Biology & Philosophy最新文献

Norms play a crucial role in governing human societies. From an early age, humans possess an innate understanding of norms, recognizing certain behaviours, contexts, and roles as being governed by them. The evolution of normativity has been linked to its contribution to the promotion of cooperation in large groups and is intertwined with the development of joint intentionality. However, there is no evolutionary consensus on what normatively differentiated our hominin ancestors from the phylogenetic lineage leading to chimpanzees and bonobos. Here we propose that the development of teaching through a process of evaluative feedback between parent and offspring functioned as a prerequisite for the later development of normativity. Parents approve or disapprove of offspring’s behaviours based on their own learned knowledge of what is appropriate or inappropriate. We argue our proposition using a simple model of cultural transmission, which shows the adaptive advantage offered by these elementary forms of teaching. We show that an important part of this adaptive advantage can arise from the benefits derived from guidance about which behaviours to adopt or reject. We propose that this type of guidance has fundamental elements that characterise the normative world. We complete our argument by reviewing several studies that examine the emergence of normativity in young children without prior exposure to a normative framework with respect to the behaviours under analysis. We suggest that this normativity is best interpreted as manifestations of teaching among young children rather than as norm recognition among early normative children.

Evolutionary changes and interspecific diversity in sexual coercion and autonomy are often linked to indirect selection on mate preferences. Yet, this approach overlooks the small fraction of indirect selection in total selection on mate choice and assumes unnecessarily specific conditions in the recent ‘autonomy-enhancing’ risk-reduction model. This paper proposes a more parsimonious approach based on direct selection and basic signalling theory, incorporating ecological variables to better explain sexual biodiversity. Particularly, the spatial dimensionality of mating environments is emphasized for its role in enhancing sexual freedom through both diminishing monopolization and elevating escape potential from sexual coercion. Empirical evidence, ranging from waterfowl to humans, seems to better align with this ecologically constrained signalling perspective. Furthermore, it suggests that choosers keep coercion risk at ecological baseline by leveraging their escape potential. This repositions intriguing protective elements like bowerbirds' constructions as courtship features that have been bargained to respect sexual autonomy rather than enhancing it through indirect selection. It implies that courtship induced risks, such as reduced mobility, may in principle increase substantially precisely because they are offset by protective measures. Future research could reveal the prevalence of such risk-balancing strategies, advancing our understanding of mating dynamics. This work suggests new theoretical and empirical research avenues within the ecology of mating dynamics.

Frans de Waal (1948-2024) transformed our understanding of primate cognition and social behavior, shaping the perspectives of scientists, philosophers, and the general public through his groundbreaking research and engagingpopular books.

This paper examines existing frameworks for understanding domestication and proposes a domestication landscape framework. Driven by the selection pressures of captivity and/or mutualism within a domesticator-dominated environment, domestication is the generations-long multidirectional process through which a domesticate accumulates new genetic and behavioral traits, potentially causing reproductive isolation between wild and domestic forms of the domesticate organism. Rather than understanding domestication as fixed states in a wild/domestic binary, domestication can be best understood as a dynamic multidimensional process of growing and declining domesticator influence on a domesticate’s genes and behavior. The categories, of wild, feral, tame, and domestic exist as blurry regions within a two-dimensional landscape that species will traverse at variable speeds. An organism’s path will vary depending on its environment and the particular domestication relationship at play. Domestication occurs through two potential pathways, either through captivity or through mutualism, though both may no longer be required once a domesticate’s dependence on the domesticator becomes clearly established. For the purposes of domestication, captivity requires intentional containment and resource dependence or reproductive control. When driven by mutualism, the domestication process does not require intent and, thereby, can occur with non-human domesticators. Alongside the coordinative consensus principle, the domestication landscape model can help achieve more functional pluralism between disciplines within domestication studies when organisms’ levels of genetic and behavioral influence are provided. Finally, this model suggests that while dingoes may have at one point been domesticated, it may be appropriate to view them as wild and perhaps even native organisms.

According to the standard formulation, natural selection requires variation, differential fitness, and heritability. I argue that this formulation is inadequate because it fails to distinguish natural selection from artificial selection, intelligent design, forward-looking orthogenetic selection, and adaptation via the selection of nonrandom variation. I suggest adding a no teleology condition. The no teleology condition says that the evolutionary process is not guided toward an endpoint represented in the mind of an agent, variation is produced randomly with respect to adaptation, and selection pressures are not forward looking.

Minimal residual disease (MRD), a measure of residual cancer cells, is a concept increasingly employed in precision oncology, touted as a key predictive biomarker to guide treatment decisions. This paper critically analyzes the expanding role of MRD as a predictive biomarker in hematologic cancers. I outline the argument for MRD as a predictive biomarker, articulating its premises and the empirical conditions that must hold for them to be true. I show how these conditions, while met in paradigmatic cases of MRD use in cancer, may not hold across other cancers where MRD is currently being applied, weakening the argument that MRD serves as an effective predictive biomarker across cancer medicine.

This essay review explores Steven Mithen’s interdisciplinary approach to the origins and evolution of language in The Language Puzzle (2024). It focuses mainly on what I call his iconic vocal origins hypothesis. Mithen challenges the prevalent gestural origins hypothesis, suggesting instead that early prehistoric languages were predominantly vocal and iconic, with conventionalization – as characteristic of symbol use – emerging later. The Language Puzzle draws on research from archaeology, philosophy, computer science, developmental psychology, and many other fields, thus assembling a wealth of insights from various disciplines. While intriguing, Mithen’s suggestion that prehistoric languages may have relied on iconicity instead of conventionalization faces substantial problems, which are discussed in this review essay. In the final section, I also briefly review the important conclusion chapter of Mithen’s book, which contains an imaginative outline of how language evolved from the last common ancestor up until modern H. sapiens. My criticisms of the iconic vocal origins hypothesis notwithstanding, The Language Puzzle is a valuable resource for anyone interested in language evolution, and once again showcases Mithen’s wide-ranging expertise and masterful writing.

Machine metaphors abound in life sciences: animals as automata, mitochondria as engines, brains as computers. Philosophers have criticized machine metaphors for implying that life functions mechanically, misleading research. This approach misses a crucial point in applying machine metaphors to biological phenomena: their reciprocity. Analogical modeling of machines and biological entities is not a one-way street where our understanding of biology must obey a mechanical conception of machines. While our understanding of biological phenomena undoubtedly has been shaped by machine metaphors, the resulting insights have likewise altered our understanding of what machines are and what they can do.

Are plants sentient? Several researchers argue that plants might be sentient. They do so on the grounds that plants exhibit cognitive behaviour similar to that of sentient organisms and that they possess a vascular system which is functionally equivalent to the animal nervous system. This paper will not attempt to settle the issue of plant sentience. Instead, the paper has two goals. First, it provides a diagnosis of the current state of the debate on plant sentience. It is argued that the current state of the debate on plant sentience cannot yield any progress because the behavioural and physiological similarities pointed to as a way of inferring consciousness are not, in themselves, indicative of consciousness. Second, the paper proposes we adopt the theory-light approach proposed by Birch (Noûs 56(1):133–153, 2022. https://doi.org/10.1111/nous.12351) whereby we start to test for clusters of cognitive abilities facilitated by consciousness in plants. Currently, there are no such tests and therefore no evidence for plant sentience. The paper proposes that the task for future research on plants be in line with the tests outlined in the theory-light approach.

This paper analyzes three multiscale modeling techniques that are commonly used in biology and physics and uses those cases to construct a normative framework for tailoring multiscale modeling techniques to specific modeling contexts. I argue that the selection of a multiscale modeling technique ought to focus on degrees of relative autonomy between scales, the measurable macroscale parameters of interest, indirect scaling relationships mediated by mesoscale features, and the degree of heterogeneity of the system’s mesoscale structures. The unique role that these features play in multiscale modeling reveals several important methodological, epistemological, and metaphysical questions for future philosophical investigations into multiscale modeling.