Hypothetico-Deductive Method

This paper integrates symbolic thought and experimental research. We hypothesized that symbolic narratives provide homeostasis for the complex adaptive system that is personality. Our interpretation of a dream was based, in part, on this hypothesis. We found that the dream retold the myth of Saturn. When, by direct experiment, we tried to falsify our interpretation, our results supported our interpretation and thereby supported our hypothesis. Previously, evidence for this hypothesis had been only anecdotal. __________________________________________ For an audio-record of entire class: (...) link is given on 1st page of the text you download from this page. (shrink)

يوريكا ... كثيرًا ما تُستخدم هذه الكلمة للإشارة إلى لحظة الكشف العلمي، تلك اللحظة الفارقة التي تُولد فيها فجأة فكرةٌ عبقرية في ذهن العالِم أو الباحث، فتفصل بين ما هو غير موجود وما هو موجود، أو بالأحرى بين ما هو غير معروف للمجتمع العملي وما هو سائد ومستهلك حتى بات غير مُشبع لمعالجة المزيد من الوقائع. فما الذي يدفع إلى مثل هذه اللحظة، وماذا يُمكننا أن نفعل لكي تأتي إلينا ونختبرها بشكلٍ مُتكرر؟!

In this essay, I will explain why Methodological Naturalism (MN) fails as a demarcating criteria for science. I will argue that MN is not precise enough to be useful for demarcation, unable to follow the evidence where it leads, not theologically neutral (despite its stated goals as such), and difficult to justify (and currently unjustified) as an ontological or epistemic principle.

Popper’s (1983, 2002) philosophy of science has enjoyed something of a renaissance in the wake of the replication crisis, offering a philosophical basis for the ensuing science reform movement. However, adherence to Popper’s approach may also be at least partly responsible for the sense of “crisis” that has developed following multiple unexpected replication failures. In this article, I contrast Popper’s approach with Lakatos’ (1978) approach and a related approach called naïve methodological falsificationism (NMF; Lakatos, 1978). The Popperian approach is powerful (...) because it is based on logical refutation, but its theories are noncausal and, therefore, lacking in scientific value. In contrast, the Lakatosian approach considers causal theories, but it concedes that these theories are not logically refutable. Finally, the NMF approach subjects Lakatosian causal theories to Popperian logical refutations. However, its approach of temporarily accepting a ceteris paribus clause during theory testing may be viewed as scientifically inappropriate, epistemically inconsistent, and “completely redundant” (Lakatos, 1978, p. 40). I conclude that the replication “crisis” makes the most sense in the context of the Popperian and NMF approaches because it is only in these two approaches that replication failures represent logical refutations of theories. In contrast, replication failures are less problematic in the Lakatosian approach because they do not logically refute theories. Indeed, in the Lakatosian approach, replication failures can be legitimately ignored or used to motivate theory development. (shrink)

One justification for preregistering research hypotheses, methods, and analyses is that it improves the transparent evaluation of the severity of hypothesis tests. In this article, I consider two cases in which preregistration does not improve this evaluation. First, I argue that, although preregistration can facilitate the transparent evaluation of severity in Mayo’s error statistical philosophy of science, it does not facilitate this evaluation in Popper’s theory-centric approach. To illustrate, I show that associated concerns about Type I error rate inflation are (...) only relevant in the error statistical approach and not in a theory-centric approach. Second, I argue that a preregistered test procedure that allows deviations in its implementation does not provide a more transparent evaluation of Mayoian severity than a non-preregistered procedure. In particular, I argue that sample-based validity-enhancing deviations cause an unknown inflation of the test procedure’s Type I (familywise) error rate and, consequently, an unknown reduction in its capability to license inferences severely. I conclude that preregistration does not improve the transparent evaluation of severity in Popper’s philosophy of science or when deviations are allowed. (shrink)

The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Questionable research practices such as p-hacking are thought to inflate Type I error rates above their nominal level, leading to unexpectedly high levels of false positives in the literature and, consequently, unexpectedly low replication rates. In this article, I offer an alternative view. I argue that questionable and other research practices do not usually inflate relevant Type I error rates. I begin (...) by introducing the concept of Type I error rates and distinguishing between statistical errors and theoretical errors. I then illustrate my argument with respect to model misspecification, multiple testing, selective inference, forking paths, exploratory analyses, p-hacking, optional stopping, double dipping, and HARKing. In each case, I demonstrate that relevant Type I error rates are not usually inflated above their nominal level, and in the rare cases that they are, the inflation is easily identified and resolved. I conclude that the replication crisis may be explained, at least in part, by researchers’ misinterpretation of statistical errors and their underestimation of theoretical errors. (shrink)

I reconstruct J. H. Lambert’s views on how practical grounds relate to epistemic features, such as certainty. I argue, first, that Lambert’s account of moral certainty does not involve any distinctively practical influence on theoretical belief. However, it does present an interesting form of fallibilism about justification as well as a denial of a tight link between knowledge and action. Second, I argue that for Lambert, the persistence principle that underwrites induction is supported by practical reasons to believe; this indicates (...) that Lambert is a moderate pragmatist about reasons for theoretical belief. (shrink)

Pierre-Sylvain Régis’s Cartesianism is quite singular in seventeenth-century French philosophy. Though, can we speak of a form of experimental science in Régis’s work? After exploring his notions of ‘system’ and ‘hypothesis’, I will define his position in relation to Claude Perrault, Jacques Rohault, and the Royal Society. I argue, first, that the contrasts which traverse French science are not so much about the use of experiments but about whether or not observational data can be traced back to hypotheses and to (...) a coherent system. Secondly, that we can detect a significant similarity between Boyle’s positions and the views expressed by Perrault and also by Régis. Lastly, that French science, even in its Cartesian version, is much more probabilistic than English experimental philosophy. (shrink)

This volume takes cue from the idea that the thought of no philosopher can be understood without considering it as the result of a constant, lively dialogue with other thinkers, both in its internal evolution as well as in its reception, re-use, and assumption as a starting point in addressing past and present philosophical problems. In doing so, it focuses on a feature that is crucially emerging in the historiography of early modern philosophy and science, namely the complexity in the (...) production of knowledge. The book explores the applicability of this approach to a long-considered armchair philosopher, namely René Descartes, who is now more and more understood as a full-blown scientist, networker, and intellectual éminence grise rather than as the mere philosopher of the cogito, as well as the originator of different ‘Cartesianisms’ which encompassed many ideas and approaches for long captured by dichotomic historiographical categories as rationalism and empiricism, or speculative and experimental philosophy. The essays gathered in the volume aim to address the ways in which Descartes’s philosophy evolved and was progressively understood by scientists, philosophers, and intellectuals from different contexts and eras, either by considering direct interlocutors of Descartes such as Isaac Beeckman and Elisabeth of Bohemia, early modern thinkers who developed upon his ideas and on particular topics as Nicolas Malebranche or Thomas Willis, those who adapted his overall methodology in developing new systems of knowledge as Johannes Clauberg and Pierre-Sylvain Régis, and contemporary thinkers from continental and analytic traditions like Emanuele Severino and Peter Strawson. (shrink)

A review of Gary Smith and Jay Cordes: The Phantom Pattern Problem: The Mirage of Big Data. New York: Oxford University Press, 2020.

It is generally accepted among philosophers of science that hypothesis testing is a key methodological feature of science. As far as philosophical theories of confirmation are con...

The indisputable success of experimental science caused a division in philosophy at the turn of the 21st century. A substantial part of philosophers was inspired by ground-breaking writings of W. V. O. Quine and they followed philosophical naturalism that considers hypothetical-deductive method the most effective or the only way to acquire justified true beliefs. Other philosophers are worried about the hegemony of empirical sciences and warn against excessive ambitions of scientific methodology. Scientism or scientific imperialism is a point of view, (...) according to which there are no boundaries of scientific knowledge. According to its supporters, science can describe and explain what is to be described and explained. In my paper I will introduce some common ways how to define and criticize scientism and scientific imperialism. The aim is to demonstrate that criticism of scientism and scientific imperialism is based on the incorrect understanding of what scientific methodology is, how scientific knowledge emerges from natural cognition and in which ways science differs from its alternatives. (shrink)

There are a bewildering variety of claims connecting Darwin to nineteenth-century philosophy of science—including to Herschel, Whewell, Lyell, German Romanticism, Comte, and others. I argue here that Herschel’s influence on Darwin is undeniable. The form of this influence, however, is often misunderstood. Darwin was not merely taking the concept of “analogy” from Herschel, nor was he combining such an analogy with a consilience as argued for by Whewell. On the contrary, Darwin’s Origin is written in precisely the manner that one (...) would expect were Darwin attempting to model his work on the precepts found in Herschel’s Preliminary Discourse on Natural Science. While Hodge has worked out a careful interpretation of both Darwin and Herschel, drawing similar conclusions, his interpretation misreads Herschel’s use of the vera causa principle and the verification of hypotheses. The new reading that I present here resolves this trouble, combining Hodge’s careful treatment of the structure of the Origin with a more cautious understanding of Herschel’s philosophy of science. This interpretation lets us understand why Darwin laid out the Origin in the way that he did and also why Herschel so strongly disagreed, including in Herschel’s heretofore unanalyzed marginalia in his copy of Darwin’s book. (shrink)

There is widespread recognition at universities that a proper understanding of science is needed for all undergraduates. Good jobs are increasingly found in fields related to Science, Technology, Engineering, and Medicine, and science now enters almost all aspects of our daily lives. For these reasons, scientific literacy and an understanding of scientific methodology are a foundational part of any undergraduate education. Recipes for Science provides an accessible introduction to the main concepts and methods of scientific reasoning. With the help of (...) an array of contemporary and historical examples, definitions, visual aids, and exercises for active learning, the textbook helps to increase students’ scientific literacy. The first part of the book covers the definitive features of science: naturalism, experimentation, modeling, and the merits and shortcomings of both activities. The second part covers the main forms of inference in science: deductive, inductive, abductive, probabilistic, statistical, and causal. The book concludes with a discussion of explanation, theorizing and theory-change, and the relationship between science and society. The textbook is designed to be adaptable to a wide variety of different kinds of courses. In any of these different uses, the book helps students better navigate our scientific, 21st-century world, and it lays the foundation for more advanced undergraduate coursework in a wide variety of liberal arts and science courses. Selling Points Helps students develop scientific literacy—an essential aspect of _any_ undergraduate education in the 21 st century, including a broad understanding of scientific reasoning, methods, and concepts Written for all beginning college students: preparing science majors for more focused work in particular science; introducing the humanities’ investigations of science; and helping non-science majors become more sophisticated consumers of scientific information Provides an abundance of both contemporary and historical examples Covers reasoning strategies and norms applicable in all fields of physical, life, and social sciences, _as well as_ strategies and norms distinctive of specific sciences Includes visual aids to clarify and illustrate ideas Provides text boxes with related topics and helpful definitions of key terms, and includes a final Glossary with all key terms Includes Exercises for Active Learning at the end of each chapter, which will ensure full student engagement and mastery of the information include earlier in the chapter Provides annotated ‘For Further Reading’ sections at the end of each chapter, guiding students to the best primary and secondary sources available Offers a Companion Website, with: For Students: direct links to many of the primary sources discussed in the text, student self-check assessments, a bank of exam questions, and ideas for extended out-of-class projects For Instructors: a password-protected Teacher’s Manual, which provides student exam questions with answers, extensive lecture notes, classroom-ready Power Point presentations, and sample syllabi Extensive Curricular Development materials, helping any instructor who needs to create a Scientific Reasoning Course, ex nihilo. (shrink)

Confirmation and falsification are different strategies for testing theories and characterizing the outcomes of those tests. Roughly speaking, confirmation is the act of using evidence or reason to verify or certify that a statement is true, definite, or approximately true, whereas falsification is the act of classifying a statement as false in the light of observation reports. After expounding the intellectual history behind confirmation and falsificationism, reaching back to Plato and Aristotle, I survey some of the main controversial issues and (...) arguments that pertain to the choice between these strategies: the Raven Paradox, the Duhem/Quine problem and the Grue Paradox. Finally, I outline an evolutionary criticism of inductive Bayesian approaches based on my assumption of doxastic involuntarism. (shrink)

How was the hypothetical character of theories of experience thought about throughout the history of science? The essays cover periods from the middle ages to the 19th and 20th centuries. It is fascinating to see how natural scientists and philosophers were increasingly forced to realize that a natural science without hypotheses is not possible.

The two principal models of design in methodological circles in architecture—analysis/synthesis and conjecture/analysis—have their roots in philosophy of science, in different conceptions of scientific method. This paper explores the philosophical origins of these models and the reasons for rejecting analysis/synthesis in favour of conjecture/analysis, the latter being derived from Karl Popper’s view of scientific method. I discuss a fundamental problem with Popper’s view, however, and indicate a framework for conjecture/analysis to avoid this problem.

يناقش الكتاب دور النماذج الفكرية والمادية في اكتساب وتشكيل كافة أنماط المعارف الإنسانية، بداية من المعرفة العادية التي يسعى بها عامة الناس إلى فهم ما يدور حولهم من أمور الحياة، ومرورًا بالمعارف الفلسفية والدينية والفنية التي تحكم توجهات الإنسان العقلانية والوجدانية، ووصولاً إلى المعرفة العلمية الرامية إلى فهم ظواهر الكون وترويضها وفقًا لقوانين حاكمة. ويطرح الكتاب فرضًا أساسيًا مؤداه أن ما يتلفظ به العلماء من كلمات مثل «الفرض» و«القانون» و«النظرية» ما هي إلا أسماء مترادفة لشيء واحد يصب في خانة «النموذج»، (...) وإذا كان ثمة فرق بين ما نعنيه بهذه الكلمات، فهو في الحقيقة فرقٌ في الدرجة لا في النوع، أو هو فرق بين نموذج أولي في مرحلة الفرض، وبين ذات النموذج في مرحلة القانون أو النظرية، وعلى هذا فمن الأجدر بنا ألا نتحدث عن فرض أو قانون أو نظرية، وإنما عن «نموذج علمي» يمر بمراحل متعددة حتى يتم تأكيده وقبوله، وهو في الوقت ذاته عُرضة لأن يحل محله نموذج آخر إذا اتسعت دائرة البحث لتشمل وقائع أخرى لا يحتويها النموذج أو يعجز عن تفسيرها. (shrink)

The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in the semantic view of theories; (...) the applicability of mathematical models to the real world and their effectiveness; the links between models and inferences; and models as a means for acquiring new knowledge. It analyzes different examples of models in physics, biology, mathematics and engineering. Written for researchers and graduate students, it provides a cross-disciplinary reference guide to the notion and the use of models and inferences in science. (shrink)

A short reconstruction of the Medieval and early modern idea of the analytic-syntetic method.

A short reconstruction of the analytic-synthetic method, a key idea in Medieval and Early Modern Logic.

During the 1630s Descartes recognized that he could not expect all legitimate claims in natural science to meet the standard of absolute certainty. The realization resulted from a change in his physics, which itself arose not through methodological reflections, but through developments in his substantive metaphysical doctrines. Descartes discovered the metaphysical foundations of his physics in 1629-30; as a consequence, the style of explanation employed in his physical writings changed. His early methodological conceptions, as preserved in the Rules and sketched (...) in Part Two of the Discourse, pertained primarily to his early work in optics. By the early 1630s, Descartes was concerned with new methodological problems pertaining to the postulation of micro-mechanisms. Recognition of the need to employ a method of hypothesis led him to lower the standard of certainty required of particular explanations in his mature physics. (shrink)

Abstract: This study explores some theoretical issues in scientific research such as, the nature of experimentation and problems of methodology in scientific practice as well as the question of truth, rationality, objectivity and utility of scientific discoveries. The paper discusses a number of theorizing that have emerged in response to the challenge raised by the above concerns. Epistemological models of science from critical rationalists, like Popper, Kuhn, Feyerabend and the neo-pragmatic methodological orientation of Arthur Fine’s Natural Ontological Attitude (NOA) to (...) Science, have been adopted as points of discussion on what science as an empirical discipline entail. The paper concludes that a rigorous epistemological discussion on the methodology of scientific inquiry is a desideratum for the progress of science. (shrink)