in nuclear medicine. (shrink)

INTRODUCTION Philosophy of science is a study of the general nature of scientific practice, explanations, theories, and the relation of scientific knowledge ...

ENG: In this brief commentary on Sara Palermo’s article, I highlight several methodological criticisms of the data analysis and hypotheses proposed by the author. I then focus on the relevance of nocebo/placebo studies for the contemporary debate on the mind/body problem. In particular, I show how these phenomena raise questions for dualistic and neurocentric approaches that are still prevalent in philosophy. Finally, I stress the role of expectations in nocebo/placebo models, with reference to a promising theoretical framework: the predictive brain. (...) -/- ITA: In questo breve commento all’articolo di Sara Palermo mi propongo di rilevare alcune criticità relative al metodo di indagine e alla solidità dell’ipotesi suggerita dall’autrice. In seguito mi concentrerò sulla rilevanza dello studio del nocebo/placebo nell’ambito del dibattito sul rapporto mente/corpo e su come questi fenomeni mettano in discussione approcci dualisti e neurocentrici ancora pervasivi soprattutto in campo filosofico. In conclusione, mi soffermerò sul ruolo delle aspettative nella costruzione del modello del nocebo/placebo, riprendendo un contesto particolarmente promettente per l’inquadramento teorico del fenomeno: il cervello predittivo. Parole chiave: Placebo; Nocebo; Meta-analisi; Cervello bayesiano; Elaborazione predittiva. (shrink)

›Bottom-up‹ und ›top-down‹ sind heutzutage gängige Methodenbezeichnungen in allen Bereichen der Wissenschaft. Dennoch sind beide Methoden keine Entdeckung der Moderne, sondern wurden unter Begriffen wie beispielsweise ›Auf-‹ und ›Abstieg‹, ›Induktion‹ und ›Deduktion‹ in der Wissenschaftsgeschichte häufig verwendet, um komplexe Wissensbestände vollständig aufzuarbeiten und zu strukturieren. Paradigmatisch für eine derartige Aufarbeitung stehen die mittelalterliche Summa und das neuzeitliche System. Aktuellen Studien zufolge hat aber bereits Dionysius Areopagita in der Spätantike eine derartige Summe verfasst, während in der Neuzeit erst J. G. Fichtes (...) Wissenschaftslehre (1804) allen Systemansprüchen genügen konnte. Daher beschäftigt sich die vorliegende Studie mit den Auf- und Abstiegsmethoden bei Dionysius und Fichte, ihrer antiken Vorgeschichte und kontrastiert ihre Methoden mit der aktuellen Wissenschaftsphilosophie. Dabei zeigt sich, dass beide Autoren bei der Aufstiegs- bzw. bottom-up-Methode bislang unberücksichtigte Strategien zur Lösung des Induktionsproblems anwenden. (shrink)

Dans cet ouvrage, Franck Varenne pose la question du réalisme scientifique, essentiellement dans sa forme contemporaine, et ce jusqu’aux années 1980. Il s’est donné pour cela la contrainte de focaliser l’attention sur ce que devenaient sa formulation et les réponses diverses qu’on a pu lui apporter en réaction spécifique à l’évolution parallèle qu’ont subie les notions de théories et surtout de modèles dans les sciences, à la même époque. Même si, bien sûr, on ne peut pas attribuer le considérable essor (...) des modèles au XXe siècle au projet qu’auraient eu les scientifiques de régler cette question, en grande partie philosophique, du réalisme – car les modèles scientifiques ont bien d’autres fonctions et ils proviennent de bien d’autres demandes techniques, cognitives et sociales –, son choix épistémologique a consisté à suivre la littérature contemporaine désormais classique, tant scientifique que philosophique, sur les théories puis sur les modèles afin d’une part, d’en rapporter l’évolution générale, mais, d’autre part aussi, afin de l’interroger de proche en proche, et systématiquement, sur ce qu’elle entend à chaque fois réévaluer ou remettre en débat au moyen de cette question persistante du réalisme et de la réalité en science. Au-delà de l’enquête historique, cette étude se révèle donc également comparative. Elle présente l’intérêt de mettre en évidence des similitudes de forme remarquables (identités, symétries, inversions, déplacements) entre des séquences argumentatives produites par des auteurs différents, dans des contextes distincts, au sujet de cette capacité qu’aurait – ou non – la science à rendre véritablement compte de la réalité. -/- Ainsi, via l’analyse épistémologique historique et comparative qu’en propose Franck Varenne, la question cruciale de la médiation du réel par nos outils conceptuels ou expérientiels reçoit dans ce livre l’éclairage d’auteurs dont les conceptions sont, pour certaines encore, méconnues du lecteur non anglophone : Peter Achinstein, Max Black, Ludwig Boltzmann, Nancy Cartwright, Pierre Duhem, Ian Hacking, Mary Hesse, Evelyn Fox Keller, Imre Lakatos, Ernst Mach, Ernest Nagel, Henri Poincaré, Willard V.O. Quine, Bas van Fraassen, etc. (shrink)

Simple regression (regression analysis with a single explanatory variable), and multiple regression (regression models with multiple explanatory variables), typically correspond to very different biological questions. The former use regression lines to describe univariate associations. The latter describe the partial, or direct, effects of multiple variables, conditioned on one another. We suspect that the superficial similarity of simple and multiple regression leads to confusion in their interpretation. A clear understanding of these methods is essential, as they underlie a large range of (...) procedures in common use in biology. Beyond simple and multiple regression in their most basic forms, understanding the key principles of these procedures is critical to understanding, and properly applying, many methods, such as mixed models, generalised models, and causal inference using graphs (including path analysis and its extensions). A simple, but careful, look at the distinction between these two analyses is valuable in its own right, and can also be used to clarify widely-held misconceptions about collinearity (correlations among explanatory variables). There is no general sense in which collinearity is a problem. We suspect that the perception of collinearity as a hindrance to analysis stems from misconceptions about interpretation of multiple regression models, and so we pursue discussions about these misconceptions in this light. In particular, collinearity causes multiple regression coefficients to be less precisely estimated than corresponding simple regression coefficients. This should not be interpreted as a problem, as it is perfectly natural that direct effects should be harder to characterise than univariate associations. Purported solutions to the perceived problems of collinearity are detrimental to most biological analyses. (shrink)

The traditional sciences have always had trouble with ambiguity. To overcome this barrier, ‘science’ has imposed “enabling constraints”—hidden assumptions which are given the status of ceteris paribus. Such assumptions allow ambiguity to be bracketed away at the expense of transparency. These enabling constraints take the form of uncritically examined presuppositions, which we refer to throughout the article as “uceps.” The meanings of the various uceps are shown via their applicability to the science of climate change. Second order science examines variations (...) in values assumed for these uceps and looks at the resulting impacts on related scientific claims. Second order science reveals hidden issues, problems and assumptions which all too often escape the attention of the practicing scientist. This article lays out initial foundations for second order science, its ontology, methodology, and implications. (shrink)

This paper defends the naïve thesis that the method of experiment has per se an epistemic superiority over the method of computer simulation, a view that has been rejected by some philosophers writing about simulation, and whose grounds have been hard to pin down by its defenders. I further argue that this superiority does not come from the experiment’s object being materially similar to the target in the world that the investigator is trying to learn about, as both sides of (...) dispute over the epistemic superiority thesis have assumed. The superiority depends on features of the question and on a property of natural kinds that has been mistaken for material similarity. Seeing this requires holding other things equal in the comparison of the two methods, thereby exposing that, under the conditions that will be specified, the simulation is necessarily epistemically one step behind the corresponding experiment. Practical constraints like feasibility and morality mean that scientists do not often face an other-things- equal comparison when they choose between experiment and simulation. Nevertheless, I argue, awareness of this superiority and of the general distinction between experiment and simulation is important for maintaining motivation to seek answers to new questions. (shrink)

Positive review of Laats and Siegel (2016) *Teaching Evolution in a Creation Nation* (University of Chicago Press).

Contesting the common opinion that, unlike the problem of induction, the problem of demarcation is of little significance, the paper maintains that Popper’s criterion of falsifiability gives an irresistible answer to the question of what can be learnt from an empirical investigation. Everything follows from the rejection of inductive logic, together with the recognition that, before it can be empirically investigated, a hypothesis has to be formulated and accepted. Scientific hypotheses emerge neither a posteriori, as inductivists hold, nor from some (...) immaculate a priori source, but from sheer guesswork. Empiricists who reject apriorism have therefore enlisted too zealously in the unphilosophical ranks of epistemological naturalism. The paper concludes with a summary of Popper’s objectivism, and with brief responses to some fashionable arguments that objective truth is not an attainable objective.RésuméContestant l’opinion commune selon laquelle le problème de la démarcation, contrairement au problème de l’induction, est relativement anecdotique, l’article soutient que le critère poppérien de falsifiabilité donne une réponse irrésistible à la question de savoir ce qui peut être appris d’une investigation empirique. Tout découle du rejet de la logique inductive, joint à la reconnaissance du fait que, avant d’être investiguée, une hypothèse doit être formulée et acceptée. Les hypothèses scientifiques n’émergent ni a posteriori comme les inductivistes le soutiennent, ni de quelque immaculée source a priori : elles sont des conjectures pures et simples. Les empiristes qui rejettent l’apriorisme ont donc rejoint trop rapidement les rangs non philosophiques du naturalisme épistémologique. L’article conclut par un résumé de l’objectivisme popperien et par de brèves réponses à certains arguments à la mode selon lesquels la vérité objective n’est pas un objectif atteignable. (shrink)

Those who comment on modern scientific institutions are often quick to praise institutional structures that leave scientists to their own devices. These comments reveal an underlying presumption that scientists do best when left alone—when they operate in what we call the ‘scientific state of nature’. Through computer simulation, we challenge this presumption by illustrating an inefficiency that arises in the scientific state of nature. This inefficiency suggests that one cannot simply presume that science is most efficient when institutional control is (...) absent. In some situations, actively encouraging unpopular, risky science would improve scientific outcomes. 1 Introduction2 Scientists and Bandits3 Choosing an ϵ4 Structure of Communication5 Discussion. (shrink)

Relatively few philosophers of science today could do all of what Nicholas Maxwell does without hesitating: treat theoretical physics as indicative of all science because it is deemed fundamental, observe and expect science to exhibit a cumulative history of more and more unified knowledge, claim to solve the problem of induction, and insist that philosophy, particularly metaphysics, is crucially relevant to ongoing progress in science. Maxwell is distinctly out of fashion—this is no dappled world—but in hewing to a line he (...) has been developing for decades he presents several intriguing and intertwined proposals for understanding and continuing the progress of physics over the last three and a half centuries toward a single, true, theory of everything. (shrink)

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

Theories of epistemology make reference—via the perspective of an observer—to the structure of information transfer, which generates reality, of which the observer himself forms a part. It can be shown that any epistemological approach which implies the participation of tautological structural elements in the information transfer necessarily leads to an antinomy. Nevertheless, since the time of Aristotle the paradigm of mathematics—and thus tautological structure—has always been a hidden ingredient in the various concepts of knowledge acquisition or general theories of information (...) transfer. We hold that Darwin’s Evolutionary Theory is the first scientific theory which consistently presupposes a non-tautological structure for the information transfer and, at the same time, keeps it strictly distinct from the tautological metric of scientific observation. The consequences of this technique—namely the dissociation of information from intentionality—have not yet been fully drawn. (shrink)

A renewed interest in the old problem of the relationship between science and metaphysics has been fuelled by the ongoing debate between naturalistic metaphysicians and non-naturalistic metaphysicians. However, I maintain that this debate is missing the mark because it is focused on the problem of the credibility of a metaphysics that is not ‘scientific’, instead of focusing on the presence of metaphysics in science. In order to show that metaphysics pervades all stages of scientific inquiry, and after analysing the distinction (...) between presuppositions and assumptions, I address the complex problem of the relation of metaphysics to truth and to experience. I advocate that there is an indirect relation of metaphysics to experience and that it is possible to choose between rival metaphysical theories. But metaphysics, according to my view, is not present in science merely as a background of presuppositions and assumptions. It is present at every step of the scientific inquiry and also in a later moment: the interpretation of the findings of science and the elaboration of unifying theories. Keywords: science, metaphysics, presuppositions, truth, experience, unification. (shrink)

The central theme running throughout this outstanding new survey is the nature of the philosophical debate created by modern science's foundation in experimental and mathematical method. More recently, recognition that reasoning in science is probabilistic generated intense debate about whether and how it should be constrained so as to ensure the practical certainty of the conclusions drawn. These debates brought to light issues of a philosophical nature which form the core of many scientific controversies today. _Scientific Method: A Historical and (...) Philosophical Introduction_ presents these debates through clear and comparative discussion of key figures in the history of science. Key chapters critically discuss * Galileo's demonstrative method, Bacon's inductive method, and Newton's rules of reasoning * the rise of probabilistic `Bayesian' methods in the eighteenth century * the method of hypotheses through the work of Herschel, Mill and Whewell * the conventionalist views of Poincaré and Duhem * the inductivism of Peirce, Russell and Keynes * Popper's falsification compared with Reichenbach's enumerative induction * Carnap's scientific method as Bayesian reasoning The debates are brought up to date in the final chapters by considering the ways in which ideas about method in the physical and biological sciences have affected thinking about method in the social sciences. This debate is analyzed through the ideas of key theorists such as Kuhn, Lakatos, and Feyerabend. (shrink)

We describe a simple, flexible exercise that can be implemented in the philosophy of science classroom: students are asked to determine the contents of a closed container without opening it. This exercise has revealed itself as a useful platform from which to examine a wide range of issues in the philosophy of science and may, we suggest, even help us think about improving the public understanding of science.

In this brief note, a concept of the ‘scientific worldview’ is examined. In particular, contrary to some of the most often misconceptions regarding the concept, it will be argued (1) that there cannot be a ‘scientific worldview’ in the traditional sense of a Weltanschauung if science is taken in its strictest sense, (2) that the remaining ontological and epistemic skeleton cannot be a single unified picture of the world (Weltbild), and (3) that the supposed ‘truth’ of these remaining pictures cannot (...) be unambiguously grounded either in the methodology of science, although the methodology itself can be explanatory and predictively adequate and successful, or in the technological success that is associated with science. (shrink)

Professor Schurz has written a book that is ambitious in both scope and aims. It begins with an introductory chapter on the historical development and general aims of the philosophy of science itself, moves on to issues associated with establishing a basis for a unified approach to science, with extensive consideration of the conceptual toolkit required, then takes us through chapters on laws and empirical testing, the empirical evaluation of theories more generally, including issues of realism and empiricism, before concluding (...) with an extensive and technically detailed account of causation and explanation. Chapters are divided into core and ‘complementary and advanced’ topics—so, ‘Methodological Features of Scientific Theories’ is included under the former, whereas ‘Instrumentalism and Realism—The Ontology of Scientific Theories’ is placed in the latter—and relevant case studies go beyond the usual run of examples from physics to include Piaget’s Theory of Cognitive Development .. (shrink)