The term “cognitive ethology” was introduced by Donald R. Griffin in his book The Question of Animal Awareness (1976). He regarded “cognitive ethology” as a study of the mental life of animals particularly as they solve everyday problems in their natural world.

A cognitive ethologist focusses on problems faced in an animal's natural world. We should be open to the possibility that the animals are solving more complex problems than have typically been set them in the lab. Thus ethological data may reveal more advanced animal cognitive capacities. On the other hand, laboratory study can lead one to search in the wild for cognitive capacities not previously apparent; the various ape and other animal “language” experiments are a case in point (Ristau and Robbins 1982 and Ristau in press). Furthermore, raising the possibility that animals have complex mental processes and are conscious may change the way we explore their behavior.

My topics are two theses about quantum mechanics that are widely doubted but curiously tempting: value-definiteness and contextualism. Value-definiteness holds that every observable has a definite value; contextualism follows from value-definiteness, and claims that one Hermitian operator can represent many observables. In fact, contextualism is my deeper interest Although it is not a view with an army of defenders, it has a long history of discussion in the literature. (See, for example, Belinfante 1973, van Fraassen 1973, Shimony 1984, Redhead 1987). The bulk of this paper will be concerned with a puzzle about degenerate operators that arises out of the standard accounts of contextualism. But before we get to the details, let us begin with a lurid example.

There is one sense in which Bayes’ theorem, and its use in statistics and in scientific inference, is clearly uncontroversial. It is an authentic, certified, theorem of the probability calculus, and even the founders of classical statistical inference, Fisher, Neyman and Pearson, were explicit about seeing no difficulty in the use of Bayes’ theorem when the conditions for its application were satisfied. For example, Fisher writes, “When there really is exact knowledge a priori Bayes’ method is available” (1971, p. 194).

In a recent article Itamar Pitowsky (1991) has analyzed some measurement possibilities presented by an entangled state of three spin ½ particles. From that analysis he has concluded that the valid predictions of results of possible future measurements, made by observers who actually carry out mutually space-like separated measurements, can be incompatible with one another in the sense that their conjunction contradicts the quantum theory. From this result Pitowsky infers the inherently observer specific, or relative, character of quantum predictions as opposed to the results of actual observations or measurements, which, he claims, are covariant; i.e. (I take it) compatibly translatable from one observer to another.

The Einstein-Podolsky-Rosen argument for the incompleteness of quantum mechanics involves two assumptions: one about locality and the other about when it is legitimate to infer the existence of an element-of-reality. Using one simple thought experiment, we argue that quantum predictions and the relativity of simultaneity require that both these assumptions fail, whether or not quantum mechanics is complete.

EPR’s (1935) argument for the incompleteness of QM turns upon the following sufficient condition:

“If, without in any way disturbing a system, we can predict with certainty (i.e., with probability equal to unity) the value of a physical quantity, then there exists an element of physical reality corresponding to this physical quantity.“

EPR apply this condition in a case where knowledge gained from measuring one quantum system allows one to predict with certainty a value for a physical quantity on another.

Classical Bayesian methodology is based on the following three principles:

1. (i) individuals have degrees of belief which, measured in the closed unit interval, and subject to a mild consistency constraint, are fonnally probabilities.

2. (ii) belief functions are updated with the acquisition of new evidence by Bayesian conditionalisation. In other words, if B is learned to be true, then your new probability function P′ takes the value P′(A) = P(A/B) on every A in domain P′, where P is your probability function prior to learning B.

3. (iii) where Hi is a statistical hypothesis and E sample data, the tenns P(E|Hi) in Bayes’ Theorem calculations are set equal to the probability assigned E by Hi.

In Theory and Evidence, Clark Glymour asserts that many philosophers are convinced that “evidence can only bear on the entire body of our beliefs, and cannot be parceled out here and there“(1980,p.5). Attributing this view to Quine, Glymour says:

Some philosophers might counter that Glymour’s criticisms apply properly to a view Quine had significantly modified two decades before the publication of Theory and Evidence.

It is commonly acknowledged in science that model construction is one of the most important components of theorizing. Philosophers of science are gradually coming to acknowledge this situation, spurred on by holders of the semantic view of theories. In this paper I wish to defend a very deflationary version of the semantic view of theories, which is more or less a re-statement of the above commonplace. I reject the view encapsulated in the identity statement “scientific theories are families of models,” although acknowledging the useful insights into science that holders of this strong position have given us. My position derives from a critique of various of the semantic views of theories, and further from a guiding presupposition that rather than providing necessary and sufficient conditions for what a theory is, philosophers should focus on the nature of scientific theorizing. Theorizing is carried out by practicing scientists, and we cannot say what scientific theories are unless we appreciate the myriad ways they are used and developed in all of the sciences.

In 1978 Roger Penrose opined that cosrnic censorship was “possibly the most important unsolved problem in classical general relativity theory” (1978, p. 230). Today the problem remains unsolved, but in the intervening years Penrose's sentiment about the importance of the problem has been shared by many leading researchers in relativistic gravitation (see, for example, Eardley 1987, Israel 1984, and Wald 1984a). This sentiment can be traced to several considerations. First, if a suitable form of cosrnic censorship obtains, then one can appeal to various “no hair” theorems for black holes to obtain a characterization of the final state of gravitationally collapsed bodies. The now Standard black hole thermodynarnics makes use of Hawking's area theorems, which in turn presuppose a form of cosmic censorship.

It is known from the singularity theorems of general relativity (see Hawking and Ellis, 1973) that, under a variety of circumstances, solutions to Einstein's equation with physically reasonable matter must develop singularities. In particular, for a sufficiently compacted body, trapped surfaces must be present (Schoen and Yau, 1983), and collapse to a singularity must occur. Of crucial importance for the theory of gravitational collapse is the issue of the nature of the final state resulting from such a coUapse. The idea that physically realistic gravitational collapse always results in a black hole-so that no “naked singularities”, visible to a distant observer, can occur-was first conjectured by Penrose (1969), although it had been implicitly assumed in many discussions and analyses prior to that time.

Since “one can seldom directly deduce from a speculation consequences that are even in principle testable,” a scientist must “articulate” a theory, mathematically altering a given speculation to bring it “into greater resonance with the world” (Hacking 1983, p. 214). When confronted with computational difficulties caused by analytically intractable equations, imprecise specifications of initial conditions, or the absence of required auxiliary theories, scientists commonly articulate a theory by applying approximations and idealizations to the theoretical equations they have at hand. Recognizing this, the following question immediately arises for both the scientist and the philosopher of science, “How does one judge the quality of a particular approximation? I.e., when is a given approximation valid?“

In 1802 a youthful Thomas Young, British physician and scientist, had the audacity to resuscitate the wave theory of light (Young 1802). For this he was excoriated by Henry Brougham (1803) in the Edinburgh Review. Brougham, a defender of the Newtonian particle theory, asserted that Young's paper was “destitute of every species of merit” because it was not based on inductions from observations but involved simply the formulation of hypotheses to explain various optical phenomena.

For Hacking, the word “real” is one of J.L. Austin's trouser-words, taking its meaning from its negative uses in much the same way as the admittedly sexist expression “wear the trousers”. In Representing and Intervening, Hacking proposes that at least some scientific realists can be interpreted as using the word “real” in this way. The word “real” is also substantive-hungry, he adds. Thus when a philosopher states that a type of entity is not real we need to know just what is being denied. The causal entity realist, for example, holds that the entities scientists postulate in their theories can be regarded as real if they have causal powers that can be manipulated to create observable and repeatable effects. Thus the causalist offers sociology a possible way to command respect: if social science entities could be manipulated, the social sciences would then be on a par with physics.

An odd sense of dissonance comes over me as I listen to the eloquent and eminently reasonable arguments presented by Professors Achinstein and Laudan. Nothing similar to either of their remarks would likely be heard today at a history of science meeting, much less at a convention, say, of the Modem Languages Association. Historians would be much more likely to ask what interests were served by the particular rhetorical characters of Whewell's or Brougham's or Mill's or even Young's or Fresnel's arguments. They would be deeply skeptical that arguments per se had anything much to do with the contagious expansion of wave methods during and after the 1830s. In their respective ways, and despite the obvious differences between them, Professors Achinstein and Laudan both feel that argumentation was a central aspect of the historical events involved in the establishrnent of wave optics.

On the surface and to a first approximation, economic theory and evolutionary theory share salient features: a commitment to optimality and maximizing, a consequent similarity in mathematical formalism, an appeal to equilibrium as the preferred explanatory strategy. Moreover, both have at various times been stigmatized as empirically empty. However, the theory of natural selection has been widely accepted as the scientific cornerstone of modern biology, while microeconomics has remained open to repeated challenges as an explanation of human action and its aggregate consequences.

Because of their similarity, evolutionary theory looks like part of a powerful defense of the status quo in economic theory. I think that Darwinian theory is a remarkably inappropriate model, metaphor, inspiration, or theoretical framework for economic theory.

In this paper, I shall be taking exception to a few of the ideas in Peter Achinstein's recent (1991). In some of these cases, I think he is flat wrong. But that does not diminish in the least my admiration for his book which is, in my judgment, the best extended piece of work we have on the epistemological problems posed by 19th-century physics.

In the Preface to his recent philosophy of biology (1988) and in his earlier Growth of Biological Thought (1982), Ernst Mayr emphasized that recent progress in evolutionary biology is a result of conceptual clarification, not a consequence of improved measurements or better scientific laws. Although complete agreement on the meaning of key concepts is not essential for all communication in science (see Hull 1988, pp. 6-7,513), we likewise believe that conceptual clarification is perhaps the most important key to progress in community ecology. In order to investigate some of the reasons that might explain why community ecology has been unable to arrive at a widely accepted general theory, in this essay we analyze “stability,” one of its most important foundational concepts. After reviewing the stability concept and sketching its associated problems, we assess the epistemological status of four difficulties with the concept.

I relate this homily to several puzzles. In one, three cards, of which I know one is a king, lie face-down. After I select, without inspecting, a card and bet that it is a king, you reveal that a certain other card is not a king. I wonder what this does to my chances on that bet. In another puzzle I am one of three prisoners and learn that one of us will be released. Then I learn that a certain other prisoner will not be released. Again I wonder what this does to my chances.

The common cause principle, roughly speaking, consists of the following 2 subprinciples:

1. i) If 2 events (or types of events, or facts, or conditions, or …..) are correlated, and the one does not cause the other, then there is a third event (type of event, …..) such that the 2 events are probabilistically independent given the presence or absence of the third event. That is to say: for every pair of correlated events that do not have direct causal links there is a screener off of that correlation.

2. ii) This screener off occurs before the correlated events.