Over the past decade philosophers of biology have discussed whether evolutionary theory is a causal theory or a phenomenological study of evolution based solely on the statistical features of a population. This article reviews this controversy from three aspects, respectively concerning the assumptions, applications, and explanations of evolutionary theory, with a view to arriving at a definite conclusion in each contention. In so doing I also argue that an implicit methodological assumption shared by both sides of the debate, namely the (...) overconfidence in conceptual analysis as a tool to understand the scientific theory, is the real culprit that has both generated the problem and precluded its solution for such a long time. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows (...) adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows (...) adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

Ernst Mayr’s classical work on the nature of causation in biology has had a huge influence on biologists as well as philosophers. Although his distinction between proximate and ultimate causation recently came under criticism from those who emphasize the role of development in evolutionary processes, the formal relationship between these two notions remains elusive. Using causal graph theory, this paper offers a unified framework to systematically translate a given “proximate” causal structure into an “ultimate” evolutionary response, and illustrates evolutionary implications (...) of various kinds of causal mechanisms including epigenetic inheritance, maternal effects, and niche construction. These results not only reveal the essential interplay between proximate and ultimate causation in the study of evolution, but also provide a formal method to evaluate or discover non-standard or yet unknown evolutionary phenomena. (shrink)

We critically examine Denis Walsh’s latest attack on the causalist view of fitness. Relying on Judea Pearl’s Sure-Thing Principle and geneticist John Gillespie’s model for fitness, Walsh has argued that the causal interpretation of fitness results in a reductio. We show that his conclusion only follows from misuse of the models, that is, (1) the disregard of the real biological bearing of the population-size parameter in Gillespie’s model and (2) the confusion of the distinction between ordinary probability and Pearl’s causal (...) probability. Properly understood, the models used by Walsh do not threaten the causalist view of fitness. (shrink)

I propose a new account of homology, according to which homology is a correspondence of developmental mechanisms due to common ancestry, formally defined as an isomorphism of causal graphs over lineages. The semiformal definition highlights the role of homology as a higher-order principle unifying evolutionary models and also provides definite meanings to concepts like constraints, evolvability, and novelty. The novel interpretation of homology suggests a broad perspective that accommodates evolutionary developmental biology and traditional population genetics as distinct but complementary approaches (...) to understand evolution, prompting further empirical and theoretical research. (shrink)

We show how faceted search using a combination of traditional classification systems and mixed-membership topic models can go beyond keyword search to inform resource discovery, hypothesis formulation, and argument extraction for interdisciplinary research. Our test domain is the history and philosophy of scientific work on animal mind and cognition. The methods can be generalized to other research areas and ultimately support a system for semi-automatic identification of argument structures. We provide a case study for the application of the methods to (...) the problem of identifying and extracting arguments about anthropomorphism during a critical period in the development of comparative psychology. We show how a combination of classification systems and mixed-membership models trained over large digital libraries can inform resource discovery in this domain. Through a novel approach of “drill-down” topic modeling—simultaneously reducing both the size of the corpus and the unit of analysis—we are able to reduce a large collection of fulltext volumes to a much smaller set of pages within six focal volumes containing arguments of interest to historians and philosophers of comparative psychology. The volumes identified in this way did not appear among the first ten results of the keyword search in the HathiTrust digital library and the pages bear the kind of “close reading” needed to generate original interpretations that is the heart of scholarly work in the humanities. Zooming back out, we provide a way to place the books onto a map of science originally constructed from very different data and for different purposes. The multilevel approach advances understanding of the intellectual and societal contexts in which writings are interpreted. (shrink)

The central role of mathematical modeling in modern evolutionary theory has raised a concern as to why and how abstract formulae can say anything about empirical phenomena of evolution. This Element introduces existing philosophical approaches to this problem and proposes a new account according to which evolutionary models are based on causal, and not just mathematical, assumptions. The novel account features causal models both as the Humean 'uniform nature' underlying evolutionary induction and as the organizing framework that integrates mathematical and (...) empirical assumptions into a cohesive network of beliefs that functions together to achieve epistemic goals of evolutionary biology. (shrink)

This article characterizes various species concepts in terms of set-theoretic models that license biological inferences and illustrates the logical connections among different species concepts. Species in this construal are abstract models, rather than biological or even tangible entities, and relate to individual organisms via representation, rather than the membership or mereological whole/part relationship. The proposal sheds new light on vexed issues of species and situates them within broader philosophical contexts of model selection, scientific representation, and scientific realism.

Scientific conflicts often stem from differences in the conceptual framework through which scientists view and understand their own field. In this chapter, I analyze the ontological and methodological assumptions of three traditions in evolutionary biology, namely, Ernst Mayr’s population thinking, the gene-centered view of the Modern Syn thesis, and the Extended Evolutionary Synthesis. Each of these frameworks presupposes a different account of "evolutionary causes," and this discrepancy prevents mutual understanding and objective evaluation in the recent contention surrounding the EES. From (...) this perspective, the chapter characterizes the EES research program as an attempt to introduce causal structures beyond genes as additional units of evolution, and compares its research methodology and objectives with those of the traditional MS framework. (shrink)

This article explores the intersection of philosophy and statistics by examining the philosophical assumptions underlying modern mathematical statistics from ontological and epistemological perspectives. Statistics holds interest for philosophers engaged with the problem of induction, as its mathematical apparatus serves as models for philosophical ideas. For instance, the much-discussed concepts of the uniformity of nature and natural kinds correspond to probability models and statistical models, which are fundamental to various statistical methods. Similarly, Dennett’s concept of a real pattern echoes the spirit (...) of various information criteria (such as AIC) used to determine the optimal level of complexity for maximizing a model’s predictive ability. Furthermore, the recent developments in machine learning models, such as deep learning, imply that these machines possess their own 'ontology,' which is potentially more complex and efficient at understanding the world than ours. This leads to a Quinean problem of radical translation between human and machine ontologies. We suggest that this issue is key to the successful application of AI technologies in our society. The other focus of this article is epistemology, where Bayesian and classical statistics are compared to internalist and externalist epistemologies, respectively. This comparison elucidates how and in what sense the statistical methods adopted in each camp are considered to justify scientific hypotheses and also sheds light on their epistemic problems. We conclude with a plea for more research and interdisciplinary dialogues between statistics and the philosophy of various traditions. (shrink)