Scientific Method, Misc

A volume of papers inspired by the work of George E. Smith on confirmation and evidence in advanced science—from Newton's gravitation theory to the physics of molecules.

This is a brief remembrance of Robert Nola.

In this article, I reconstruct and interpret the early Vico’s oft-neglected theory of scientific cognition, as found in his 1710 metaphysical treatise On the Most Ancient Wisdom of the Italians, a work whose aim was to be the handmaid to experimental physics. In particular, I offer a new reading of his verum-factum principle, which holds that the true and the made are interchangeable, by examining this doctrine in light of its unexpected connections to much later trends in philosophy. I also (...) present his criticism of Descartes’ cogito and, finally, Vico’s own solution to the problem of skepticism, which is meant to provide a new foundation for the sciences. (shrink)

Kant’s denial that psychology is a properly so-called natural science, owing to the lack of application of mathematics to inner sense, has garnered a great deal of attention from scholars. Although the interpretations of this claim are diverse, commentators by and large fail to ground their views on an account of Kant’s conception of applied mathematics. In this article, I develop such an account, according to which the application of mathematics to a natural science requires both a mathematical representation and (...) a metaphysical validation for the positive use of this representation to achieve a priori knowledge about nature. The second condition—that of metaphysical validation—has been overlooked in the literature. I show that psychology’s falling short of natural scientific propriety consists not in our lacking sufficient mathematical tools for the representation of inner states, according to Kant. After all, we can represent the mere temporality of inner states with the line and their intensities with numbers. Rather, the problem is that metaphysics does not validate the further use of such mathematical entities for the achievement of a priori knowledge about inner phenomena. (shrink)

In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data science (machine learning in (...) particular). These lie mainly in the creation of predictive models which performances increase as data set increases. Next, we will identify a tradeoff between predictive and explanatory performances by comparing the features of mechanistic and predictive models. Finally, we show how this a priori analysis of machine learning and mechanistic research applies to actual biological practice. This will be done by analyzing the publications of a consortium—The Cancer Genome Atlas—which stands at the forefront in integrating data science and molecular biology. The result will be that biologists have to deal with the tradeoff between explaining and predicting that we have identified, and hence the explanatory force of the ‘new’ biology is substantially diminished if compared to the ‘old’ biology. However, this aspect also emphasizes the existence of other research goals which make predictive force independent from explanation. (shrink)

Academia is a competitive environment. Early Career Researchers (ECRs) are limited in experience and resources and especially need achievements to secure and expand their careers. To help with these issues, this book offers a new approach for conducting research using the combination of mindsponge innovative thinking and Bayesian analytics. This is not just another analytics book. 1. A new perspective on psychological processes: Mindsponge is a novel approach for examining the human mind’s information processing mechanism. This conceptual framework is used (...) to construct models in studies. The framework is highly flexible and widely applicable for many different types of information processes. The mindsponge approach can help researchers discover interesting ideas or even formulate their very own theories when investigating psychosocial phenomena. This approach brings a fresh wind to the current landscape of social sciences and humanities (SSH). 2. Easy-to-follow analysis protocol: The Bayesian Mindsponge Framework (BMF analytics) is useful in terms of computing and visualizing power but also easy to learn and apply. Contrary to being intimidating, the Bayesian analytics section of this book is presented in a reader-friendly manner with a detailed yet clear step-by-step procedure. Examples are from published BMF articles, allowing readers to immediately practice the method and quickly create their own applications. With educational purposes in mind, the book is very suitable for ECRs who are looking to innovate their research methods. 3. Advocating for low-cost, high-quality research: Doing science can be very costly. Mindsponge innovative thinking and BMF analytics help produce impactful studies using openly available data on online repositories. This is based on the authors’ previous works and experiences. The book presents examples of employing the open R package bayesvl on secondary data from different sources. With less financial constraints, researchers can have more freedom of thought to pursue their curiosity and creativity. ECRs in low- and middle-income countries may find this aspect crucial in their careers. 4. Support and collaboration: The authors share their insights from experiences in the academic publishing system to help readers get through the processes of manuscript writing and peer-reviewing more easily. The authors are also ready to support other researchers with further inquiries and collaboration opportunities at the following website, mindsponge(dot)info. This book is for: a) ECRs whose only abundant resources are their innovation capacity and strength of will; b) Researchers in SSH who want to explore a novel approach to thinking and study conducting; c) Low- and middle-income countries’ researchers looking for a cost-effective research protocol; and, d) Innovative thinkers who want to turn their interesting thoughts into good publications. (shrink)

Prior experimental studies of anomalous information reception (AIR) have been touted as strong evidence for postmortem survival of consciousness yet are plagued by several methodological weaknesses that preclude clear evidence of positive results. The present team provides an adversarial collaboration to identify and compensate for the major limitations of these previous approaches. We outline a more rigorous preregistered study design that eliminates or minimizes researcher bias in (a) data cleaning and (b) statistical analysis. Obtaining positive results with our recommended design (...) would arguably yield data that skeptics and sympathetic researchers would agree is more clearly interpretable and offers stronger support for a survivalist interpretation. However, this proposed study is not intended to be definitive but rather only a next step in a research program that aims to improve on earlier published efforts. It would also admittedly be time-consuming and expensive to implement, as well as raise ethical considerations in utilizing vulnerable research populations. However, these costs are required to achieve the rigor necessary to advance scientific knowledge in survival research. 1. Introduction -- 2. Laying a Working Foundation -- 3. Choice of "Survival Effect" -- 4. The Recommended Preregistered Protocol -- 5. Considerations and Caveats -- 5.1. Strengths of Such Protocol -- 6. Concluding Thoughts. (shrink)

O objetivo deste artigo é analisar as relações entre agnotologia (construção social da ignorância) e o princípio da precaução (PP) sob dois aspectos. O primeiro diz respeito à crítica de que parcela dos defensores do PP teria utilizado estratégias de construção de ignorância. A partir do trabalho do filósofo Daniel Steel, mostro como elas enfraquecem um critério interno ao próprio princípio: a proporcionalidade. Sob o segundo aspecto, comento documentos tornados públicos que evidenciam estratégias de agnotologia por setores da indústria tanto (...) sobre o PP como sobre resultados científicos para que ele não fosse aplicado. Semelhante exposição ainda não foi realizada na literatura especializada no PP. A partir dessa análise, busco contribuir para identificar estratégias de agnotologia em debates sobre o PP. (shrink)

Criticism is a staple of the scientific enterprise and of the social epistemology of science. Philosophical discussions of criticism have traditionally focused on its roles in relation to objectivity, confirmation, and theory choice. However, attention to criticism and to criticizability should also inform our thinking about scientific pursuits: the allocation of resources with the aim of developing scientific tools and ideas. In this paper, we offer an account of scientific pursuitworthiness which takes criticizability as its starting point. We call this (...) the apokritic model of pursuit. Its core ideas are that pursuits are practices governed by norms for asking and answering questions, and that criticism arises from the breach of these norms. We illustrate and advertise our approach using examples from institutional grant review, neuroscience, and sociology. We show that the apokritic model can unify several indices of criticizability, that it can account for the importance of criticizing pursuits in scientific practice, and that it can offer ameliorative advice to erstwhile pursuers. (shrink)

Correlating it to contemporary society, the article in question beckons with the reading of the idols of the cave [Bacon], holding specifically that the question involves the nature of the individual, whose trend can prevail only to adapt the framework of your perspective content resulting from the endoculturação, converging, in short, to the borders of dogma, as highlighted by the emergence of materialistic scientism, in the name of progress, establishing the techno-scientific belief in the assumptions, proposing the credibility of the (...) referential framework of science and technical division of conditionalities as determinants of social change, characterized because, as a false notion, as evidenced by the consequences. (shrink)

The clash between Galileo and the Catholic Inquisition has been discussed, studied, and written about for many decades. The scientific, theological, political, and social implications have all been carefully analysed and appreciated in all their interpretative fruitfulness. The relatively recent trend in this kind of scholarship however seems to have underestimated the fact that Galileo in this debate, as in his earlier debates, showed a particular style marked by overconfidence. If we keep in mind the Lakatosian account of scientific development, (...) it is of course perfectly understandable that scientists at times stick to their convictions by producing auxiliary hypotheses as buffers against contrary evidence. And elements of this are detectable in the arguments of both Galileo and his opponents. But one still needs to ask: To what extent did Galileo depend on auxiliary hypotheses? How insecure did they render his position? And how ad hoc were they? These are important questions because Galileo’s particular way of dealing with auxiliary hypotheses can throw light on the broader question of when and how auxiliary hypotheses are needed within scientific practice in general. It can even indicate some way of conceiving degrees of ad hocness. In this paper, I explore this issue by comparing two important debates in which Galileo was involved: one about the nature of water and buoyancy, the other about cosmology. I revisit not only the scientific content of these debates but also the cultural context in which they took place, especially their dependence on patronage and their theological repercussions. The results indicate that scholarship on Galileo can still be useful in clarifying currently relevant aspects of scientific practice, and is thus still far from its expiry date. (shrink)

(1) In the first part of this paper, I review Chomsky's meandering journey from the formalism/mentalism of Syntactic Structures, through several methodological positions, to the minimalist theory of his latest work. Infected with mentalism from first to last, each and every position vitiates Chomsky's repeated claims that his theories will provide useful guidance to later theories in such fields as cognitive psychology and cognitive neuroscience. With the guidance of his insights, he claims, psychologists and neuroscientists will be able to avoid (...) costly dead-end lines of research. -/- (2) This never happened. As I have shown, this never could have happened. (See Johnston, 2018). What has happened, instead, is that current neurolinguistic research (with the arguable exception of the now-dated Lemma Model of Willem Levelt) proceeds without reference to Chomsky. It also wholeheartedly rejects the mentalism of the associated Language of Thought theory of Jerry Fodor. (See Johnston, 2018). -/- (3) I make this argument in the first part of this paper. I would also like to point out that most of my argument was developed in 1972, when I was a graduate student. I know of no other sustained criticisms of Chomsky at that time, and certainly none along the lines I had developed back then. -/- (4) In the second part of this paper, I present my own account of the methodology of science. When I was a graduate student, philosophy of science was dominated by an attempt to describe a methodology common to all the specific sciences, i.e. Hempel’s deductive-nomological model. These days, Hempel’s emphasis on the methodological unity of science has been rejected by such “dis-unity” philosophers of science as Ian Hacking, Patrick Suppes and Nancy Cartwright (see Cat, 2021). -/- (5) I view this change as the swing of a pendulum or, to change the metaphor, a journey from one end point of a continuum to another. As the level of abstraction at which one tries to describe scientific method is raised, the descriptions become increasingly general. Whether or not unity-of-science theories become so general as to be vacuous, is ultimately a subjective judgment. And so I expect that philosophers will eventually become tired of increasingly specific “close to the workbench” descriptions of how scientists work, and begin to turn back to methodological “big pictures”, finding in them powerful abstractions rather than empty irrelevancies. -/- (6) In the second part of this paper, I present my own account of the methodology of science, which I would situate somewhere between the “unity” and “dis-unity” accounts. However, I am not a scientist. My own views about scientific method have three origins: -/- (6a) my work as a graduate student from 1966 until I passed my comprehensive exams in 1973 (at a different university); -/- (6b) reading every issue of Scientific American from 1972 until nearly 2000, (at which point I continued to read it only sporadically, since I concluded that, around that time, it had evolved from a serious science magazine to a popular science magazine); and -/- (6c) my three-year immersion in the cognitive neuroscience of language after I retired, based on repeated study of and note-taking for (Banesh & Compton, 2018), (Kemmerer, 2015), several other books and, finally, numerous articles not hidden behind a paywall. -/- So, as always with my writings: caveat emptor. (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)

In philosophical studies regarding mathematical models of dynamical systems, instability due to sensitive dependence on initial conditions, on the one side, and instability due to sensitive dependence on model structure, on the other, have by now been extensively discussed. Yet there is a third kind of instability, which by contrast has thus far been rather overlooked, that is also a challenge for model predictions about dynamical systems. This is the numerical instability due to the employment of numerical methods involving a (...) discretization process, where discretization is required to solve the differential equations of dynamical systems on a computer. We argue that the criteria for numerical stability, as usually provided by numerical analysis textbooks, are insufficient, and, after mentioning the promising development of backward analysis, we discuss to what extent, in practice, numerical instability can be controlled or avoided. (shrink)

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)

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)

This paper presents a simple, neutral, unbiased framework for assessing scientific methodologies that serves as both a positive contribution to the literature and an implicit critique of Reber and Alcock’s recent paper in the American Psychologist (2019). This is followed by an explicit critique of some of their key claims.

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)

Summary Popper's methodology does not entail any playing down of the various indispensible distinctions such as the distinction between knowing and guessing, the distinction between myth and science, the distinction between the observational and the theoretical, and between the vernacular and technical sublanguages or technical vocabulary. By avoiding both the totalization that led to the foundationalist position and the scepticist reactions to these frustrated foundationalist hopes, Popper's methodology makes it possible to combine fallibilism with a realist view of theories. It (...) combines the perennial willingness to re-examine positions, statements, etc. with the claim that a particular theory (as an item of knowledge in the objective sense) constitutes cognitive progress over its rivals. However, some of his formulations have been deliberately provocative and in this way have given rise to certain misgivings about possible paradoxical implications, even in philosophers congenial with Popper's approach. The concept of knowledge in the objective sense is, of course, an explicatum which Popper proposes primarily for use in methodology and epistemology. The concept is an expression of the acknowledgment of fallibility in principle. The phrasing that ‘knowledge is conjectural’ or ‘knowledge is fallible’, even when it refers to knowledge in the objective sense, is but an abbreviation for: since our methods for ascertaining the truth-value of a particular statement about empirical reality are fallible in principle, there cannot be any certain knowledge about reality. In everyday life and in politics tolerance will be possible to the extent to which the recognition of this fallibility is more than a declaration. (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)

This paper traces the reception of Babylonian astronomy into the history of science, beginning in early to mid twentieth century when cuneiform astronomical sources became available to the scholarly public. The dominant positivism in philosophy of science of this time influenced criteria employed in defining and demarcating science by historians, resulting in a persistently negative assessment of the nature of knowledge evidenced in cuneiform sources. Ancient Near Eastern astronomy was deemed pre- or non-scientific, and even taken to reflect a stage (...) in the evolution of thought before the emergence of science. Two principal objections are examined: first, that the Near East produced merely practical as opposed to theoretical knowledge and, second, that astronomy was in the service of astrology and religion. As the notion of a universal scientific method has been dismantled by post-positivists and constructivists of the second half of the twentieth century, an interest in varieties of intellectual and cultural contexts for science has provided a new ground for the re-consideration of Babylonian astronomical texts as science developed here.Author Keywords: Babylonian astronomy; Cuneiform texts; Epistemology; Hellenistic astronomy; Religion and science; Theory. (shrink)

After a chapter which is an introduction to and summary of the rest of the book, chapter 2 begins by criticizing various attempts to do away with theories, such as the Reichenbach-Salmon conception of theoretical truth in terms of observational consequences, and the Ramsey strategy of replacing first-order theoretical sentences by second-order nontheoretical ones; it then argues against hypothetico-deductivist theories of confirmation on the grounds that they are unable to handle the relevance of evidence to theory, whether or not other (...) formal constraints or even nonformal ones such as simplicity and explanatory power are added to those theories; it ends with an exposition of the Reichenbach-Carnap conventionalist thesis that the confirmation of hypotheses with evidence presupposes analytic principles connecting hypothetical and empirical concepts. Chapter 3 criticizes Bayesian theories of confirmation on such grounds as that the a priori arguments for Bayesian restrictions on beliefs are insufficient; that the Bayesian explanations of notions like variety of evidence, ad hocness, and simplicity are inadequate; and that they cannot account, without drastic revisions, for the relevance of evidence to theory, especially old evidence to new theory. Chapter 4 is an unsympathetic account of historically oriented philosophies of science; Lakatos’s notion of progressive research programs and Laudan’s theory of problem-solving effectiveness are found to be insufficiently precise and dubbed examples of "new fuzziness", while the Sneed-Stegmüller dynamics of theories is regarded as "a paradigm of misplaced rigor" ; and all three are criticized as unable to explicate the concept of evidential relevance. Chapter 5 is a formal and informal elaboration of the basic idea in Glymour’s account of theory and evidence, namely that confirmation or support is a three-term relation among evidence, hypothesis, and theory, so that evidence confirms an hypothesis only relative to a theory, and such that evidence e confirms hypothesis h relative to T if T with e implies, but T without e does not imply, an instance of h, and T with e does not imply a comparable hypothesis h’ different from h; the most interesting part of this chapter is a series of discussions showing how such an idea makes sense of the "methodological truisms" that it is possible selectively to test certain parts of a theory but not others, that a theory is supported better by a greater variety of evidence, that redundant or physically meaningless quantities are an undesirable feature of theories, that there are no inviolable rules, that a "white shoe" does not confirm "all ravens are black," that a theory is more useful and better supported than the set of its observational consequences, and that the hypothetico-deductive method often works. Since Glymour claims no originality for the conception of this general account, but only for its description, he plausibly thinks it necessary to apply it to some important historical cases of actual science; he does so in the next chapter by discussing at some length the structure and merits of Ptolemaic and Copernican astronomy, of Newton’s universal gravitation, of nineteenth century atomism, of Freud’s Rat Man, and of general relativity. For example, he argues convincingly that Copernicanism was better supported by the evidence available even before the telescope because it alone, and not the Ptolemaic theory, can determine some planetary properties which are presupposed by both theories, can test and confirm some common hypotheses, and can be confirmed in an essential rather than incidental manner; and though Glymour admits that the Copernicans tended to argue in terms of explanatory rather than confirmatory superiority, he sketches an interesting account of the relation between explanation and confirmation which strengthens his case. He also analyzes the text at the beginning of book 3 of Newton’s Principia and compiles a reconstruction of the intricate details of the inferential structure of the argument to universal gravitation; his impressive reconstruction clearly shows that Newton’s method is neither the inductivist one he himself thought he was following, nor the one attributed to him by Pierre Duhem, but rather one in accordance with Glymour’s so-called "bootstrap strategy" of repeatedly using the evidence from Kepler’s second and third laws, from lunar data, and from falling bodies, together with the theory consisting of the second and third laws of motion, to arrive at increasingly general instances of the principle of universal gravitation. Glymour’s account of arguments for and against the atomic theory from Thomson to Cannizzaro is his longest historical example, but he himself admits that this illustration of the bootstrap strategy is "certainly not the neatest", and rather "diffuse, and perhaps disconnected". Chapter 7 is a detailed application of the same principles to the technique known among social scientists as "causal modeling"; since such "causal models" are essentially systems of algebraic equations, Glymour’s account shows indirectly that the bootstrap strategy is applicable to any scientific theory presented as a set of algebraic equations; this, of course is not surprising, since the formal considerations with which Glymour begins the exposition of his theory in chapter 5 involve systems of algebraic equations. Chapter 8 is an attempt to apply Glymour’s theory of evidence to the very common scientific practice of curve-fitting, where one measures values of two or more quantities and then infers a functional relationship; Glymour argues that simpler polynomials are preferred because they are tested more frequently and more severely by the data and because they are more informative; but then he criticizes his own explanation and concludes that "the bootstrap procedures of chapter 5 do not seem to help the problem much more than a whit" ; this is admirably honest, but if one wants an additional logical or methodological rationale, then one would perhaps have to go to the meta-level and say that Glymour is here testing his own theory, and he is more interested in a further illustration of the bootstrap methodology even with a failed test, than he is to claim universal or exclusive validity for it. In chapter 9 Glymour uses his bootstrap theory of confirmation to criticize geometrical conventionalism; he considers the alternative theories of space or space-time proposed by conventionalists to show the radical undetermination of geometries by evidence, for example, a non-Euclidean geometry with no universal force instead of Newtonian gravitation with Euclidean geometry; he argues that such alternatives are simply not as well tested as the originals and that their equivalence to the originals is questionable. The last chapter is a brief discussion of further problems worthy of future investigation. (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)