Inheritance and variation were a major focus of Charles Darwin’s studies. Small inherited variations were at the core of his theory of organic evolution by means of natural selection. He put forward a developmental theory of heredity (pangenesis) based on the assumption of the existence of material hereditary particles. However, unlike his proposition of natural selection as a new mechanism for evolutionary change, Darwin’s highly speculative and contradictory hypotheses on heredity were unfruitful for further research. They attempted to explain many (...) complex biological phenomena at the same time, disregarded the then modern developments in cell theory, and were, moreover, faithful to the widespread conceptions of blending and so-called Lamarckian inheritance. In contrast, Mendel’s approaches, despite the fact that features of his ideas were later not found to be tenable, proved successful as the basis for the development of modern genetics. Mendel took the study of the transmission of traits and its causes (genetics) out of natural history; by reducing complexity to simple particulate models, he transformed it into a scientific field of research. His scientific approach and concept of discrete elements (which later gave rise to the notion of discrete genes) also contributed crucially to the explanation of the existence of stable variations as the basis for natural selection. (shrink)

In the last few years, the lack of a unitary notion of gene across biological sciences has troubled the philosophy of biology community. However, the debate on this concept has remained largely historical or focused on particular cases presented by the scientific empirical advancements. Moreover, in the literature there are no explicit and reasonable arguments about why a philosophical clarification of the concept of gene is needed. In our paper, we claim that a philosophical clarification of the concept of gene (...) does not contribute to biology. Unlike the question, for example, “What is a biological function?”, we argue that the question “What is a gene?” could be answered by means of empirical research, in the sense that biologists' labour is enough to shed light on it. (shrink)

The most conspicuous form of agricultural experiment is the field trial, and within the history of such trials, the arrival of the randomised control trial is considered revolutionary. Originating with R.A. Fisher within British agricultural science in the 1920s and 30s, the RCT has since become one of the most prodigiously used experimental techniques throughout the natural and social sciences. Philosophers of science have already scrutinised the epistemological uniqueness of RCTs, undermining their status as the ‘gold standard’ in experimental design. (...) The present paper introduces a historical case study from the origins of the RCT, uncovering the initially cool reception given to this method by agricultural scientists at the University of Cambridge and the National Institute of Agricultural Botany. Rather than giving further attention to the RCT, the paper focuses instead on a competitor method – the half-drill strip – which both predated the RCT and remained in wide use for at least a decade beyond the latter’s arrival. In telling this history, John Pickstone’s Ways of Knowing is adopted, as the most flexible, and productive way to write the history of science, particularly when sciences and scientists have to work across a number of different kinds of place. It is shown that those who resisted the RCT did so in order to preserve epistemic and social goals that randomisation would have otherwise run a tractor through. (shrink)

Both clinical research and basic science rely on the epistemic practice of extrapolation from surrogate models, to the point that explanatory accounts presented in review papers and biology textbooks are in fact composite pictures reconstituted from data gathered in a variety of distinct experimental setups. This raises two new challenges to previously proposed mechanistic-similarity solutions to the problem of extrapolation: one pertaining to the absence of mechanistic knowledge in the early stages of research and the second to the large number (...) of extrapolations underpinning explanatory accounts. An analysis of the strategies deployed in experimental research supports the conclusion that while results from validated surrogate models are treated as a legitimate line of evidence supporting claims about target systems, the overall structure of research projects also demonstrates that extrapolative inferences are not considered definitive or sufficient evidence, but only partially justified hypotheses subjected to further testing. 1 Introduction2 Surrogate Models2.1 What exactly is a surrogate model?2.2 Why use surrogate models?3 Prior Validation of Surrogate Models3.1 The validation and ranking of surrogate models in the early stages of basic research3.2 The validation of surrogate models in later stages of basic research and in clinical research4 ‘Big Picture’ Accounts and the Extrapolations Underpinning Them4.1 The mosaic nature of mechanistic descriptions in basic science4.2 Challenges for mechanistic-similarity-based validation protocols5 Retrospective Testing of Extrapolated Knowledge5.1 Holistic confirmation5.2 Fallback strategies6 Conclusions. (shrink)

Multidisciplinary models aggregating ‘lower-level’ biological and ‘higher-level’ psychological and social determinants of a phenomenon raise a puzzle. How is the interaction between the physical, the psychological and the social conceptualized and explained? Using biopsychosocial models of pain as an illustration, I argue that these models are in fact level-neutral compilations of empirical findings about correlated and causally relevant factors, and as such they neither assume, nor entail a conceptual or ontological stratification into levels of description, explanation or reality. If inter-level (...) causation is deemed problematic or if debates about the superiority of a particular level of description or explanation arise, these issues are fueled by considerations other than empirical findings. (shrink)

Multidisciplinary models aggregating ‘lower-level’ biological and ‘higher-level’ psychological and social determinants of a phenomenon raise a puzzle. How is the interaction between the physical, the psychological and the social conceptualized and explained? Using biopsychosocial models of pain as an illustration, I argue that these models are in fact level-neutral compilations of empirical findings about correlated and causally relevant factors, and as such they neither assume, nor entail a conceptual or ontological stratification into levels of description, explanation or reality. If inter-level (...) causation is deemed problematic or if debates about the superiority of a particular level of description or explanation arise, these issues are fueled by considerations other than empirical findings. (shrink)

Causal pluralism can be defended not only in respect to causal concepts and methodological guidelines, but also at the finer-grained level of causal inference from a particular source of evidence for causation. An argument for this last variety of pluralism is made based on an analysis of causal inference from randomized experiments (RCTs). Here, the causal interpretation of a statistically significant association can be established via multiple paths of reasoning, each relying on different assumptions and providing distinct elements of information (...) in favour of a causal interpretation. (shrink)

Current debates surrounding the virtues and shortcomings of randomization are symptomatic of a lack of appreciation of the fact that causation can be inferred by two distinct inference methods, each requiring its own, specific experimental design. There is a non-statistical type of inference associated with controlled experiments in basic biomedical research; and a statistical variety associated with randomized controlled trials in clinical research. I argue that the main difference between the two hinges on the satisfaction of the comparability requirement, which (...) is in turn dictated by the nature of the objects of study, namely homogeneous or heterogeneous populations of biological systems. Among other things, this entails that the objection according to which randomized experiments fail to provide better evidence for causation because randomization cannot guarantee comparability is mistaken. (shrink)

Agricultural experimentation is a world in constant evolution, spanning multiple scientific domains and affecting society at large. Even though the questions underpinning agricultural experiments remain largely the same, the instruments and practices for answering them have changed constantly during the twentieth century with the advent of new disciplines like molecular biology, genomics, statistics, and computing. Charting this evolving reality requires a mapping of the affinities and antinomies at work within the realm of agricultural research, and a consideration of the practices, (...) tools and social and political structures in which agricultural experiments are grounded. Three main questions will be addressed to provide an overview of the complex world of agricultural research investigated by the special issue: What is an agricultural experiment? Who is an experimenter in agriculture? Where do agricultural experiments take place? It will become apparent that agricultural experiments have a wide relevance for human development as they touch upon concerns related to human health and nutrition, contribute to policy discussions, and can affect the social and political structures in which farming is embedded. (shrink)

In addition to his experiments on selection in pure lines, Wilhelm Johannsen performed less well-known hybridisation experiments with beans. This article describes these experiments and discusses Johannsen’s motivations and interpretations, in the context of developments in early genetics. I will show that Johannsen first presented the hybridisation experiments as an additional control for his selection experiments. The latter were dedicated to investigating heredity with respect to debates concerning the significance of natural selection of continuous variation for evolution. In the course (...) of the establishment of a Mendelian research program after 1900, the study of heredity gained increasing independence from questions of evolution, and focused more on the modes and mechanisms of heredity. Further to their role as control experiments, Johannsen also saw his hybridisation experiments as contributing to the Mendelian program, by extending the scope of the principles of Mendelian inheritance to quantitative characters. Towards the end of the first decade of genetics, Johannsen revisited his experiments to illustrate the many–many relationship between genes and characters, at a time when that relationship appeared increasingly complex, and the unit-character concept, accordingly, became inadequate. For the philosophy of science, the example shows that experiments can have multiple roles in a research programme, and can be interpreted in the light of questions other than those that motivated the experiments in the first place. (shrink)

The history of twentieth-century life sciences is not exactly a new topic. However, in view of the increasingly rapid development of the life sciences themselves over the past decades, some of the well-established narratives are worth revisiting. Taking stock of where we stand on these issues was the aim of a conference in 2015, entitled “Perspectives for the History of Life Sciences”. The papers in this topical collection are based on work presented and discussed at and around this meeting. Just (...) as the conference, the collection aims at exploring fields in the history of life sciences that appear understudied, sources that have been overlooked, and novel ways of engaging with this material. The papers convened in this collection may not be representative of the field as a whole; but we feel that they do indicate some elements that have received emphasis in recent years, and may become more central in the years to come, such as the history of previously neglected contexts and domains of the life sciences, the question of continuity and change on the level of practices, the history of complexity and diversity in twentieth-century life sciences and the reconsideration of the relationship between history and philosophy of life sciences. (shrink)

Microbial diversity has become a leitmotiv of contemporary microbiology, as epitomized in the concept of the microbiome, with significant consequences for the classification of microbes. In this paper, I contrast microbiology’s current diversity ideal with its influential predecessor in the twentieth century, that of purity, as epitomized in Robert Koch’s bacteriological culture methods. Purity and diversity, the two polar opposites with regard to making sense of the microbial world, have been operationalized in microbiological practice by tools such as the “clean” (...) Petri dish versus the “dirty” Winogradsky column, the latter a container that mimics, in the laboratory, the natural environment that teems with diverse microbial life. By tracing the impact of the practices and concepts of purity and diversity on microbial classification through a history of techniques, tools, and manuals, I show the shifts in these concepts over the last century. Juxtaposing the dominant purity ideal with the more restricted, but continuously articulated, diversity ideal in microbial ecology not only provides a fresh perspective on microbial classification that goes beyond its intellectual history, but also contextualizes the present focus on diversity. By covering the period of a century, this paper outlines a revised longue durée historiography that takes its inspiration from artifacts, such as Petri dish and the Winogradsky column, and thereby simple, but influential technologies that often remain invisible. This enables the problem of historical continuity in modern science to be addressed and the accelerationist narratives of its development to be countered. (shrink)

Microbial diversity has become a leitmotiv of contemporary microbiology, as epitomized in the concept of the microbiome, with significant consequences for the classification of microbes. In this paper, I contrast microbiology’s current diversity ideal with its influential predecessor in the twentieth century, that of purity, as epitomized in Robert Koch’s bacteriological culture methods. Purity and diversity, the two polar opposites with regard to making sense of the microbial world, have been operationalized in microbiological practice by tools such as the “clean” (...) Petri dish versus the “dirty” Winogradsky column, the latter a container that mimics, in the laboratory, the natural environment that teems with diverse microbial life. By tracing the impact of the practices and concepts of purity and diversity on microbial classification through a history of techniques, tools, and manuals, I show the shifts in these concepts over the last century. Juxtaposing the dominant purity ideal with the more restricted, but continuously articulated, diversity ideal in microbial ecology not only provides a fresh perspective on microbial classification that goes beyond its intellectual history, but also contextualizes the present focus on diversity. By covering the period of a century, this paper outlines a revised longue durée historiography that takes its inspiration from artifacts, such as Petri dish and the Winogradsky column, and thereby simple, but influential technologies that often remain invisible. This enables the problem of historical continuity in modern science to be addressed and the accelerationist narratives of its development to be countered. (shrink)