Adrian Currie

We argue for conceptual pluralism about music. In our view, there is no right answer to the question ‘What is music?’ divorced from some context or interest. Instead, there are several, non-equivalent music concepts suited to different interests – from within some tradition or practice, or by way of some research question or field of inquiry. We argue that unitary definitions of music are problematic, that the role music concepts play in various research questions should motivate conceptual pluralism about music, and that taking music pluralism seriously grounds a fruitful research programme in aesthetics. We suspect that pluralism about music is a good test case for the utility of pluralism in aesthetics more generally, and we present it as such.

Many biological investigations are organized around a small group of species, often referred to as ‘model organisms’, such as the fruit fly Drosophila melanogaster. The terms ‘model’ and ‘modelling’ also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka–Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown to have different epistemic characters. Theoretical modelling is grounded in explicit and known analogies between model and target. By contrast, inferences from model organisms are empirical extrapolations. Often such extrapolation is based on shared ancestry, sometimes in conjunction with other empirical information. One implication is that such inferences are unique to biology, whereas theoretical models are common across many disciplines. We close by discussing the diversity of uses to which model organisms are put, suggesting how these relate to our overall account. 1 Introduction2 Volterra and Theoretical Modelling3 Drosophila as a Model Organism4 Generalizing from Work on Model Organisms5 Phylogenetic Inference and Model Organisms6 Further Roles of Model Organisms6.1 Preparative experimentation6.2 Model organisms as paradigms6.3 Model organisms as theoretical models6.4 Inspiration for engineers6.5 Anchoring a research community7 Conclusion

Historical scientists frequently face incomplete data, and lack direct experimental access to their targets. This has led some philosophers and scientists to be pessimistic about the epistemic potential of the historical sciences. And yet, historical science often produces plausible, sophisticated hypotheses. I explain this capacity to generate knowledge in the face of apparent evidential scarcity by examining recent work on Thylacoleo carnifex, the ‘marsupial lion’. Here, we see two important methodological features. First, historical scientists are methodological omnivores, that is, they construct purpose-built epistemic tools tailored to generate evidence about highly specific targets. This allows them to produce multiple streams of independent evidence and thus maximize their epistemic reach. Second, investigative scaffolding: research proceeds in a piece-meal fashion, information only gaining evidential relevance once certain hypotheses are well supported. I illustrate scaffolding in a discussion of the nature of functional ascription in paleobiology. Frequently, different senses of ‘function’ are not discriminated during paleobiological investigation—something which can mar adaptationist investigations of extant organisms. However, I argue that, due to scaffolding, conflating senses of ‘function’ can be the right thing to do. Coarse-grained functional hypotheses are required before it is clear what evidence could discriminate between more fine-grained ones. I draw on omnivory and scaffolding to argue that pessimists make a bad empirical bet. It is a bad idea to bet against the epistemic fortunes of such opportunistic and resourceful scientists, especially when we have reason to think we will systematically underestimate the amount of evidence ultimately available to them

David Sepkoski and Michael Ruse’s edited collection The Peolobiological Revolution covers the changes in paleontological science in the last half-century. The collection should be of interest to philosophers of science (particularly those interested in non-reductive unity) as well as historians. I give an overview of the content and major themes of the volume and draw some lessons for the philosophy of science along the way. In particular, I argue that the history of paleontology demands a new approach to philosophical delineation of sciences

Cognitive archaeologists infer from material remains to the cognitive features of past societies. We characterize cognitive archaeology in terms of trace-based reasoning, which in the case of cognitive archaeology involves inferences drawing upon background theory linking objects from the archaeological record to cognitive features. We analyse such practices, examining work on cognitive evolution, language, and musicality. We argue that the central epistemic challenge for cognitive archaeology is often not a paucity of material remains, but insufficient constraint from cognitive theories. However, we also argue that the success of cognitive archaeology does not necessarily require well-developed cognitive theories: Success might instead lead to them.

I develop an account of the relationship between aesthetics and knowledge, focusing on scientific practice. Cognitivists infer from ‘partial sensitivity’—aesthetic appreciation partly depends on doxastic states—to ‘factivity’, the idea that the truth or otherwise of those beliefs makes a difference to aesthetic appreciation. Rejecting factivity, I develop a notion of ‘epistemic engagement’: partaking genuinely in a knowledge-directed process of coming to epistemic judgements, and suggest that this better accommodates the relationship between the aesthetic and the epistemic. Scientific training (and other knowledge-directed activities), I argue, involves ‘attunement’: the co-option of aesthetic judgements towards epistemic ends. Thus, the connection between aesthetic appreciation and knowledge is psychological and contingent. This view has consequences for the warrant of aesthetic judgement in science, namely, the locus of justification is those processes of attunement, not the aesthetic judgements themselves.

Caitlin Wylie’s “Preparing Dinosaurs: the work behind the scenes” (MIT Press 2021) provides a rich ethnographic analysis of the work of fossil preparators. On her account, knowledge in vertebrate paleontology is mediated through a three-way division of labour between paleontologists, preparators and volunteers, each with their own role, expertise and responsibility. In this review, I develop her notion of ‘preparation as knowledge’, focusing in particular on the nature of objectivity in paleontological knowledge and on the middle-road she indicates between constructivist and realist approaches to epistemology.

Many accounts of scientific modeling conceive of models as fictions: scientists interact with models in ways analogous to various aesthetic objects. Fictionalists follow most other accounts of modeling by taking them to be revelatory of the actual world in virtue of bearing some resemblance relation to a target system. While such fictionalist accounts capture crucial aspects of modelling practice, they are ill-suited to some design and engineering contexts. Here, models sometimes serve to underwrite design projects whereby real-world targets are constructed. In such circumstances, it is unclear what the model is supposed to resemble. Further, while fictionalists often require that models qua models have their content in virtue of construal or interpretation, in some engineering and design contexts success-conditions do not require such content—all that is required is that the model generates the required outputs. I take these points to motivate a view which accommodates fictionalism, but is broader. I articulate and defend an account of models as tools: specifically, material objects which are put to particular uses in particular contexts.

Angela Potochnik’s Idealization and the Aims of Science defends an ambitious and systematic account of scientific knowledge: ultimately science pursues human understanding rather than truth. Potochnik argues that idealization is rampant and unchecked in science. Further, given that idealizations involve departures from truth, this suggests science is not primarily about truth. I explore the relationship between truths about causal patterns and scientific understanding in light of this, and suggest that Potochnik underestimates the importance and power of highly particular narrative explanations.

Angela Potochnik’s Idealization and the Aims of Science (Chicago) defends an ambitious and systematic account of scientific knowledge: ultimately science pursues human understanding rather than truth. Potochnik argues that idealization is rampant and unchecked in science. Further, given that idealizations involve departures from truth, this suggests science is not primarily about truth. I explore the relationship between truths about causal patterns and scientific understanding in light of this, and suggest that Potochnik underestimates the importance and power of highly particular narrative explanations.

Many accounts of scientific modeling conceive of models as fictions: scientists interact with models in ways analogous to various aesthetic objects. Fictionalists follow most other accounts of modeling by taking them to be revelatory of the actual world in virtue of bearing some resemblance relation to a target system. While such fictionalist accounts capture crucial aspects of modelling practice, they are ill-suited to some design and engineering contexts. Here, models sometimes serve to underwrite design projects whereby real-world targets are constructed. In such circumstances, it is unclear what the model is supposed to resemble. Further, while fictionalists often require that models qua models have their content in virtue of construal or interpretation, in some engineering and design contexts success-conditions do not require such content—all that is required is that the model generates the required outputs. I take these points to motivate a view which accommodates fictionalism, but is broader. I articulate and defend an account of models as tools: specifically, material objects which are put to particular uses in particular contexts.

Biologists often study living systems in light of their having evolved, of their being the products of various processes of heredity, adaptation, ancestry, and so on. In their investigations, then, biologists think comparatively: they situate lineages into models of those evolutionary processes, comparing their targets with ancestral relatives and with analogous evolutionary outcomes. This element characterizes this mode of investigation - 'comparative thinking' - and puts it to work in understanding why biological science takes the shape it does. Importantly, comparative thinking is local: what we can do with knowledge of a lineage is limited by the evolutionary processes into which it fits. In light of this analysis, the Element examines the experimental study of animal cognition, and macroevolutionary investigation of the 'shape of life', demonstrating the importance of comparative thinking in understanding both the power and limitations of biological knowledge.

We argue that narratives are central to the success of historical reconstruction. Narrative explanation involves tracing causal trajectories across time. The construction of narrative, then, often involves postulating relatively speculative causal connections between comparatively well-established events. But speculation is not always idle or harmful: it also aids in overcoming local underdetermination by forming scaffolds from which new evidence becomes relevant. Moreover, as our understanding of the past’s causal milieus become richer, the constraints on narrative plausibility become increasingly strict: a narrative’s admissibility does not turn on mere logical consistency with background data. Finally, narrative explanation and explanation generated by simple, formal models complement one another. Where models often achieve isolation and precision at the cost of simplification and abstraction, narratives can track complex changes in a trajectory over time at the cost of simplicity and precision. In combination both allow us to understand and explain highly complex historical sequences.

Here’s something I’m willing to claim we know: Homo sapiens, in particular the Polynesian settlers who first arrived in Aotearoa around the twelfth century, take the lion’s share of causal blame for the extinction of a lineage of enormous flightless birds: the moa. Stretching to three metres at their tallest, moa were a distinctive and remarkable feature of Aotearoa’s primeval forests, playing the main browser and grazer role in this unique bird-based ecosystem. Once humans turned up forests were burned, moa were stalked, and human-0introduced arrivals such as kiore had dramatic ecological repercussions. Within a few centuries, the moa were gone.

Both paleobiology and investigations of ‘major evolutionary transitions’ are intimately concerned with the macroevolutionary shape of life. It is surprising, then, how little studies of major transitions are informed by paleontological perspectives and. I argue that this disconnect is partially justified because paleobiological investigation is typically ‘phenomena-led’, while investigations of major transitions are ‘theory-led’. The distinction turns on evidential relevance: in the former case, evidence is relevant in virtue of its relationship to some phenomena or hypotheses concerning those phenomena; in the latter, evidence is relevant in virtue of providing insights into, or tests of, an abstract body of theory. Because paleobiological data is by-and-large irrelevant to the theory which underwrites the traditional conception of major transitions, it is of limited use to that research program. I suggest that although the traditional conception of major transitions is neither ad-hoc or problematically incomplete, its promise of providing unificatory explanations of the transitions is unlikely to be kept. Further, examining paleobiological investigations of mass extinctions and organogenesis, I further argue that whether or not transitions in paleobiology count as ‘major’ turns on how we conceive of major transitions ; although major transitions potentially have a unified theoretical basis, recent developments suggest that investigations are becoming increasingly phenomena-led; adopting phenomena-led investigations maximizes the evidence available to paleobiologists.

There has been much discussion of the moral, legal and prudential implications of geoengineering, and of governance structures for both the research and deployment of such technologies. However, insufficient attention has been paid to how such measures might affect geoengineering in terms of the incentive structures which underwrite scientific progress. There is a tension between the features that make science productive, and the need to govern geoengineering research, which has thus far gone underappreciated. I emphasize how geoengineering research requires governance which reaches beyond science’s traditional boundaries, and moreover requires knowledge which itself reaches beyond what we traditionally expect scientists to know about. How we govern emerging technologies should be sensitive to the incentive structures which drive science.

It is often thought that the vindication of experimental work lies in its capacity to be revelatory of natural systems. I challenge this idea by examining laboratory experiments in ecology. A central task of community ecology involves combining mathematical models and observational data to identify trophic interactions in natural systems. But many ecologists are also lab scientists: constructing microcosm or ‘bottle’ experiments, physically realizing the idealized circumstances described in mathematical models. What vindicates such ecological experiments? I argue that ‘extrapolationism’, the view that ecological lab work is valuable because it generates truths about natural systems, does not exhaust the epistemic value of such practices. Instead, bottle experiments also generate ‘understanding’ of both ecological dynamics and empirical tools. Some lab work, then, aids theoretical understanding, as well as targeting hypotheses about nature. 1Introduction2Trophic Interactions and Observational Techniques3Cryptic Dynamics in Bottle Experiments4Extrapolationism 4.1Ecological possibility and actuality4.2Ecological heterogeneity5Understanding 5.1The epistemic good of understanding5.2Bottle experiments as understanding-generators5.3How understanding travels6Conclusion

Common philosophical accounts of creativity align creative products and processes with a particular kind of agency: namely, that deserving of praise or blame. Considering evolutionary examples, we explore two ways of denying that creativity requires forms of agency. First, we argue that decoupling creativity from praiseworthiness comes at little cost: accepting that evolutionary processes are non-agential, they nonetheless exhibit many of the same characteristics and value associated with creativity. Second, we develop a ‘product-first’ account of creativity by which a process is creative just in case it gives rise to products deserving of certain forms of aesthetic engagement.