Papers by Christophe Malaterre
Life, 2024
The binary nature of life is deeply ingrained in daily experiences, evident in the stark distinct... more The binary nature of life is deeply ingrained in daily experiences, evident in the stark distinctions between life and death and the living and the inert. While this binary perspective aligns with disciplines like medicine and much of biology, uncertainties emerge in fields such as microbiology, virology, synthetic biology, and systems chemistry, where intermediate entities challenge straightforward classification as living or non-living. This contribution explores the motivations behind both binary and non-binary conceptualizations of life. Despite the perceived necessity to unequivocally define life, especially in the context of origin of life research and astrobiology, mounting evidence indicates a gray area between what is intuitively clearly alive and what is distinctly not alive. This prompts consideration of a gradualist perspective, depicting life as a spectrum with varying degrees of “lifeness”. Given the current state of science, the existence or not of a definite threshold remains open. Nevertheless, shifts in epistemic granularity and epistemic perspective influence the framing of the question, and scientific advancements narrow down possible answers: if a threshold exists, it can only be at a finer level than what is intuitively taken as living or non-living. This underscores the need for a more refined distinction between the inanimate and the living.
Scientometrics, 2024
Author networks in science often rely on citation analyses. In such cases, as in others, network ... more Author networks in science often rely on citation analyses. In such cases, as in others, network interpretation usually depends on supplementary data, notably about authors' research domains when disciplinary interpretations are sought. More general social networks also face similar interpretation challenges as to the semantic content specificities of their members. In this research-in-progress, we propose to infer author networks not from citation analyses but from topic similarity analyses based on a topic-model of published documents. Such author networks reveal, as we call them, "hidden communities of interest" (HCoIs) whose semantic content can easily be interpreted by means of their associated topics in the model. We use an astrobiology corpus of full-text articles (N = 3,698) to illustrate the approach. Having conducted an LDA topic-model on all publications, we identify the underlying communities of authors by measuring author correlations in terms of topic distributions. Adding publication dates makes it possible to examine HCoI evolution over time. This approach to social networks supplements traditional methods in contexts where textual data are available.
Social network analysis is known to provide a wealth of insights relevant to many aspects of poli... more Social network analysis is known to provide a wealth of insights relevant to many aspects of policymaking. Yet, the social data needed to construct social networks are not always available. Furthermore, even when they are, interpreting such networks often relies on extraneous knowledge. Here, we propose an approach to infer social networks directly from the texts produced by actors and the terminological similarities that these texts exhibit. This approach relies on fitting a topic model to the texts produced by these actors and measuring topic profile correlations between actors. This reveals what can be called "hidden communities of interest," that is, groups of actors sharing similar semantic contents but whose social relationships with one another may be unknown or underlying. Network interpretation follows from the topic model. Diachronic perspectives can also be built by modeling the networks over different time periods and mapping genealogical relationships between communities. As a case study, the approach is deployed over a working corpus of academic articles (domain of philosophy of science; N=16,917). Policy Significance Statement Mapping groups of actors sharing similar interests is crucial for understanding and addressing their specific claims. This occurs, for instance, when targeting groups of voters during political campaigns or sorting out claims of sets of stakeholders during negotiations, or still when mapping the balance of pros and cons around large infrastructure public projects. Yet, social network data, such as who-follows-who, that would be necessary to delineate these groups of actors and identify their claims are not always available. In this study, we propose a computational approach that makes use of the textual contents produced by actors to infer underlying social networks. Indeed, since actors' claims manifest themselves in the topical content of the text data they produce, we show that these texts can be used to identify latent groups of individuals sharing similar interests (i.e., hidden communities of interests).
European Journal for Philosophy of Science, 2024
The optimism vs. pessimism debate about the historical sciences is often framed in terms of argum... more The optimism vs. pessimism debate about the historical sciences is often framed in terms of arguments about the relative importance of overdetermination vs. underdetermination of historical claims by available evidence. While the interplay between natural processes that create multiple traces of past events (thereby conducive of overdetermination) and processes that erase past information (whence underdetermination) cannot be ignored, I locate the root of the debate in the epistemic granularity, or intuitively the level of detail, that pervades any historical claim justification network. To reveal the role played by granularity, I elaborate a model of historical claim justification. This model maps out the different elements that enter the justification of historical claims (incl., actual and inferred states of affairs, dating and information reconstructing theories). It also incorporates the different types of processes that affect traces of past events (information creating, preserving, modifying, and destroying processes). Granularity is shown to play a pivotal role in all elements of this model, and thereby in the inferred justification of any historical claim. As a result, while upward or downward shifts in granularity may explain changes about claims being considered as overdetermined or underdetermined, epistemic granularity constitutes an integral part of evidential reasoning in the historical sciences (and possibly elsewhere).
Philosophy of Science, 2024
The central role of such epistemic concepts as theory, explanation, model, or mechanism is rarely... more The central role of such epistemic concepts as theory, explanation, model, or mechanism is rarely questioned in philosophy of science. Yet, what is their actual use in the practice of science? Here, we deploy text-mining methods to investigate the usage of 61 epistemic notions in a corpus of full-text articles from the biological and biomedical sciences (N = 73,771). The influence of disciplinary context is also examined by splitting the corpus into subdisciplinary clusters. The results reveal the intricate semantic networks that these concepts actually form in the scientific discourse, not always following our intuitions, at least in some parts of science.
Digital Scholarship in the Humanities, 2023
As one of the oldest continuously publishing journals in statistics (published since 1901), Biome... more As one of the oldest continuously publishing journals in statistics (published since 1901), Biometrika provides a unique window onto the history of statistics and its epistemic development throughout the 20th and the beginning of the 21st centuries. While the early history of the discipline, with the works of key figures such as Karl Pearson, Francis Galton, or Ronald Fisher, is relatively well-known, the later (and longer) episodes of its intellectual development remain understudied. By applying digital tools to the full-text corpus of the journal articles (N = 5,596), the objective of this study is to provide a novel quantitative exploration of the history of the statistical sciences via an all-encompassing view of 120 years of Biometrika. To this aim, topic-modelling analyses are used and provide insights onto the epistemic content of the journal and its evolution. Striking changes in the thematic content of the journal are documented and quantified for the first time, from the decline of Pearsonian and Weldonian biometrical research and the journal's tight connection to biology in the 1930s, to the rise of modern statistical methods beginning in the 1960s and 1970s. Newly developed approaches are used to infer author networks from publication topics. The resulting network of authors shows the existence of several communities, well-aligned with topic clusters and their evolution through time. It also highlights the role of specific figures over more than a century of publishing history and provides a first window onto the foundation, development, and diverse applications of the statistical sciences.
British Journal for the Philosophy of Science, 2023
Much attention in philosophy of science has been devoted to explicating highly prized concepts su... more Much attention in philosophy of science has been devoted to explicating highly prized concepts such as explanation, theory, or model among many others, resulting in a plurality of nuanced philosophical accounts (e.g., for explanation: the DN-, causal-, unification-or mechanistic-accounts). The rationale for this enterprise is to be found in the central epistemic roles that such concepts are taken to play in science. Yet, do these concepts actually play such significant roles? In this contribution, we propose to investigate the actual usage of epistemic concepts in the practice of science by analysing terminological occurrence patterns in scientific publications. Narrowing down the study to six major epistemic concepts (theory, model, mechanism, explanation, understanding and prediction), we use textmining methods to quantify actual terminological usage and relationships in a corpus of 73,771 full-text scientific articles of the biological and medical sciences (BioMed database). The resulting terminological cartographies partly validate select philosophical intuitions but also suggest notable differences between philosophical reconstructions and the actual roles that epistemic concepts appear to be playing in the scientific discourse. We also investigate the incidence of disciplinary context.
Astrobiology, 2022
The question of the origin of life is a tenacious question that challenges many branches of scien... more The question of the origin of life is a tenacious question that challenges many branches of science but is also extremely multifaceted. While prebiotic chemistry and micropaleontology reformulate the question as that of explaining the appearance of life on Earth in the deep past, systems chemistry and synthetic biology typically understand the question as that of demonstrating the synthesis of novel living matter from nonliving matter independently of historical constraints. The objective of this contribution is to disentangle the different readings of the origin-of-life question found in science. We identify three main dimensions along which the question can be differently constrained depending on context: historical adequacy, natural spontaneity, and similarity to lifeas-we-know-it. We argue that the epistemic status of what needs to be explained-the explanandum-varies from approximately true when the origin-of-life question is the most constrained to entirely speculative when the constraints are the most relaxed. This difference in epistemic status triggers a shift in the nature of the origin-of-life question from an explanation-seeking question in the most constrained case to a fact-establishing question in the lesser-constrained ones. We furthermore explore how answers to some interpretations of the origin-of-life questions matter for other interpretations.
Synthese, 2021
The concept of "life" certainly is of some use to distinguish birds and beavers from water and st... more The concept of "life" certainly is of some use to distinguish birds and beavers from water and stones. This pragmatic usefulness has led to its construal as a categorical predicate that can sift out living entities from non-living ones depending on their possessing specific properties-reproduction, metabolism, evolvability etc. In this paper, we argue against this binary construal of life. Using text-mining methods across over 30,000 scientific articles, we defend instead a degrees-of-life view and show how these methods can contribute to experimental philosophy of science and concept explication. We apply topic-modeling algorithms to identify which specific properties are attributed to a target set of entities (bacteria, archaea, viruses, prions, plasmids, phages and the molecule of adenine). Eight major clusters of properties were identified together with their relative relevance for each target entity (two that relate to metabolism and catalysis, one to genetics, one to evolvability, one to structure, and-rather unexpectedly-three that concern interactions with the environment broadly construed). While aligning with intuitions-for instance about viruses being less alive than bacteria-these quantitative results also reveal differential degrees of performance that have so far remained elusive or overlooked. Taken together, Beyond categorical definitions of life: a data-driven approach to assessing lifeness 2 these analyses provide a conceptual "lifeness space" that makes it possible to move away from a categorical construal of life by empirically assessing the relative lifeness of more-or-less alive entities.
Life, 2021
Natural selection is commonly seen not just as an explanation for adaptive evolution, but as the ... more Natural selection is commonly seen not just as an explanation for adaptive evolution, but as the inevitable consequence of “heritable variation in fitness among individuals”. Although it remains embedded in biological concepts, such a formalisation makes it tempting to explore whether this precondition may be met not only in life as we know it, but also in other physical systems. This would imply that these systems are subject to natural selection and may perhaps be investigated in a biological framework, where properties are typically examined in light of their putative functions. Here we relate the major questions that were debated during a three-day workshop devoted to discussing whether natural selection may take place in non-living physical systems. We start this report with a brief overview of research fields dealing with “life-like” or “proto-biotic” systems, where mimicking evolution by natural selection in test tubes stands as a major objective. We contend the challenge may be as much conceptual as technical. Taking the problem from a physical angle, we then discuss the framework of dissipative structures. Although life is viewed in this context as a particular case within a larger ensemble of physical phenomena, this approach does not provide general principles from which natural selection can be derived. Turning back to evolutionary biology, we ask to what extent the most general formulations of the necessary conditions or signatures of natural selection may be applicable beyond biology. In our view, such a cross-disciplinary jump is impeded by reliance on individuality as a central yet implicit and loosely defined concept. Overall, these discussions thus lead us to conjecture that understanding, in physico-chemical terms, how individuality emerges and how it can be recognised, will be essential in the search for instances of evolution by natural selection outside of living systems.
Synthese, 2021
Pluralism is widely appealed to in many areas of philosophy of science, though what is meant by ‘... more Pluralism is widely appealed to in many areas of philosophy of science, though what is meant by ‘pluralism’ may profoundly vary. Because explanations of behaviour have been a favoured target for pluralistic theses, the sciences of behaviour offer a rich context in which to further investigate pluralism. This is what the topical collection The Biology of Behaviour: Explanatory pluralism across the life sciences is about. In the present introduction, we briefly review major strands of pluralist theses and their motivations. We highlight three distinct types of pluralisms—type pluralism, fragmentation pluralism and insular pluralism—and introduce the articles of the topical collection.
iScience, 2020
Thresholds are widespread in origin of life scenarios, from the emergence of chirality, to the ap... more Thresholds are widespread in origin of life scenarios, from the emergence of chirality, to the appearance of vesicles, of autocatalysis, all the way up to Darwinian evolution. Here, we analyze the ''error threshold,'' which poses a condition for sustaining polymer replication, and generalize the threshold approach to other properties of prebiotic systems. Thresholds provide theoretical predictions, prescribe experimental tests, and integrate interdisciplinary knowledge. The coupling between systems and their environment determines how thresholds can be crossed, leading to different categories of prebiotic transitions. Articulating multiple thresholds reveals evolutionary properties in prebiotic scenarios. Overall, thresholds indicate how to assess, revise, and compare origin of life scenarios.
Synthese, 2020
As a discipline of its own, the philosophy of science can be traced back to the founding of its a... more As a discipline of its own, the philosophy of science can be traced back to the founding of its academic journals, some of which go back to the first half of the twentieth century. While the discipline has been the object of many historical studies, notably focusing on specific schools (e.g., logical empiricism) or major figures of the field (e.g., Carnap, Kuhn), little work has focused on the journals themselves. Here, we investigate contemporary philosophy of science by means of computational text-mining approaches: we apply topic-modeling algorithms to eight major philosophy of science journals, from the 1930s up until 2017. Based on the full-text content of some 15,897 articles, we identified 25 research themes and 8 thematic clusters that show how the research agenda of the philosophy of science has changed in its content over the course of the last eight decades, up to the philosophy of science we now know. We also show how each one of the journals contributed in its own way to this thematic evolution.
PLos One, 2020
Scientific articles have semantic contents that are usually quite specific to their disciplinary ... more Scientific articles have semantic contents that are usually quite specific to their disciplinary origins. To characterize such semantic contents, topic-modeling algorithms make it possible to identify topics that run throughout corpora. However, they remain limited when it comes to investigating the extent to which topics are jointly used together in specific documents and form particular associative patterns. Here, we propose to characterize such patterns through the identification of "topic associative rules" that describe how topics are associated within given sets of documents. As a case study, we use a corpus from a subfield of the humanities-the philosophy of science-consisting of the complete full-text content of one of its main journals: Philosophy of Science. On the basis of a pre-existing topic modeling, we develop a methodology with which we infer a set of 96 topic associative rules that characterize specific types of articles depending on how these articles combine topics in peculiar patterns. Such rules offer a finer-grained window onto the semantic content of the corpus and can be interpreted as "topical recipes" for distinct types of philosophy of science articles. Examining rule networks and rule predictive success for different article types, we find a positive correlation between topological features of rule networks (connectivity) and the reliability of rule predictions (as summarized by the F-measure). Topic associative rules thereby not only contribute to characterizing the semantic contents of corpora at a finer granularity than topic modeling, but may also help to classify documents or identify document types, for instance to improve natural language generation processes.
Biology and Philosophy, 2020
Though only established as a discipline since the 1970s, philosophy of biology has already trigge... more Though only established as a discipline since the 1970s, philosophy of biology has already triggered investigations about its own history. When it comes to assessing the road since travelled—the research questions that have been pursued—manuals and ontologies also offer specific viewpoints, highlighting dedicated domains of inquiry and select work. In this article, we propose to approach the history of the philosophy of biology with a complementary data-driven perspective that makes use of statistical algorithms applied to the complete full-text corpus of one major journal of the field—Biology and Philosophy— from its launch in 1986 up until 2017. By running text-mining and topic-modeling algorithms, we identified 67 key research topics that span across these 32 years. We also investigated the evolution of these topics over time and their fluctuating significance in the journal articles. Our results concur with known episodes or traits of the discipline—for instance, the significance of evolution-related topics or the decrease of articles with a marked historical dimension—but also highlight a diversity of topics that is much richer than what is usually acknowledged.
PLos ONE, 2020
Scientific articles have semantic contents that are usually quite specific to their disciplinary ... more Scientific articles have semantic contents that are usually quite specific to their disciplinary origins. To characterize such semantic contents, topic-modeling algorithms make it possible to identify topics that run throughout corpora. However, they remain limited when it comes to investigating the extent to which topics are jointly used together in specific documents and form particular associative patterns. Here, we propose to characterize such patterns through the identification of “topic associative rules” that describe how topics are associated within given sets of documents. As a case study, we use a corpus from a subfield of the humanities—the philosophy of science—consisting of the complete full-text content of one of its main journals: Philosophy of Science. On the basis of a pre-existing topic modeling, we develop a methodology with which we infer a set of 96 topic associative rules that character- ize specific types of articles depending on how these articles combine topics in peculiar pat- terns. Such rules offer a finer-grained window onto the semantic content of the corpus and can be interpreted as “topical recipes” for distinct types of philosophy of science articles. Examining rule networks and rule predictive success for different article types, we find a positive correlation between topological features of rule networks (connectivity) and the reli- ability of rule predictions (as summarized by the F-measure). Topic associative rules thereby not only contribute to characterizing the semantic contents of corpora at a finer granularity than topic modeling, but may also help to classify documents or identify docu- ment types, for instance to improve natural language generation processes.
Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 2019
Behaviour is a widespread object of research in biology, yet it is often left undefined, and the ... more Behaviour is a widespread object of research in biology, yet it is often left undefined, and the variety of existing definitions have not led to a consensus. We argue that the fundamental problem in defining behaviour has been the assumption that the concept must be categorical: either a phenomenon is a behaviour or it is not. We propose instead that 'behaviour' is best understood as a spectrum concept. We have identified three major characteristics of phenomena which, we argue, fuel the intuitions of biologists regarding the classification of cases as behaviour. All are related to the mechanistic explanations put forth to account for the phenomena, and are (i) the complexity of the mechanism, (ii) the stability of the constitutive entities, and (iii) the quantity and significance of the inputs to the underlying mechanism. We illustrate this new conceptualisation through a three-dimensional behaviour-space which highlights the apparently different conceptualizations of behaviour attributed to humans, animals and plants, showing that they, in fact, all partake of a unified, malleable understanding of a single concept.
BioScience, 2019
Functional diversity holds the promise of understanding ecosystems in ways unattainable by taxono... more Functional diversity holds the promise of understanding ecosystems in ways unattainable by taxonomic diversity studies. Underlying this promise is the intuition that investigating the diversity of what organisms actually do-i.e. their functional traits-within ecosystems will generate more reliable insights into the ways these ecosystems behave, compared to considering only species diversity. But this promise also rests on several conceptual and methodological-i.e. epistemic-assumptions that cut across various theories and domains of ecology. These assumptions should be clearly addressed, notably for the sake of an effective comparison and integration across domains, and for assessing whether or not to use functional diversity approaches for developing ecological management strategies. The objective of this contribution is to identify and critically analyze the most salient of these assumptions. To this aim, we provide an "epistemic roadmap" that pinpoints these assumptions along a set of historical, conceptual, empirical, theoretical, and normative dimensions.
HOPOS, 2019
What is philosophy of science? Numerous manuals, anthologies or essays provide carefully reconstr... more What is philosophy of science? Numerous manuals, anthologies or essays provide carefully reconstructed vantage points on the discipline that have been gained through expert and piecemeal historical analyses. In this paper, we address the question from a complementary perspective: we target the content of one major journal of the field—Philosophy of Science— and apply unsupervised text-mining methods to its complete corpus, from its start in 1934 until 2015. By running topic-modeling algorithms over the full-text corpus, we identified 126 key research topics that span across 82 years. We also tracked their evolution and fluctuating significance over time in the journal articles. Our results concur with and document known and lesser-known episodes of the philosophy of science, including the rise and fall of logic and language-related topics, the relative stability of a metaphysical and ontological questioning (space and time, causation, natural kinds, realism), the significance of epistemological issues about the nature of scientific knowledge as well as the rise of a recent philosophy of biology and other trends. These analyses exemplify how computational text-mining methods can be used to provide an empirical large-scale and data-driven perspective on the history of philosophy of science that is complementary to other current historical approaches.
The Routledge Handbook of the Philosophy of Biodiversity, 2016
Questions of biodiversity are so much more likely to be associated with the fate of larger plants... more Questions of biodiversity are so much more likely to be associated with the fate of larger plants and animals that one may wonder whether microorganisms matter at all in this debate. Nevertheless, microbial diversity has become the focus of intense research in the past decades, owing much to technical advances that now greatly facilitate the identification of microorganisms and their study. Despite being largely invisible to the naked eye, microorganisms account for a significant proportion of Earth’s biomass, species abundance and richness. Even more importantly, it is now well-established that microorganisms drive massive biogeochemical cycles that affect the entire planet. Microbial diversity matters, and this chapter will be largely about that. Along the way, my objective will also be to point to specific philosophical questions that the study of microbial diversity raises. In Section 1, I first provide a brief account of the concept of microorganism and how the field of microbial diversity studies has recently developed in relationship to both microbiology and ecology. I then review, in Section 2, a number of reasons why microorganisms are interesting to look at from a diversity point of view, in particular their quantity, ubiquity and ecological significance. In Section 3, I address the question of defining microbial diversity, and focus on the units of diversity problem in the context of microorganisms, with a special attention to taxonomic and functional perspectives. In Section 4, I review key reasons why microbial diversity matters, including a set of applied and purely theoretical reasons. Because diversity studies venture into smaller and smaller entities, such as viruses, this raises the question of extending microbial diversity to non-cellular micro-entities, as I show in Section 5. And in Section 6, I review how conservation questions also arise in the context of microbial diversity.
Uploads
Papers by Christophe Malaterre
Développées à la charnière des XIXe et XXe siècles comme alternative aux deux approches antinomiques du vivant que sont le vitalisme et le mécanisme, la notion philosophique d'émergence connait aujourd'hui de nouveaux développements : avec la prise de conscience de la complexité du vivant, un nouveau discours émergentiste refait surface en biologie et dans le champ scientifique des origines de la vie. Que signifie la notion d'émergence lorsqu'elle s'applique à l'apparition de la vie sur Terre ? Quelles sont sa pertinence et sa portée ?
Dans ce livre, Christophe Malaterre propose une clarification conceptuelle de la notion philosophique d'émergence ; il en défend une conception epistémique et contextuelle, adossée à la notion d'explication. En s'inspirant des travaux les plus contemporains sur les origines de la vie, il montre que, selon le contexte epistémique dans lequel le phénomène est évalué, la qualification de l'apparition de la vie comme émergente est, ou non, justifié. Il défend alors la thèse selon laquelle la caractérisation émergentiste de l'apparition de la vie n'est qu'une conséquence temporaire des limites de nos connaissances scientifiques."