This chapter contains sections titled: Introduction A Brief History of Developmental Explanations of Phenotypic Evolution Research Questions of Evo‐Devo Unifying Themes of the Conceptual Basis of Evo‐Devo Conclusion: A Mechanistic Theory of Evo‐Devo Challenges the Modern Synthesis Postscript: Counterpoint References.
This paper argues in defense of theanti-reductionist consensus in the philosophy ofbiology. More specifically, it takes issues with AlexRosenberg's recent challenge of this position. Weargue that the results of modern developmentalgenetics rather than eliminating the need forfunctional kinds in explanations of developmentactually reinforce their importance.
COVID-19 has revealed that science needs to learn how to better deal with the irreducible uncertainty that comes with global systemic risks as well as with the social responsibility of science towards the public good. Further developing the epistemological principles of new theories and experimental practices, alternative investigative pathways and communication, and diverse voices can be an important contribution of history and philosophy of science and of science studies to ongoing transformations of the scientific enterprise.
Journal of the History of Biology provides a fifty-year long record for examining the evolution of the history of biology as a scholarly discipline. In this paper, we present a new dataset and preliminary quantitative analysis of the thematic content of JHB from the perspectives of geography, organisms, and thematic fields. The geographic diversity of authors whose work appears in JHB has increased steadily since 1968, but the geographic coverage of the content of JHB articles remains strongly lopsided toward the (...) United States, United Kingdom, and western Europe and has diversified much less dramatically over time. The taxonomic diversity of organisms discussed in JHB increased steadily between 1968 and the late 1990s but declined in later years, mirroring broader patterns of diversification previously reported in the biomedical research literature. Finally, we used a combination of topic modeling and nonlinear dimensionality reduction techniques to develop a model of multi-article fields within JHB. We found evidence for directional changes in the representation of fields on multiple scales. The diversity of JHB with regard to the representation of thematic fields has increased overall, with most of that diversification occurring in recent years. Drawing on the dataset generated in the course of this analysis, as well as web services in the emerging digital history and philosophy of science ecosystem, we have developed an interactive web platform for exploring the content of JHB, and we provide a brief overview of the platform in this article. As a whole, the data and analyses presented here provide a starting-place for further critical reflection on the evolution of the history of biology over the past half-century. (shrink)
Computational methods and perspectives can transform the history of science by enabling the pursuit of novel types of questions, dramatically expanding the scale of analysis , and offering novel forms of publication that greatly enhance access and transparency. This essay presents a brief summary of a computational research system for the history of science, discussing its implications for research, education, and publication practices and its connections to the open-access movement and similar transformations in the natural and social sciences that emphasize (...) big data. It also argues that computational approaches help to reconnect the history of science to individual scientific disciplines. (shrink)
This paper emphasizes the crucial role of variation, at several different levels, for a detailed historical understanding of the development of the biomedical sciences. Going beyond valuable recent studies that focus on model organisms, experimental systems and instruments, we argue that all of these categories can be accommodated within our approach, which pays special attention to organismal and cultural variation. Our empirical examples are drawn in particular from recent historical studies of nineteenth- and early twentieth-century genetics and physiology. Based on (...) the quasi-paradoxical conclusion that biological and cultural variation both constrains and enables innovation in the biomedical sciences, we argue that more attention should be paid to variation as an analytical category in the historiography of the life sciences. (shrink)
In this paper we argue that an operational organism concept can help to overcome the structural deficiency of mathematical models in biology. In our opinion, the structural deficiency of mathematical models lies mainly in our inability to identify functionally relevant biological characters in biological systems, and not so much in a lack of adequate mathematical representations of biological processes. We argue that the problem of character identification in biological systems is linked to the question of a properly formulated organism concept. (...) Lastly, we demonstrate how a decomposition of an organism into independent characters in the context of a specific biological process--such as adaptation by means of natural selection--depends on the dynamical properties and invariance conditions of the equations that describe this process. (shrink)
The complexities of modern science are not adequately reflected in many bioethical discussions. This is especially problematic in highly contested cases where there is significant pressure to generate clinical applications fast, as in stem cell research. In those cases a more integrated approach to bioethics, which we call systems bioethics, can provide a useful framework to address ethical and policy issues. Much as systems biology brings together different experimental and methodological approaches in an integrative way, systems bioethics integrates aspects of (...) the history and philosophy of science, social and political theory, and normative analysis with the science in question. In this paper we outline how a careful analysis of the science of stem cell research can help to refocus the discussions related to the clinical applications of stem cells. We show how inaccurate or inadequate scientific assumptions help to create a set of unrealistic expectations and badly inform ethical deliberations and policy development. Systems bioethics offers resources for moving beyond the current impasse. (shrink)
This book represents an effort to understand very old questions about biological form, function, and the relationships between them. The essays collected here reflect the diversity of approaches in evolutionary developmental biology, including not only studies by prominent scientists whose research focuses on topics concerned with evolution and development, but also historically and conceptually oriented studies that place the scientific work within a larger framework and ask how it can be pushed further. Topics under discussion range from the use of (...) theoretical and empirical biomechanics to understand the evolution of plant form, to detailed studies of the evolution of development and the role of developmental constraints on phenotypic variation. The result is a rich and interdisciplinary volume that will begin a wider conversation about the shape of Evo Devo as it matures as a field. (shrink)
Contrary to concerns of some critics, we present evidence that biomedical research is not dominated by a small handful of model organisms. An exhaustive analysis of research literature suggests that the diversity of experimental organisms in biomedical research has increased substantially since 1975. There has been a longstanding worry that organism‐centric funding policies can lead to biases in experimental organism choice, and thus negatively impact the direction of research and the interpretation of results. Critics have argued that a focus on (...) model organisms has unduly constrained the diversity of experimental organisms. The availability of large electronic databases of scientific literature, combined with interest in quantitative methods among philosophers of science, presents new opportunities for data‐driven investigations into organism choice in biomedical research. The diversity of organisms used in NIH‐funded research may be considerably lower than in the broader biomedical sciences, and may be subject to greater constraints on organism choice. (shrink)
In this paper we argue that an operational organism concept can help to overcome the structural deficiency of mathematical models in biology. In our opinion, the structural deficiency of mathematical models lies mainly in our inability to identify functionally relevant biological characters in biological systems, and not so much in a lack of adequate mathematical representations of biological processes. We argue that the problem of character identification in biological systems is linked to the question of a properly formulated organism concept. (...) Lastly, we demonstrate how a decomposition of an organism into independent characters in the context of a specific biological process—such as adaptation by means of natural selection—depends on the dynamical properties and invariance conditions of the equations that describe this process. (shrink)
This essay describes the approach and early results of the collaborative Embryo Project and its on-line encyclopedia. The project is based on a relational database that allows federated searches and inclusion of multiple types of objects targeted for multiple user groups. The emphasis is on the history and varied contexts of developmental biology, focusing on people, places, institutions, techniques, literature, images, and other aspects of study of embryos. This essay introduces the ways of working as well as the long-term goals (...) of the project. We invite others to join the effort, both in this particular project and in joining together in digital collection, archiving, and knowledge generation at the borders of biology and history. (shrink)
Here we argue that the concept of strategies, as it was introduced into biology by John Maynard Smith, is a prime illustration of the four dimensions of theoretical biology in the post-genomic era. These four dimensions are: data analysis and management, mathematical and computational model building and simulation, concept formation and analysis, and theory integration. We argue that all four dimensions of theoretical biology are crucial to future interactions between theoretical and empirical biologists as well as with philosophers of biology.
Ioannidis [Why most published research findings are false. PLoS Med 2: e124 ] identifies six factors that contribute to explaining why most of the current published research findings are more likely to be false than true, and argues that for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this article, we argue that three “hot” areas in current biological research, viz., agent-based modeling, evolutionary developmental biology , and systems biology, are (...) especially prone to the flaws. (shrink)
Ioannidis [Why most published research findings are false. PLoS Med 2: e124 ] identifies six factors that contribute to explaining why most of the current published research findings are more likely to be false than true, and argues that for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this article, we argue that three “hot” areas in current biological research, viz., agent-based modeling, evolutionary developmental biology, and systems biology, are especially (...) prone to the flaws. (shrink)
Digital technologies have transformed both the historical record and the historical profession. This Focus section examines how computational methods have influenced, and will influence, the history of science. The essays discuss the new types of questions and narratives that computational methods enable and the need for better data management in the history and philosophy of science (HPS) community. They showcase various methodological approaches, including textual and network analyses, and they place the computational turn in historiographical and societal context. Rather than (...) surrendering to either technophilia or technophobia, the essays articulate both the benefits and the drawbacks of computational HPS. They agree that the future of the field depends on the successful integration of technological developments, social practices, and infrastructural support and that historians of science must learn to embrace collaboration both within and beyond disciplinary boundaries. (shrink)