Scientific Method, Miscellaneous

Is there a universal set of rules for discovering and testing scientific hypotheses? Since the birth of modern science, philosophers, scientists, and other thinkers have wrestled with this fundamental question of scientific practice. Efforts to devise rigorous methods for obtaining scientific knowledge include the twenty-one rules Descartes proposed in his Rules for the Direction of the Mind and the four rules of reasoning that begin the third book of Newton's Principia , and continue today in debates over the very possibility (...) of such rules. Bringing together key primary sources spanning almost four centuries, Science Rules introduces readers to scientific methods that have played a prominent role in the history of scientific practice. Editor Peter Achinstein includes works by scientists and philosophers of science to offer a new perspective on the nature of scientific reasoning. For each of the methods discussed, he presents the original formulation of the method selections written by a proponent of the method together with an application to a particular scientific example and a critical analysis of the method that draws on historical and contemporary sources. The methods included in this volume are Cartesian rationalism with an application to Descartes' laws of motion Newton's inductivism and the law of gravity two versions of hypothetico-deductivism -- those of William Whewell and Karl Popper -- and the nineteenth-century wave theory of light Paul Feyerabend's principle of proliferation and Thomas Kuhn's views on scientific values, both of which deny that there are universal rules of method, with an application to Galileo's tower argument. Included also is a famous nineteenth-century debate about scientific reasoning between the hypothetico-deductivist William Whewell and the inductivist John Stuart Mill and an account of the realism-antirealism dispute about unobservables in science, with a consideration of Perrin's argument for the existence of molecules in the early twentieth century. (shrink)

The received view of an ad hochypothesis is that it accounts for only the observation(s) it was designed to account for, and so non-ad hocness is generally held to be necessary or important for an introduced hypothesis or modification to a theory. Attempts by Popper and several others to convincingly explicate this view, however, prove to be unsuccessful or of doubtful value, and familiar and firmer criteria for evaluating the hypotheses or modified theories so classified are characteristically available. These points (...) are obscured largely because the received view fails to adequately separate psychology from methodology or to recognise ambiguities in the use of ''ad hoc''. (shrink)

There is a very plausible principle of the transitivity of justifying reasons. It says that if "p" is better justified than "q" (all things considered) and "q" better than "r", then "p" is better justified than "r" (all things considered). There is a corresponding principle of rational theory choice. Call one theory "a better theory than" another theory if all criteria of theory choice considered (explanatory power, simplicity, empirical adequacy, etc.), the first theory meets the criteria better than the second (...) theory. The corresponding transitivity principle says that if theory A is a better theory than theory B and if theory B is a better theory than theory C, then A is a better theory than theory C. I argue against this principle. It turns out that whenever there are 2 or more relevant and independent criteria of theory evaluation, and whenever at least of one the criteria is "non-linear" in a certain sense, there may be violations of transitivity which do not violate any standards of rationality (of theory choice). This shows, again, that theory choice cannot be seen as merely the application of given rules of rational theory choice. (shrink)

The first part of this paper shows that Qualitative Comparative Analysis (QCA)--also in its most recent forms as presented in Ragin (2000, 2008)--, does not correctly analyze data generated by causal chains, which, after all, are very common among causal processes in the social sciences. The incorrect modeling of data originating from chains essentially stems from QCA’s reliance on Quine-McCluskey optimization to eliminate redundancies from sufficient and necessary conditions. Baumgartner (2009a,b) has introduced a Boolean methodology, termed Coincidence Analysis (CNA), that (...) is related to QCA, yet, contrary to the latter, does not eliminate redundancies by means of Quine-McCluskey optimization. The second part of the paper applies CNA to chain-generated data. It will turn out that CNA successfully detects causal chains in small-N data. (shrink)

While standard procedures of causal reasoning as procedures analyzing causal Bayesian networks are custom-built for (non-deterministic) probabilistic struc- tures, this paper introduces a Boolean procedure that uncovers deterministic causal structures. Contrary to existing Boolean methodologies, the procedure advanced here successfully analyzes structures of arbitrary complexity. It roughly involves three parts: first, deterministic dependencies are identified in the data; second, these dependencies are suitably minimalized in order to eliminate redundancies; and third, one or—in case of ambiguities—more than one causal structure is (...) assigned to the minimalized deterministic dependencies. (shrink)

Bayesians often assume, suppose, or conjecture that for any reasonable explication of the notion of simplicity a prior can be designed that will enforce a preference for hypotheses simpler in just that sense. But it is shown here that there are simplicity-driven approaches to curve-fitting problems that cannot be captured within the orthodox Bayesian framework.

Poincaré’s conventionalism has thoroughly transformed both the philosophy of science and the philosophy of mathematics. In the former it gave rise to new insights into the complexities of scientific method, in the latter to a new account of the nature of (so-called) necessary truth. Not only proponents of conventionalism, such as the logical positivists, were influenced by Poincaré, but also outspoken critics of conventionalism, such as Quine, Putnam, and (as I will argue) Wittgenstein, were deeply inspired by conventionalist ideas. Indeed, (...) during the twentieth century, most philosophers of science and mathematics engaged in dialogue with conventionalism. As is often the case with complex ideas, there is no consensus about the meaning of conventionalism in general and Poincaré’s original version of it in particular. Nonetheless, notions such as underdetermination (of theory), empirical equivalence (of incompatible theories), implicit definition, holism, and conceptual relativity, all of which can be linked to Poincaré’s writings, have become central to philosophy. In tracing the flow of Poincaré’s ideas through the philosophical space of the twentieth century, this article emphasizes not only the stimulus provided by his actual views but also the effects of misreading and unjustified appropriation. (shrink)

This discussion paper proposes that a meaningful distinction between science and technoscience can be found at the level of the objects of research. Both notions intermingle in the attitudes, intentions, programs and projects of researchers and research institutions—that is, on the side of the subjects of research. But the difference between science and technoscience becomes more explicit when research results are presented in particular settings and when the objects of research are exhibited for the specific interest they hold. When an (...) experiment is presented as scientific evidence which confirms or disconfirms a hypothesis, this agrees with traditional conceptions of science. When organic molecules are presented for their capacity to serve individually as electric wires that carry surprisingly large currents, this would be a hallmark of technoscience. Accordingly, we propose research on the ontology of research objects. The focus on the character and significance of research objects makes this a specifically philosophical project. (shrink)

A part of the scientific literature consists of intermediate results within a longer project. Scientists often publish a first result in the course of their work, while aware that they should soon achieve a more advanced result from this preliminary result. Should they follow the proverb “a bird in the hand is worth two in the bush”, and publish any intermediate result they get? This is the normative question addressed in this paper. My aim is to clarify, to refine, and (...) to assess informal arguments about the choice whether to publish intermediate results. To this end, I adopt a rational decision framework, supposing some utility or preferences, and I propose a formal model. The best publishing strategy turns out to depend on the research situation. In some simple circumstances, even selfish and short-minded scientists should publish their intermediate results, and should thus behave like their altruistic peers, i. e. like society would like them to behave. In other research situations, with inhomogeneous reward or difficulty profiles, the best strategy is opposite. These results suggest qualified philosophical morals. (shrink)

Should the Christian community engage in Christian science – doing science starting from the standpoint of the Christian evidence base? Plantinga asks this question, and I argue that the answer is ‘yes’. Moreover, this is an answer that both Christians and atheists can agree upon. Scientific progress should not be shackled by methodological naturalism; instead we need an ecumenical approach to science, which will allow for various high-level research programmes to count as science (including Christian science). If one does science (...) by giving scientific arguments for or against such research programmes, one will fulfil the goal of having science be objective, open, and universal, not constrained by a methodology that favours the naturalistic worldview. (shrink)

This chapter explores the idea that causal inference is warranted if and only if the mechanism underlying the inferred causal association is identified. This mechanistic stance is discernible in the epidemiological literature, and in the strategies adopted by epidemiologists seeking to establish causal hypotheses. But the exact opposite methodology is also discernible, the black box stance, which asserts that epidemiologists can and should make causal inferences on the basis of their evidence, without worrying about the mechanisms that might underlie their (...) hypotheses. I argue that the mechanistic stance is indeed a bad methodology for causal inference. However, I detach and defend a mechanistic interpretation of causal generalisations in epidemiology as existence claims about underlying mechanisms. (shrink)

In this paper we show that the coherence measures of Olsson (J Philos 94:246–272, 2002), Shogenji (Log Anal 59:338–345, 1999), and Fitelson (Log Anal 63:194–199, 2003) satisfy the two most important adequacy requirements for the purpose of assessing theories. Following Hempel (Synthese 12:439–469, 1960), Levi (Gambling with truth, New York, A. A. Knopf, 1967), and recently Huber (Synthese 161:89–118, 2008) we require, as minimal or necessary conditions, that adequate assessment functions favor true theories over false theories and true and informative (...) theories over true but uninformative theories. We then demonstrate that the coherence measures of Olsson, Shogenji, and Fitelson satisfy these minimal conditions if we confront the hypotheses with a separating sequence of observational statements. In the concluding remarks we set out the philosophical relevance, and limitations, of the formal results. Inter alia, we discuss the problematic implications of our precondition that competing hypotheses must be confronted with a separating sequence of observational statements, which also leads us to discuss theory assessment in the context of scientific antirealism. (shrink)

Taking Carnap’s classic exposition as a starting point, this paper develops a pragmatic account of the method of explication, defends it against a range of challenges and proposes a detailed recipe for the practice of explicating. It is then argued that confusions are involved in characterizing explications as definitions, and in advocating precising definitions as an alternative to explications. Explication is better characterized as conceptual re-engineering for theoretical purposes, in contrast to conceptual re-engineering for other purposes and improving exactness for (...) purely practical reasons. Finally, three limitations which call for further development of the method of explication are discussed. (shrink)

The nature of the scientific method has been a main concern of philosophy from Plato to Mill. In that period logic has been considered to be a part of the methodology of science. Since Mill, however, the situation has completely changed. Logic has ceased to be a part of the methodology of science, and no Discourse on method has been written. Both logic and the methodology of science have stopped dealing with the process of discovery, and generally with the actual (...) process of scientific research. As a result, several first-rate scientists, from Feynman and Weinberg to Dyson and Hawkins, have concluded that philosophy has become useless and totally irrelevant to science. The aim of this paper is to give some indications as to how to develop a logic concerned with the process of discovery and a methodology of science dealing with the actual process of scientific research. (shrink)

WE AIM HERE to outline a theory of evidence for use. More specifically we lay foundations for a guide for the use of evidence in predicting policy effectiveness in situ, a more comprehensive guide than current standard offerings, such as the Maryland rules in criminology, the weight of evidence scheme of the International Agency for Research on Cancer (IARC), or the US ‘What Works Clearinghouse’. The guide itself is meant to be well-grounded but at the same time to give practicable (...) advice, that is, advice that can be used by policy-makers not expert in the natural and social sciences, assuming they are well-intentioned and have a reasonable but limited amount of time and resources available for searching out evidence and deliberating. (shrink)

What is special about the philosophy of history when the history is about science? I shall focus on an impasse between two perspectives — one seeking an ideal of rationality to guide scientific practices, and one stressing the contingency of the practices. They disagree on what this contingency means for scientific norms. Their impasse underlies some fractious relations within History and Philosophy of Science. Since the late 1960s, this interdisciplinary field has been described, variously, as an “intimate relationship or marriage (...) of convenience”, a “marriage for the sake of reason”, a “troubling interaction ”, a “precarious relationship”, or one at risk of “ epistemological derangement”. -/- My paper has three aims. First, I characterise two idealised perspectives in this impasse: the sublimers and subversives. Then I describe a curious dynamic in which each perspective accuses the other of, simultaneously, claiming too little and too much. Subliming is dismissed for being scholastic, and condemned for being imperialist. Subverting is disparaged for being merely sociological, then criticised for being irrational or relativist. Here I draw on and extend the analyses of science studies in Kitcher, Zammito and others. Second, I argue that sublimers and subversives often talk past each other. Their mutual dismissals and condemnations arise partly because each perspective misconstrues the other’s claims. Each fails to see that the other is interested in different problems and interprets concepts differently. Third, I suggest that my analysis clarifies some current disagreements and old debates about contingency in science. It may also apply to debates on the contingency of norms in non- scientific realms. (shrink)

Defenders of Inference to the Best Explanation claim that explanatory factors should play an important role in empirical inference. They disagree, however, about how exactly to formulate this role. In particular, they disagree about whether to formulate IBE as an inference rule for full beliefs or for degrees of belief, as well as how a rule for degrees of belief should relate to Bayesianism. In this essay I advance a new argument against non-Bayesian versions of IBE. My argument focuses on (...) cases in which we are concerned with multiple levels of explanation of some phenomenon. I show that in many such cases, following IBE as an inference rule for full beliefs leads to deductively inconsistent beliefs, and following IBE as a non-Bayesian updating rule for degrees of belief leads to probabilistically incoherent degrees of belief. (shrink)

In their paper, 'When are thought experiments poor ones?' (Peijnenburg and Atkinson, 2003, Journal of General Philosophy of Science 34, 305-322), Jeanne Peijnenburg and David Atkinson argue that most, if not all, philosophical thought experiments are "poor" ones with "disastrous consequences" and that they share the property of being poor with some (but not all) scientific thought experiments. Noting that unlike philosophy, the sciences have the resources to avoid the disastrous consequences, Peijnenburg and Atkinson come to the conclusion that the (...) use of thought experiments in science is in general more successful than in philosophy and that instead of concocting more "recherché" thought experiments, philosophy should try to be more empirical. In this comment I will argue that Peijnenburg's and Atkinson's view on thought experiments is based on a misleading characterization of both, the dialectical situation in philosophy as well as the history of physics. By giving an adequate account of what the Discussion in contemporary philosophy is about, we will arrive at a considerably different evaluation of philosophical thought experiments. (shrink)

Review of Soler et al. (eds.) Characterizing the robustness of science: After the practice turn in philosophy of science.

One of the most powerful tools in science is the analytic method, whereby we seek to understand complex systems by studying simpler sub-systems from which the complex is composed. If this method is to be successful, something about the sub-systems must remain invariant as we move from the relatively isolated conditions in which we study them, to the complex conditions in which we want to put our knowledge to use. This paper asks what this invariant could be. The paper shows (...) that the kinds of thing that a Humean might point to – behaviour, laws, and dispositions – cannot play the role required of the invariant in question. Nor, indeed, can non-Humean causal powers of the kind advocated by contemporary metaphysicians such as Ellis and Lierse. The paper suggests that the analytic method presupposes a kind of entity that does not appear in standard ontologies – a metaphysically substantial notion of causal influence. This notion of causal influence is one that Cartwright has also seen the need for, though she does not seem to take the notion as seriously as she should. (shrink)

In this article I attempt to reconstruct David Hume's use of the label ?experimental? to characterise his method in the Treatise. Although its meaning may strike the present-day reader as unusual, such a reconstruction is possible from the background of eighteenth-century practices and concepts of natural inquiry. As I argue, Hume's inquiries into human nature are experimental not primarily because of the way the empirical data he uses are produced, but because of the way those data are theoretically processed. He (...) seems to follow a method of analysis and synthesis quite similar to the one advertised in Newton's Opticks, which profoundly influenced eighteenth-century natural and moral philosophy. This method brings him much closer to the methods of qualitative, chemical investigations than to mechanical approaches to both nature and human nature. (shrink)

Current philosophical reflections on science have departed from mainstream history of science with respect to both methodology and conclusions. The article investigates how different approaches to reconstructing commitments can explain these differences and facilitate a mutual understanding and communication of these two perspectives on science. Translating the differences into problems pertaining to principles of charity, the paper offers a platform for clarification and resolution of the differences between the two perspectives. The outlined contextual approach occupies a middle ground between mainstream (...) history and sociology of science, bracketing questions of rationality, and individual coherence-maximizing, rationality-centered approaches. It can satisfy those, who believe that science is an epistemically privileged endeavor, and its epistemic content should not be neglected when reconstructing the scientists’ positions. It can also satisfy those who hold that it is naive to believe that the immediate context, e.g. the challenges to a theory, the expectations of the author about his audience, etc., does not affect the position a scientist takes. Its theoretical considerations are exemplified with a close study of the debate following the 1672 publication of Newton's theory of light and colours, also offering a novel reading of the development of his methodological views concerning the demonstrativity of the famous crucial experiment. Although we only show the capacity of the framework to analyze a direct controversy, given that it is hard to think about any scientific text as detached from an argumentative context, this approach has the potential to be a general guide for interpretation. (shrink)

This work was originally published anonymously.

This is a review essay of what is probably the best contribution to the history of the philosophical investigation into thought experiments.

Interest in the computational aspects of modeling has been steadily growing in philosophy of science. This paper aims to advance the discussion by articulating the way in which modeling and computational errors are related and by explaining the significance of error management strategies for the rational reconstruction of scientific practice. To this end, we first characterize the role and nature of modeling error in relation to a recipe for model construction known as Euler’s recipe. We then describe a general model (...) that allows us to assess the quality of numerical solutions in terms of measures of computational errors that are completely interpretable in terms of modeling error. Finally, we emphasize that this type of error analysis involves forms of perturbation analysis that go beyond the basic model-theoretical and statistical/probabilistic tools typically used to characterize the scientific method; this demands that we revise and complement our reconstructive toolbox in a way that can affect our normative image of science. (shrink)

Conceptual metaphors facilitate both productive and pernicious analogical reasoning. This article addresses the question: When and why does the frequently helpful use of metaphor become pernicious? By applying the most influential theoretical framework from cognitive psychology in analysing the philosophically most prominent example of pernicious metaphorical reasoning, we identify a philosophically relevant but previously undescribed fallacy in analogical reasoning with metaphors. We then outline an explanation of why even competent thinkers commit this fallacy and obtain a psychologically informed ‘debunking’ explanation (...) of the kind experimental philosophy’s ‘sources project’ seeks. (shrink)

Lakatos's methodology, if analysed as belonging to the demarcationist-rationalist program launched by Popper gives some interesting conclusions concerning the feasibility of the project: (1) Rationalism cannot provide arguments against relativism. (2) A theory of scientific rationality cannot be defended without relying on scientific authorities. (3) A historical justification of scientific rationality does not show that the procedures that are rational according to the theory are truth-conducive.

Peirce claims that the methods of abduction, deduction and induction are jointly sufficient for the attainment of truth, regardless of the state of belief from which inquiry begins. This article summarizes Peirce’s defence of the thesis that the scientific method is self-corrective and addresses common mistakes in its interpretation.

A very brief outline of Popper's methodology.

In recent years, several authors have debated about the justifiability of so-called scientific imperialism. To date, however, widespread disagreements remain regarding both the identification and the normative evaluation of scientific imperialism. In this paper, I aim to remedy this situation by making some conceptual distinctions concerning scientific imperialism and by providing a detailed assessment of the most prominent objections to it. I shall argue that these objections provide a valuable basis for opposing some instances of scientific imperialism, but do not (...) yield cogent reasons to think that scientific imperialism in general is objectionable or unjustified. I then highlight three wide-ranging implications of this result for the ongoing philosophical debate about the justifiability of scientific imperialism. (shrink)

In (Gebharter 2014) I suggested a framework for modeling the hierarchical organization of mechanisms. In this short addendum I want to highlight some connections of my approach to the statistics and machine learning literature and some of its limitations not mentioned in the paper.

Editors’ introduction to the monographic section _Explanation, Causality, and Unification_.

In its last round of publications in September 2012, the Encyclopedia Of DNA Elements (ENCODE) assigned a biochemical function to most of the human genome, which was taken up by the media as meaning the end of ‘Junk DNA’. This provoked a heated reaction from evolutionary biologists, who among other things claimed that ENCODE adopted a wrong and much too inclusive notion of function, making its dismissal of junk DNA merely rhetorical. We argue that this criticism rests on misunderstandings concerning (...) the nature of the ENCODE project, the relevant notion of function and the claim that most of our genome is junk. We argue that evolutionary accounts of function presuppose functions as ‘causal roles’, and that selection is but a useful proxy for relevant functions, which might well be unsuitable to biomedical research. Taking a closer look at the discovery process in which ENCODE participates, we argue that ENCODE’s strategy of biochemical signatures successfully identified activities of DNA elements with an eye towards causal roles of interest to biomedical research. We argue that ENCODE’s controversial claim of functionality should be interpreted as saying that 80 % of the genome is engaging in relevant biochemical activities and is very likely to have a causal role in phenomena deemed relevant to biomedical research. Finally, we discuss ambiguities in the meaning of junk DNA and in one of the main arguments raised for its prevalence, and we evaluate the impact of ENCODE’s results on the claim that most of our genome is junk. (shrink)

This essay proposes an ontological model in which a legal person such as a polity possesses natural unity from group properties that emerge in the self-organization of the human population. Also, analysis of customary legal persons and property indicates noncontradictory paradoxes that include Aristotelian essence of an entity, relative identity over time, ubiquitous authority, coinciding authorities, and identical entities. Mathematical modeling helps to explain the logic of the paradoxes.

Acknowledging that Nature is one unified whole, we expect that physics and biology are intimately related. Keeping in mind that physics became an exact science with which we are already familiar with, while, apparently, we do not have at present a similar knowledge about biology, we consider how can we make useful the clarity of physics to shed light to biology. The next question will be what are the most basic categories of physics and biology. If we do not want (...) to cut laws of Nature into different parts, we obtain a constraint, and the remaining part of physics will be the input data to the equations of physics. In these terms, our question will be: if we keep biological laws intact, as indivisible units, what remains in case of biology? This approach, just because it is more fundamental, has significant consequences for philosophy, and obviously offers a new conceptual framework considering the relation between the ontopoietic principle of Anna-Teresa Tymieniecka and the biological principle. The quintessence of science, namely, the first essentially complete scientific world picture is presented in a detailed form. (shrink)

Life scientists increasingly rely upon abstraction-based modeling and reasoning strategies for understanding biological phenomena. We introduce the notion of constraint-based reasoning as a fruitful tool for conceptualizing some of these developments. One important role of mathematical abstractions is to impose formal constraints on a search space for possible hypotheses and thereby guide the search for plausible causal models. Formal constraints are, however, not only tools for biological explanations but can be explanatory by virtue of clarifying general dependency-relations and patterning between (...) functions and structures. We describe such situations as constraint-based explanations and argue that these differ from mechanistic strategies in important respects. While mechanistic explanations emphasize change-relating causal features, constraint-based explanations emphasize formal dependencies and generic organizational features that are relatively independent of lower-level changes in causal details. Our distinction between mechanistic and constraint-based explanations is pragmatically motivated by the wish to understand scientific practice. We contend that delineating the affordances and assumptions of different explanatory questions and strategies helps to clarify tensions between diverging scientific practices and the innovative potentials in their combination. Moreover, we show how constraint-based explanation integrates several features shared by otherwise different philosophical accounts of abstract explanatory strategies in biology. (shrink)

The increasing application of network models to interpret biological systems raises a number of important methodological and epistemological questions. What novel insights can network analysis provide in biology? Are network approaches an extension of or in conflict with mechanistic research strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from (...) the investigation of organizational properties of biological networks using tools from graph theory to the application of dynamical systems theory to understand the behavior of complex biological systems. We show how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological complexity. (shrink)

As the English word “scientism” is currently used, it is a trivial verbal truth that scientism—an inappropriately deferential attitude to science—should be avoided. But it is a substantial question when, and why, deference to the sciences is inappropriate or exaggerated. This paper tries to answer that question by articulating “six signs of scientism”: the honorific use of “science” and its cognates; using scientific trappings purely decoratively; preoccupation with demarcation; preoccupation with “scientific method”; looking to the sciences for answers beyond their (...) scope; denying the legitimacy or worth of non-scientific (e.g., legal or literary) inquiry, or of writing poetry or making art. (shrink)

Simulation techniques, especially those implemented on a computer, are frequently employed in natural as well as in social sciences with considerable success. There is mounting evidence that the "model-building era" (J. Niehans) that dominated the theoretical activities of the sciences for a long time is about to be succeeded or at least lastingly supplemented by the "simulation era". But what exactly are models? What is a simulation and what is the difference and the relation between a model and a simulation? (...) These are some of the questions addressed in this article. I maintain that the most significant feature of a simulation is that it allows scientists to imitate one process by another process. "Process" here refers solely to a temporal sequence of states of a system. Given the observation that processes are dealt with by all sorts of scientists, it is apparent that simulations prove to be a powerful interdisciplinarily acknowledged tool. Accordingly, simulations are best suited to investigate the various research strategies in different sciences more carefully. To this end, I focus on the function of simulations in the research process. Finally, a somewhat detailed case-study from nuclear physics is presented which, in my view, illustrates elements of a typical simulation in physics. (shrink)

In the Aristotelian curriculum, De anima or the study of the soul fell under the rubric of physics. This area of study covered the vital (“vegetative”), sensitive, and rational powers of the soul. Descartes’ substance dualism restricted reason or intellect, and conscious sensation, to human minds. Having denied mind to nonhuman animals, Descartes was required to explain all animal behavior using material mechanisms possessing only the properties of size, shape, position, and motion. Within the framework of certainty provided by the (...) metaphysical foundations of his physics, he posited such mechanisms in accordance with appropriately lessened standards of certainty. As Cartesianism (or the Cartesian revolution) spread, adherents offered survey textbooks or treatises of physics to replace the corresponding Aristotelian curriculum. These books typically discussed the role of experience in physics and the appropriate standard of certainty. A comprehensive Cartesian natural philosophy needed to mechanize the offices of the Aristotelian sensitive soul, including sense perception, memory, and cognitive and appetitive responses to the environment. Descartes’ Treatise on Man (1664) offered an initial explanatory program. This chapter examines the role of experience in the natural philosophy and mechanistic psychology of Descartes’ English follower Antoine Le Grand. He offered detailed accounts of the sensory and motor mechanisms shared by human and nonhuman animals (for which he claimed “physical certainty”). These frame his Cartesian psychology. (shrink)

Review of: Husain Sarkar. A Theory of Method. xvii+ 229 pp., bibl., indexes. Berkeley/Los Angeles/London: University of California Press, 1983. $29.95. The subject of this book is best stated in the author's words: "A theory is about the world; a method is about theories; and, a theory of method is about methods" (p. 1). A theory of method seeks to offer a general framework within which to choose among methods. Through critical examination of the positions of Karl Popper, Imre Lakatos, (...) and Larry Laudan, Sarkar develops his own framework for evaluating methods, which includes two bold proposals: that the history of science cannot be used as an arbitrator among methods, and that methods should be chosen by testing the heuristic advice they give about which lines of scientific research to pursue further. (shrink)

Four different interpretations of measurement are distinguished that are compatible with the formal frame of the representational theory of measurement: (1) the classical interpretation, the additive, (3) the operationalis, (4) the correlative one.

On the received view, the Representational Theory of Measurement reduces measurement to the numerical representation of empirical relations. This account of measurement has been widely criticized. In this article, I provide a new interpretation of the Representational Theory of Measurement that sidesteps these debates. I propose to view the Representational Theory of Measurement as a library of theorems that investigate the numerical representability of qualitative relations. Such theorems are useful tools for concept formation that, in turn, is one crucial aspect (...) of measurement for a broad range of cases in linguistics, rational choice, metaphysics, and the social sciences. (shrink)