International Society for History, Philosophy, and Social Studies of Biology


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Program

MONDAY, JULY 6  /  11:00 - 12:30  /  DS-M460
Individual papers
Causation, Explanation and Information in Biology

Limiting cases for the new mechanists: Intralevel causation is insufficient for modeling complex biological systems

Sarah Roe (Southern Connecticut State University, United States); Bert Baumgaertner (University of Idaho, United States)

Mechanistic accounts of explanation pervade the philosophy of science. Typically, however, such accounts struggle to explain complex biological systems. Craver and Bechtel offer one suggestion along these lines: levels of mechanisms are related by constitution, and causation only occurs intralevel (there is no interlevel causation; ‘bottom-up’ or ‘top-down’). We argue that this suggestion leads to a difficulty when we take seriously the modeling practices involved in studying contemporary complex biological systems. Such explanations often involve multilevel, nonlinear dynamic mechanisms, in which the mechanistic environment frequently plays an important organizational role. Our suggestion is that the New Mechanists should go the route of allowing for interlevel causation, because it better reflects modeling practices, and broadens the scope for mechanistic explanations.


Causal explanation in genetics and the pathway concept

Lauren Ross (University of Pittsburgh, United States)

In this paper I examine the concept of a causal pathway and how it is used to provide explanations in both classical Mendelian genetics and modern biochemical genetics. I indicate how the pathway concept is used to explain phenotypes that are causally complex in the sense that: (1) the phenotype is caused by multiple causal factors that work in aggregate in individual systems and (2) the phenotype is caused by heterogeneous causal factors in different systems with the same phenotype. In both cases, the numerous causal factors can be integrated on the basis of their causal influence on a shared or common pathway, which leads to the specific phenotype of interest. Shared pathways are appealed to in explaining these phenotypes, in part, because they represent sets of causal factors that make a difference to the phenotype of interest. As these common pathways often represent causal factors more upstream from gene variants, these cases clarify the rationale behind abstracting from genetic factors in explaining some phenotypes. Extant accounts of explanation in biology often assume that all complex causal factors can be characterized in terms of mechanisms. In this paper I will give reasons for doubting this assumption. To do so, I discuss the relation of pathway explanations in genetics to Batterman's work on minimal model explanations and multiple-realizability (Batterman 2001, 2002). I argue that when the concept of a causal pathway is invoked in these explanations, it differs in important ways from the philosophical concept of a mechanism. The central aim of this paper is to begin clarifying the differences among these complex causal concepts and why they find their respective application in particular contexts.


On the impossibility of measuring biological information

Agustín Mercado-Reyes (Universidad Nacional Autónoma de México, Mexico)

Since the inception of Shannon's theory of information, there have been several attempts to elaborate a method for measuring semantic information. This is a concern especially relevant in present day biological sciences, not only because of the enormous amount of data that has been produced in the past decades, but also because of the increasing interest to integrate the raw data into a broader picture of the processes of life. However, in order to measure biological information one must make the necessary presupposition that its semantic dimension is quantifiable. I analyse this presupposition and find that it is based on a series of idealizations which are detrimental to our understanding of living systems. On the one hand, semantic meaning is assumed to emerge out of a previously defined and fixed structure, on which there is a finite number of possible outcomes. Meaning is thus reduced to a correspondence between data and states of affairs. On the other hand, semantic processes are deprived of their temporal dimension, as they are analysed based solely on the formal structure. I argue that the reductionist programmes do not fully account for the complexity of biological systems, a fact which is especially evident when confronted with concepts like information and meaning. I suggest that a more appropriate theoretic framework must take into account different temporal descriptions, which would allow us to include phenomena such as the historical establishment of meaning and the repetitiveness of the outcome of informational processes. In this view, mechanicism need not be discarded, but rather included in a larger theory which more closely resembles biological reality.