Philosophy of Science in the Courtroom: From Falsification to Methodological Naturalism

Haixin Dang

Karl Popper had gone as far as setting the demarcation problem—distinguishing science from non-science— as the key to solving most of the fundamental problems in the philosophy of science (Popper 1962: 42). Although many contemporary philosophers of science reject falsification as an appropriate demarcation criterion, it remains one of the most influential ideas in philosophy as well as a powerful tool in public debates about the nature of science. Most notably, falsification was adopted by Judge William Overton in a remarkable decision in 1982 which ruled that creation-science is not science and therefore cannot be taught in Arkansas public schools and cannot receive equal-time treatment as evolution. This project will trace the various demarcation criteria employed in three major American court cases: Scopes (1925), McLean (1981), Dover (2005). I will also be giving a brief history of the creationism movement in 20th century America and the philosophical development of the intelligent design. I will at the end offer some suggestions on how we can–or should–move on from methodological naturalism.

The Likelihood Principle (Prospectus Preview)

Greg Gandenberger

This talk will provide an overview of the ideas I plan to develop in my prospectus. The presentation will be informal and will feature at least one leaping cat. Feel free to share both feedback on the content and general advice on writing a prospectus, forming a committee, and so on.

Abstract

Debates between frequentists and Bayesians often revolve around prior probabilities, but the frequentist and Bayesian positions also differ in that Bayesian methods conform to the Likelihood Principle while frequentist methods do not. There are strong arguments for the Likelihood Principle that do not depend on the familiar coherence arguments for Bayesianism. These arguments are controversial and raise many deep issues that are ripe for philosophical scrutiny. They constitute a strong case for the Likelihood Principle, but they do not directly address key questions about the performance characteristics of likelihood-based methods. If it turns out that likelihood-based methods perform well even without appealing to priors, then frequentist methods are in serious trouble. If it turns out that likelihood-based methods perform poorly despite the strong first-principles arguments for the Likelihood Principle, then the choice between frequentist and Bayesian/likelihoodist methods involves a genuine tradeoff between evidentialist and reliabilist considerations. Widespread acceptance of the Likelihood Principle would have many important effects on science, including that it would allow ethically superior sequential clinical trials to be performed without elaborate and restrictive pre-trial planning.

Value, Dysmenorrhea and the Definition of Disease

Lauren Ross

Two main philosophical positions contrast the role of value in the definition of disease. The descriptivist position, championed most influentially by Christopher Boorse’s biostatistical theory (BST), claims that the definition of disease should be value-free, an “objective matter” that can be read, more or less, from the scientific facts of nature. The opposing normativist position asserts instead that this definition should involve value, although many different philosophers have widely different conceptions of how exactly it should.

I argue that the Boorsian theory fails to provide a definition of disease that accounts for dysmenorrhea, a disease of severe pelvic pain with menstruation. According to Boorse’s BST an organism is diseased if and only if it experiences subnormal function, with regard to its species, age-group and sex, which impinges upon the organism’s survival or reproductive fitness. The example dysmenorrhea not only fails to fit the BST’s analysis in that it lacks dysfunction and does not reduce survival or reproductive fitness but it also undermines the rationale for that analysis in that its treatment (hysterectomy) diminishes the patient’s survival and reproductive fitness, and does so far more than the disease itself.

Second, I argue for the normativist position in maintaining that the definition of disease must include at least some value because, as demonstrated by the example of dysmenorrhea, it encompasses the notion of suffering—a subjective experience of the patient. Suffering is value-laden because it depends on the patient’s judgment of her condition (its effects on daily life, severity, etc.) and personal preferences (longevity, quality of life, etc.).

My assessment of “value”, in the definition of disease, refers to a subjective assessment of worth made by an individual or collective, and as such, depends on their judgments or preferences. Values are often juxtaposed to objective or empirical scientific facts which, through detached scientific experimentation, provide descriptions of ourselves and our world. Of course whether there is a sharp fact-value distinction is controversial; my argument requires that only a rough distinction of this sort exists and I will not broach the controversies related to the topic.

Experiment as a Source and Test of Causal Content in Science

Karen Zwier

This presentation explores the history of the idea of experiment as a privileged method for gaining knowledge of causes.  Part of my aim is to argue against any temptation one might have to view manipulationist accounts of causation (a la Woodward) just as a current philosophical fad, as marginalizable, as just one out of several equally valid candidates for fleshing out the meaning of causal claims.  I will show that manipulationist accounts are part of a long tradition of thinking about causation as empirically testable and intimately tied to experiment.  I will also show that the tradition itself—i.e., that of thinking about causation as tied to experiment—was by no means a sideline in history; it is wrapped up in the fundamental ideas of the scientific revolution—the great reconceptualization of human inquiry into nature that resulted in what we call the “New Science”.

I begin by examining the thought of two of the main advocates for experiment during the early stages of the scientific revolution: Galileo and Bacon.  I explore their explicit statements about the connection between experiment and knowledge of causes, and I also examine examples of experiments that they carried out and discussed in their writings. My examination will show that the turn toward experiment during the scientific revolution was marked by a sharp change in what was validly considered to be a cause. The early thinkers of the scientific revolution worked on eliminating or removing emphasis on certain senses of causation prevalent in the academic Aristotelian philosophy of nature, while elevating different sense of cause that was directly linked with the very experimental methodology that they were advocating.

I jump forward in history to show that the narrowed experimental sense of cause that the early modern thinkers sought to characterize is strongly present in the work of John Stuart Mill two centuries later.  Finally, I touch on a few of the main points of the manipulationist account of causation advanced by several philosophers in recent decades, including its understanding of causal claims as referring to the results of actual or hypothetical experiments.

Ultimately, my examination of this historical thread of thought will reveal a great deal of constancy over the past four centuries, in addition to a great deal of progress and increasing sophistication of experimental methods to test causal relationships.

Explanation/Models in Chemistry

Julia Bursten

I want to describe how chemists reason when they are confronted with conflicting models of a given phenomenon. To meet this aim, I study the phenomenon of hypervalent compounds, that is, compounds whose central atom is bound to more than four ligands. Standard models used to predict molecular structure, such as VSEPR and Lewis structures, hold that four is the expected maximum number of ligands that can be affixed to a central atom. So hypervalent compounds are anomalous with respect to standard molecular-structure models, and if the models are to be preserved, this anomaly demands an explanation. Moreover, the fact that hypervalence cannot obtain in compounds whose central atom is in the first row of the periodic table suggests that there is a principled reason why hypervalence occurs in some compounds and not others. This reason should factor into a satisfactory explanation of the phenomenon.

Explanations of non-hypervalent, four-ligand molecules centered on atoms that can express hypervalence refer to the participation of s- and p-orbitals. Atoms have one s-orbital and three p-orbitals in their outer (valence) shells that are available to form bonding orbitals. Bonding orbitals accept electrons from ligand atoms to form bonds; hence, the expected maximum number of bonds around a central atom is four.
The received view among chemists has held that a central atom can express hypervalence just in case the outer electrons of the atom are of sufficiently high energy to involve d-orbitals as well as s- and p-orbitals. In such cases, the central atom can form up to seven bonding orbitals. This explanation of hypervalence involves direct reference to the systematic molecular-structure modeling tool of molecular orbitals, which is accepted as generally accurate for predicting molecular geometry and explaining relationships between geometric and energetic features of sets compounds. As such, it provides a strong basis for generalization and prediction, and it relates intimately to explanations of other bonding phenomena.

A competing view, which is rapidly gaining traction, holds instead that a central atom can express hypervalence just in case it is sufficiently large; that is, just in case there is enough room around the nucleus to fit in additional electrons. This explanation is simpler, and some research suggests it accords better with empirical data. It provides a rationale for why some atoms and not others can express hypervalence. And yet, it is somehow unsatisfying—it does not reveal new capabilities of the bonding model, nor does it confirm or disconfirm beliefs about the model. And it fails to provide as strong a basis for predicting molecular geometries of hypervalent compounds as the d-orbital explanation does.

So which explanation is better, for chemists? It turns out that neither explanation should be thrown out full-stop. The d-orbital explanation is more useful in predicting geometries and reinforcing the systematic relationships that underlie the bonding model, where the size explanation is more useful in predicting bond energies and accommodating empirical results. That both explanations survive is a testament to the diverse and context-sensitive explanatory needs of chemists, as well as to intricate and nonreductive relationships between theoretical models.

Is Psychology Mechanistic?

Catherine Stinson

This will literally be a work in progress talk where I present the current state of a (part of a) chapter of my dissertation. The wider context is a discussion of whether cognitive psychology and neurobiology can be integrated (unified, reduced one to the other, related by multi-level mechanistic explanation, …) and if so how. Whether cognitive psychology is a mechanistic science, and its particular way(s) of either being so or failing to be so has implications for its compatibility with neurobiology in an integrative project like cognitive neuroscience.

I’ll focus on cognitive psychology, and in particular, information-processing models. I’ll try to characterize information processing, relating it to functional analysis, computation, flow-charts, and maybe some other related notions, then compare examples of information-processing models to prototypical mechanistic models. Some nitpicking about what the definition of a mechanism should be will be necessary here; in particular I’ll try to clarify what a mechanism schema is.

If there’s time I’ll discuss a couple of recent/forthcoming papers by Piccinini and Craver, and Weiskopf that argue back and forth about whether psychological explanations are mechanistic, whether non-mechanistic or non-componential explanations can still be good explanations (yes, they can), and whether Craver-style unification can swallow up cognitive psychology (probably not).

Frequentism and Birnbaum’s Theorem

Greg Gandenberger

Frequentists appear to be committed to the sufficiency principle (S) and the conditionality principle (C). However, Birnbaum (1962) proved that (S) and (C) entail the likelihood principle (L), which frequentist methods violate.  To respond adequately to Birnbaum’s theorem, frequentists must place restrictions on (S) and/or (C) that block Birnbaum’s proof and argue that those restrictions are well motivated.  Restricting (C) alone will not suffice, because (S) by itself implies too much of the content of (L) to be compatible with frequentist methods. Specifically, frequentists need to restrict (S) so that it does not apply to mixture experiments some of whose components have respective outcomes with the same likelihood function.  Berger and Wolpert (1988, p. 46) claim that such a restriction would be artificial, but in fact it has a strong frequentist motivation: reduction to the minimal sufficient statistic in such an experiment throws away information about what sampling distribution is appropriate for frequentist inference.  On the other hand, frequentists face difficult challenges in trying to state the restriction they need in a precise and general way.

T-invariance and T-violation

Bryan Roberts

The old question of intrinsic properties seems to be intimately connected to the symmetries of time in quantum theory. In particular, there is a precise sense in which, in the absence of internal degrees of freedom, Galilei-invariant quantum mechanics is guaranteed to be time reversal invariant. After illustrating this result, I show how it sheds light on some of the puzzling examples of time reversal violation.

Neuroscience and the Vehicles of Thought

Joe McCaffrey

Cognitive scientists traditionally assume that concepts, the so-called “vehicles of thought” that serve as the currency of higher cognition, are amodal representations. Concepts in mainstream cognitive science are thought of as representations that are independent of any particular perceptual capacity or set of perceptual capacities. However, a number of psychologists and philosophers, such as Jesse Prinz and Lawrence Baralou, have recently argued that conceptual knowledge is composed of perceptual representations. Thinking, on this “neo-empiricist” view, involves reenacting and manipulating past sensory, motor, and other introspective states (e.g. affect). Neo-empiricism is becoming increasingly popular among philosophers and cognitive scientists, especially among proponents of embodied cognition.

In my presentation, I will argue that current evidence from neuroscience undermines the claim that percepts are the vehicles of thought. My talk has three main goals: 1) To spell out more precisely what neo-empiricists claim about conceptual knowledge and what role neuroscience might play in adjudicating between amodal and neo-empiricist theories of concepts. 2) To outline the major empirical commitments of neo-empiricism concerning neuroscientific data. 3) To examine current evidence from fMRI and neuropsychology (via a case study of semantic dementia) to evaluate the neo-empiricist position. I argue that evidence from fMRI fails to confirm the empirical commitments of neo-empiricism while, moreover, findings from neuropsychology undermine them.

Breakdowns in the Vending Machine

Bihui Li

The “vending machine” view of theories holds that the theoretical content of non-fundamental theories is derivative of the fundamental theory and that non-fundamental theories are used only to make applications of the fundamental theory to empirical phenomena easier. I argue that non-fundamental theories are important even in theoretical realms outside the context of immediate application. Much of their importance lies in the informativeness of the specific ways in which they break down. I use examples from early quantum electrodynamics to illustrate how physicists resolved the theoretical problems they faced using non-fundamental theories. The strategies of these physicists are mysterious under the vending machine picture but coherent in a piecemeal engineering approach towards theorising, and methodological considerations suggest that these strategies apply more generally.