History and Philosophy of the Life Sciences最新文献

The concept of regulation is used in biology to explain properties such as stability, robustness, and long-term persistence of biological systems. Regulation claims often focus, however, on the capabilities of these systems, rather than the mechanisms underlying them. In an attempt to produce a full-fledged theoretical account of regulation, a stricter concept has been proposed by Bich and colleagues based on the theory of biological autonomy. According to these authors, regulation is exerted by specialized subsystems that can change the constitutive regime of a system (enabling it to deal with a wider range of perturbations) but whose dynamics are not specified by the latter. In this paper, we present a brief survey on how regulation has been treated in biology and, more specifically, in ecology. We show how the ecological literature attributes regulatory powers either to organismic phenomena or to the propagation of perturbations through the network of relations in ecological systems. We were not able to find any study proposing a specialized subsystem dedicated to regulation in an ecological system. This raises doubts about the feasibility of a regulatory subsystem such as conceived by Bich and colleagues. Nonetheless, we argue that ecological systems may encompass more than just dynamic stability and feedback mechanisms, such that it can be worthy applying their concept to investigate regulation in these systems.

This paper examines the early evolution of cognition in animals through the lens of the Transitions in Structural Complexity approach. By focusing on the emergence and transformation of coordination systems, the study identifies three progressive stages: collective, specialised, and integrated coordination. Each stage is characterised by distinct structural innovations-ranging from contractile epithelia and cytoskeletal coupling to the development of neurons, neurosecretory cells, and integrated nervous tissues-and is shaped by the processes of modularisation, subfunctionalisation, and integration. By conceptualising coordination as a transferable biological function, this approach offers an analysis of the evolution of this capacity without presupposing specific mechanisms or structures. Rather than defining cognition in advance, this approach tracks how functions associated with cognition become structurally embodied in multicellular systems through the progressive reorganisation of coordination across levels of biological organisation. Besides offering a general schema for analysing the early stages of cognitive evolution in metazoans, this approach has broader implications for the comparative study of cognition and the structural focus within the major evolutionary transitions framework.

Recent work in philosophy of measurement has converged on a "theory-dependence consensus", according to which measurement reliability requires sophisticated theoretical scaffolding. This consensus has been largely shaped by case studies from physics and high-precision metrology. This paper questions whether this consensus adequately captures measurement practices in biology, where researchers often operate under significant uncertainty about their target phenomena. Through detailed historical analysis of early electrophysiological research-from Carlo Matteucci through Emil du Bois-Reymond, Hermann von Helmholtz, and Ludimar Hermann-I examine how quantitative measurement practices emerged under theoretical uncertainty. The cases reveal recurring patterns including productive theoretical inadequacy and instrumental constraint-driven discovery, supporting an analytical framework that distinguishes multiple levels of theoretical involvement in measurement. Building on these cases, I argue that biological measurement practices function productively as strategies for causal discovery, and theoretically inadequate frameworks prove epistemically valuable by structuring empirical inquiry to reveal previously unrecognised causal factors.

The consensus in philosophy of biology seems to be that although nothing in biological systems is strictly incompatible with physical laws, biology is to a very great extent autonomous from physics. The main thesis of this paper is that, although biology is autonomous from the physical sciences in several ways, it is not explanatorily independent from physics. Physical explanations are pervasive and important in biology, including in evolutionary biology. The paper presents three case studies of physical explanations in evolutionary biology: a case of adaptation to pressure in deep-sea invertebrates, which illustrates how a physical parameter imposes selective pressures that organisms adapt to by changing their own physical properties; the case of water viscosity and the evolution of multicellularity, which shows how a global change in a physical parameter is thought to have triggered a macroevolutionary event; and the case of quantum tunnelling in respiration, which shows how quantum physics is relevant to the evolution of sex in eukaryotes.

This paper analyzes an episode of scientific work that was prompted by observations of a novel defect in early embryonic development, which was unexpectedly induced in an experimental context and has tentatively been dubbed "xenogastrulation." The researchers worked to individuate this as a novel phenomenon-both by distinguishing it from what it is not (e.g., exogastrulation) and by forming a positive conception of what it is-in order to facilitate further inquiry. Our analysis provides new insights into the role of explanatory reasoning in nascent experimental research programs. We argue that the researchers' efforts to individuate the novel phenomenon were entangled with their efforts to explain it. By this, we mean that tentative answers to the individuative question, "what is it?" also served as tentative answers to the explanatory question, "by what means does it occur?" This case study therefore demonstrates that explanation need not wait until an explanandum has been clearly individuated but instead can be deeply entangled with the process of individuating the explanandum in the first place.

In 1949, the social psychologists Leonard S. Cottrell, Jr. and Rosalind Dymond wrote a paper calling for increased attention to the empathic responses in empirical social psychology. The empathic responses, they wrote, "occupy a crucial position in human interaction and adjustment" (Psychiatry 12(4):355-359, 1949, https://doi.org/10.1080/00332747.1949.11022747 ). Not only practically important for therapy and communication, the empathic responses were considered to be foundational for the very development of the self. In this paper, I examine challenges that arose in the 1940s and 1950s, when researchers attempted to subject empathy to scientific scrutiny. I focus specifically on conceptual and methodological problems that Dymond faced in developing her measures of empathy, which are typically considered to be the first in existence. This foray into the history of empathy measures offers a case study for considering questions about validity and coherence in the philosophy of psychological measurement.

Estuaries, the dynamic transitional zones where rivers converge with oceans, represent complex ecosystems characterized by the mixing of fresh and saltwater, resulting in what is known as brackish water. These coastal interfaces, along with tidal flats and other littoral features, embody a unique duality, existing as neither fully terrestrial nor entirely marine environments. This ambiguous nature poses significant challenges for scientific inquiry when coastal regions become the focus of study. Inspired by Stefan Helmreich's (2011) call to 'think with seawater', we propose the concept of "brackish knowledge" as a way to engage with knowledge practices that are entangled with both the material complexity of the environments they describe and the practical contingencies of the contemporary science system. In this paper, we follow the development and maintenance of the General Estuarine Transport Model (GETM), a hydrodynamic model designed to represent the complex tidal processes in estuaries and shallow shelf-sea areas such as those along the Dutch coast. We show how the model's developers move across and recombine properties that are often framed in opposition to one another, namely the physical and ecological, social and computational, and public and private, in order to continue making knowledge about coastal and estuarine environments. We conclude that the material, epistemic, and institutional dimensions of brackish knowledge should be considered alongside one another in the governing of scientific knowledge about environmental change, since this ultimately shapes what can be known about potential coastal futures.

In the decade between the mid-1980s and mid-1990s, critical voices within the conservation biology community argued that site selection for protected areas was most often done in a way that was unscientific. Conservation practitioners, many of whom became acutely aware of the constraints of the policy world through direct participation, believed that they needed to think pragmatically about establishing a scientific basis for the design of protected areas. Some of the conservation practitioners came to see rationalistic tools such as optimization algorithms embedded within decision-support systems as means of reconciling social, economic, and environmental interests. This paper recapitulates the history of the first significant policy initiative that purported to use algorithmic decision support software, MARXAN, by interweaving environmental history, history of computing, and history of science. Specifically, it is a historical reconstruction of the use of MARXAN in its first large-scale conservation policy project: a rezoning of Australia's Great Barrier Reef that took place between 1998 and 2004. This paper asks: how exactly was MARXAN used in the conservation policy planning initiative? And, what role did MARXAN play in narratives about the success of the policy initiative? I argue that in Australian case, it was the commitment to political value of democratic deliberation and not the allure of algorithmic objectivity that stood behind what was by many considered an agenda-setting marine conservation policy. These findings add support to the growing consensus in critical algorithmic studies against algorithmic determinism by situating the agency of the users of MARXAN within a larger context of a "drama" as reported (Hilgartner in Science on Stage: Expert Advice as Public Drama. Stanford University Press, Stanford, 2000) of science advice.

In contemporary biology laboratories, animal models have become essential scientific tools. From modeling psychiatric disorders to investigating embryonic development and genetic diseases, they facilitate research across various fields. Although scientists are generally cautious about extrapolating results from these models, this paper introduces a thought-provoking case study-the three-criteria addiction model-which boldly endeavors to induce "full addiction" in laboratory rats. Given the model's influence in the field of behavioral neuroscience, this paper aims to conduct its comprehensive epistemic analysis, exploring whether "addicted rats" genuinely exist and the potential implications for understanding addiction and mental disorders. Conducting such an epistemic analysis presents a difficulty in itself due to the heterogeneity of approaches employed by philosophers of science to analyze animal models. The second objective of this paper is, therefore, to propose a general method to guide epistemic scrutiny of animal models.