This article compares causal and constitutive explanation. While scientific inquiry usually addresses both causal and constitutive questions, making the distinction is crucial for a detailed understanding of scientific questions and their interrelations. These explanations have different kinds of explananda and they track different sorts of dependencies. Constitutive explanations do not address events or behaviors, but causal capacities. While there are some interesting relations between building and causal manipulation, causation and constitution are not to be confused. Constitution is a synchronous and (...) asymmetric relation between relata that cannot be conceived as independent existences. However, despite their metaphysical differences, the same key ideas about explanation largely apply to both. Causal and constitutive explanations face similar challenges (such as the problems of relevance and explanatory regress) and both are in the business of mapping networks of counterfactual dependence—i.e. mechanisms—although the relevant counterfactuals are of a different sort. In the final section the issue of developmental explanation is discussed. It is argued that developmental explanations deserve their own place in taxonomy of explanations, although ultimately developmental dependencies can be analyzed as combinations of causal and constitutive dependencies. Hence, causal and constitutive explanation are distinct, but not always completely separate forms of explanation. (shrink)

This article examines to what extent a particular case of cross-disciplinary research in the 1930s was structured by mechanistic reasoning. For this purpose, it identifies the interfield theories that allowed biologists and chemists to use each other’s techniques and findings, and that provided the basis for the experiments performed to identify plant growth hormones and to learn more about their role in the mechanism of plant growth. In 1930, chemists and biologists in Utrecht and Pasadena began to cooperatively study plant (...) growth. I will argue that these researchers decided to join forces because they believed to rely on each other’s findings and methods to solve their research problems adequately. In the course of the cooperation, organic chemists arrived at isolating plant growth hormones by using a test method developed in plant physiology. This achievement, in turn, facilitated biologists’ investigation of the mechanism of plant growth. Researchers eventually believed to have the means to study the relation between a substance’s molecular structure and its physiological activity. The way they conceptualized the problem of identifying hormones and unraveling the mechanism of plant growth, as well as their actual research actions are compatible with the new mechanists’ account of mechanism research. The study illustrates that focusing on researchers’ mechanistic reasoning can contribute considerably to explaining the structure of cross-disciplinary research projects. (shrink)

There have been repeated attempts in the history of comparative biology to provide a mechanistic account of morphological homology. However, it is well-established that homologues can develop from diverse sets of developmental causes, appearing not to share any core causal architecture that underwrites character identity. We address this challenge with a new conceptual model of Character Identity Mechanisms. ChIMs are cohesive mechanisms with a recognizable causal profile that allows them to be traced through evolution as homologues despite having a diverse (...) etiological organization. Our model hypothesizes that anatomical units at different levels of organization—cell types, tissues, and organs—have level-specific ChIMs with different conserved parts, activities, and organization. Relying on a methodology of conceptual engineering, we show how the ChIM concept advances our understanding of the developmental basis of morphological characters, while forging an important link between comparative and mechanistic biology. (shrink)

Despite the importance of network analysis in biological practice, dominant models of scientific explanation do not account satisfactorily for how this family of explanations gain their explanatory power in every specific application. This insufficiency is particularly salient in the study of the ecology of the microbiome. Drawing on Coyte et al. (2015) study of the ecology of the microbiome, Deulofeu et al. (2021) argue that these explanations are neither mechanistic, nor purely mathematical, yet they are substantially empirical. Building on their (...) criticisms, in the present work we make a step further elucidating this kind of explanations with a general analytical framework according to which scientific explanations are ampliative, specialized embeddings (ASE), which has recently been successfully applied to other biological subfields. We use ASE to reconstruct in detail the Coyte et al.’s case study and on its basis, we claim that network explanations of the ecology of the microbiome, and other similar explanations in ecology, gain their epistemological force in virtue of their capacity to embed biological phenomena in non-accidental generalizations that are simultaneously ampliative and specialized. (shrink)

In the last few decades, philosophy of science has increasingly focused on multilevel models and causal mechanistic explanations to account for complex biological phenomena. On the one hand, biological and biomedical works make extensive use of mechanistic concepts; on the other hand, philosophers have analyzed an increasing range of examples taken from different domains in the life sciences to test—support or criticize—the adequacy of mechanistic accounts. The article highlights some challenges in the elaboration of mechanistic explanations with a focus on (...) cancer research and neuropsychiatry. It jointly considers fields, which are usually dealt with separately, and keeps a close eye on scientific practice. The article has a twofold aim. First, it shows that identification of the explananda is a key issue when looking at dynamic processes and their implications in medical research and clinical practice. Second, it discusses the relevance of organizational accounts of mechanisms, and questions whether thorough self-sustaining mechanistic explanations can actually be provided when addressing cancer and psychiatric diseases. While acknowledging the merits of the wide ongoing debate on mechanistic models, the article challenges the mechanistic approach to explanation by discussing, in particular, explanatory and conceptual terms in the light of stances from medical cases. (shrink)

Though the realm of biology has long been under the philosophical rule of the mechanistic magisterium, recent years have seen a surprisingly steady rise in the usurping prowess of process ontology. According to its proponents, theoretical advances in the contemporary science of evo-devo have afforded that ontology a particularly powerful claim to the throne: in that increasingly empirically confirmed discipline, emergently autonomous, higher-order entities are the reigning explanantia. If we are to accept the election of evo-devo as our best conceptualisation (...) of the biological realm with metaphysical rigour, must we depose our mechanistic ontology for failing to properly “carve at the joints” of organisms? In this paper, I challenge the legitimacy of that claim: not only can the theoretical benefits offered by a process ontology be had without it, they cannot be sufficiently grounded without the metaphysical underpinning of the very mechanisms which processes purport to replace. The biological realm, I argue, remains one best understood as under the governance of mechanistic principles. (shrink)