Hayley Clatterbuck

Hierarchical cognitive mechanisms underlie sophisticated behaviors, including language, music, mathematics, tool-use, and theory of mind. The origins of hierarchical logical reasoning have long been, and continue to be, an important puzzle for cognitive science. Prior approaches to hierarchical logical reasoning have often failed to distinguish between observable hierarchical behavior and unobservable hierarchical cognitive mechanisms. Furthermore, past research has been largely methodologically restricted to passive recognition tasks as compared to active generation tasks that are stronger tests of hierarchical rules. We argue that it is necessary to implement learning studies in humans, non-human species, and machines that are analyzed with formal models comparing the contribution of different cognitive mechanisms implicated in the generation of hierarchical behavior. These studies are critical to advance theories in the domains of recursion, rule-learning, symbolic reasoning, and the potentially uniquely human cognitive origins of hierarchical logical reasoning.

In the Origin, Darwin forwards two incompatible lines of attack on special creationism. First, he argues that imperfect or functionless traits are evidence against design. Second, he argues that since special creationism can be made compatible with any observation, it is unscientific and explanatorily vacuous. In later works, Darwin shifts to an argument that he finds much more persuasive and which would undermine theistic evolutionism as well. He argues that variation is random with respect to selection and that this demonstrates that there is no design in the biological world. I examine why Darwin found the argument from independence of variation and selection more compelling than the argument from imperfection. I argue that Darwin utilized general principles of causal inference, akin to those used in modern causal modeling, to rule out any unified cause behind the evolutionary process.

I evaluate the plausibility of explanatory elitism, the view that a good scientific explanation of an outcome will show that it was highly probable. I consider an argument from Michael Strevens that elitism is the only view that can account for the historical acceptance of probabilistic theories in physics. I argue that biology provides better test cases for evaluating elitism and conclude that theories in that domain were favored in virtue of conferring correct, and not necessarily high, probabilities on outcomes.

The probability that the fitter of two alleles will increase in frequency in a population goes up as the product of N (the effective population size) and s (the selection coefficient) increases. Discovering the distribution of values for this product across different alleles in different populations is a very important biological task. However, biologists often use the product Ns to define a different concept; they say that drift “dominates” selection or that drift is “stronger than” selection when Ns is much smaller than some threshold quantity (e.g., ½) and that the reverse is true when Ns is much larger than that threshold. We argue that the question of whether drift dominates selection for a single allele in a single population makes no sense. Selection and drift are causes of evolution, but there is no fact of the matter as to which cause is stronger in the evolution of any given allele

The theory-theory of human uniqueness posits that the capacity to theorize, in a way strongly analogous to theorizing in scientific practice, was a key innovation in the hominid lineage and was responsible for many of our unique cognitive traits. One of the central arguments that its proponents have used to support the claim that animals are not theorists, the logical problem, bears strong similarities to Hempel's theoretician's dilemma, which purports to show that theories are unnecessary. This similarity threatens to undermine both the claim that theorizing serves a unique, adaptive role in human cognition and our ability to test for the presence of theories. I examine two historical responses to the theoretician's dilemma and argue that they open up strategies for experimentally testing for theoretical ability in other animals.

Several major breakthroughs in the history of physics have been prompted not by new empirical data but by thought experiments. James Robert Brown and John Norton have developed accounts of how thought experiments can yield such advances. Brown argues that knowledge gained via thought experiments demands a Platonic explanation; thought experiments for Brown are a window into the Platonic realm of the laws of nature. Norton argues that thought experiments are just cleverly disguised inductive or deductive arguments, so no new account of their epistemology is needed. In this paper, I argue that although we do not need to invoke any Platonic insight to explain thought experimentation, Norton’s eliminativist account fails to capture the unique epistemological importance of thought experiments qua thought experiments. I then present my own account, according to which thought experiments are a particular type of inductive inference that is uniquely suited to generate new breakthroughs

I analyze two recent parsimony arguments that have been offered to break the current impasse in the chimpanzee mindreading controversy, the ‘logical problem’ argument from Povinelli, Penn, and Vonk, and Sober's attempt to apply model selection criteria in support of the mindreading hypothesis. I argue that Sober's approach fails to adequately rebut the ‘logical problem’. However, applying model selection criteria to chimpanzees' own mental models of behavior does yield a response to the ‘logical problem’ and reveals an adaptive advantage of mindreading models and a potential solution to a paradox raised by Whiten.

Several recent arguments by philosophers of biology have challenged the traditional view that evolutionary factors, such as drift and selection, are genuine causes of evolutionary outcomes. In the case of drift, advocates of the statistical theory argue that drift is merely the sampling error inherent in the other stochastic processes of evolution and thus denotes a mathematical, rather than causal, feature of populations. This debate has largely centered around one particular model of drift, the Wright–Fisher model, and this has contributed to the plausibility of the statisticalists’ arguments. However, an examination of alternative, predictively inequivalent models shows that drift is a genuine cause that can be manipulated to change population outcomes. This case study illustrates the influence of methodological assumptions on ontological judgments, particularly the pernicious effect of focusing on a particular model at the expense of others and confusing its assumptions and idealizations for true claims about the phenomena being modeled

Charles Darwin and C. Lloyd Morgan forward two influential principles of cognitive ethological inference that yield conflicting results about the extent of continuity in the cognitive traits of humans and other animals. While these principles have been interpreted as reflecting commitments to different senses of parsimony, in fact, both principles result from the same vera causa inferential strategy, according to which “We ought to admit no more causes of natural things, than such as are both true and sufficient to explain their appearances”. Instead, the conflict stems from Darwin’s and Morgan’s views about the true causes of human psychology. Darwin holds a thoroughly Humean philosophy of the human mind, from which he infers significant continuity between human and animal minds. In contrast, Morgan argues that Humean cognitive mechanisms cannot account for a class of uniquely human behaviors, and therefore, he concludes that there is a significant discontinuity between human and animal cognition. This historical debate is informative for current controversies in comparative psychology.