Paleobiologists often provide simple narratives to explain complex, contingent episodes. These narratives are sometimes ‘one-shot hypotheses’ which are treated as being mutually exclusive with other possible explanations of the target episode, and are thus extended to accommodate as much about the episode as possible. I argue that a provisional preference for such hypotheses provides two kinds of productive scaffolding. First, they generate ‘hypothetical difference-makers’: one-shot hypotheses highlight and isolate empirically tractable dependencies between variables. Second, investigations of hypothetical difference-makers provision explanatory (...) resources, the ‘raw materials’ for constructing more complex—and likely more adequate—explanations. Provisional preferences for simple, one-shot hypotheses in historical science, then, is defeasibly justified on indirect—strategic—grounds. My argument is made in reference to recent developments regarding the K–Pg extinction. (shrink)

Debate about the epistemic prowess of historical science has focused on local underdetermination problems generated by a lack of historical data; the prevalence of information loss over geological time, and the capacities of scientists to mitigate it. Drawing on Leonelli’s recent distinction between ‘phenomena-time’ and ‘data-time’ I argue that factors like data generation, curation and management significantly complexifies and undermines this: underdetermination is a bad way of framing the challenges historical scientists face. In doing so, I identify circumstances of epistemic (...) scarcity where underdetermination problems are particularly salient, and discuss cases where legacy data—data generated using differing technologies and systems of practice—are drawn upon to overcome underdetermination. This suggests that one source of overcoming underdetermination is our knowledge of science’s past. Further, data-time makes agnostic positions about the epistemic fortunes of scientists working under epistemic scarcity more plausible. But agnosticism seems to leave philosophers without much normative grip. So, I sketch an alternative approach: focusing on the strategies scientists adopt to maximize their epistemic power in light of the resources available to them. (shrink)

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. (shrink)

An overview on archaeological evidence, provided by Colagè and d’Errico, reveals that the timing, location, and pace of cultural innovations are more consistent with scenarios that take culture, rather than genetic evolutionary processes, as the key driving force for human cognition. The authors elaborate on those mechanisms by which cultural evolution operates, with a specific focus on cultural exaptation and cultural neural reuse.

The paper works towards an account of explanatory integration in biology, using as a case study explanations of the evolutionary origin of novelties-a problem requiring the integration of several biological fields and approaches. In contrast to the idea that fields studying lower level phenomena are always more fundamental in explanations, I argue that the particular combination of disciplines and theoretical approaches needed to address a complex biological problem and which among them is explanatorily more fundamental varies with the problem pursued. (...) Solving a complex problem need not require theoretical unification or the stable synthesis of different biological fields, as items of knowledge from traditional disciplines can be related solely for the purposes of a specific problem. Apart from the development of genuine interfield theories, successful integration can be effected by smaller epistemic units (concepts, methods, explanations) being linked. Unification or integration is not an aim in itself, but needed for the aim of solving a particular scientific problem, where the problem's nature determines the kind of intellectual integration required. (shrink)

The incredible achievements of modern scientific theories lead most of us to embrace scientific realism: the view that our best theories offer us at least roughly accurate descriptions of otherwise inaccessible parts of the world like genes, atoms, and the big bang. In Exceeding Our Grasp, Stanford argues that careful attention to the history of scientific investigation invites a challenge to this view that is not well represented in contemporary debates about the nature of the scientific enterprise. The historical record (...) of scientific inquiry, Stanford suggests, is characterized by what he calls the problem of unconceived alternatives. Past scientists have routinely failed even to conceive of alternatives to their own theories and lines of theoretical investigation, alternatives that were both well-confirmed by the evidence available at the time and sufficiently serious as to be ultimately accepted by later scientific communities. Stanford supports this claim with a detailed investigation of the mid-to-late 19th century theories of inheritance and generation proposed in turn by Charles Darwin, Francis Galton, and August Weismann. He goes on to argue that this historical pattern strongly suggests that there are equally well-confirmed and scientifically serious alternatives to our own best theories that remain currently unconceived. Moreover, this challenge is more serious than those rooted in either the so-called pessimistic induction or the underdetermination of theories by evidence, in part because existing realist responses to these latter challenges offer no relief from the problem of unconceived alternatives itself. Stanford concludes by investigating what positive account of the spectacularly successful edifice of modern theoretical science remains open to us if we accept that our best scientific theories are powerful conceptual tools for accomplishing our practical goals, but abandon the view that the descriptions of the world around us that they offer are therefore even probably or approximately true. (shrink)

Thomas S. Kuhn's classic book is now available with a new index.

Material traces of the past are notoriously inscrutable; they rarely speak with one voice, and what they say is never unmediated. They stand as evidence only given a rich scaffolding of interpretation which is, itself, always open to challenge and revision. And yet archaeological evidence has dramatically expanded what we know of the cultural past, sometimes demonstrating a striking capacity to disrupt settled assumptions. The questions we address in Evidential Reasoning are: How are these successes realized? What gives us confidence (...) in the credibility and robustness, the trustworthiness, of the evidential claims based on archaeological data? And, what constitute best practices in building evidential claims, critically scrutinizing them and putting them to work in archaeological contexts? Rather than retreat to abstractions about how how science operates in the ideal, we approach this question by interrogating a number of close-to-the-ground case studies with the aim of teasing out the wisdom embodied in archaeological practice. The cases we consider – of fieldwork, strategies for working with old evidence, and the role of external resources – illuminate the role of various types of inferential scaffolding and bring into focus practice-grounded epistemic norms that we believe serve archaeologists better than the all-or-nothing ideals of truth and objectivity that dominate programmatic debate. (shrink)

As a working hypothesis for philosophy of science, the unity of science thesis has been decisively challenged in all its standard formulations; it cannot be assumed that the sciences presuppose an orderly world, that they are united by the goal of systematically describing and explaining this order, or that they rely on distinctively scientific methodologies which, properly applied, produce domain-specific results that converge on a single coherent and comprehensive system of knowledge. I first delineate the scope of arguments against global (...) unity theses. However implausible old-style global unity theses may now seem, I argue that unifying strategies of a more local and contingent nature do play an important role in scientific inquiry. This is particularly clear in archaeology where, to establish evidential claims of any kind, practitioners must exploit a range of inter-field and inter-theory connections. At the same time, the robustness of these evidential claims depends on significant disunity between the sciences from which archaeologists draw background assumptions and auxiliary hypotheses. This juxtaposition of unity with disunity poses a challenge to standard positions in the debate about scientific unity. (shrink)

In July, 1939, a celebration was held at Leland Stanford University to commemorate the hundredth anniversary of the discovery that the cell is the basic unit of all living tissue. Today we are beginning to realize and to appreciate the fact that the symbol is the basic unit of all human behavior and civilization.

Until relatively recently, it was often supposed that changes in the material record of hominin life indexed advances in hominin cognitive sophistication in a relatively direct way. In particular, the “Upper Paleolithic Transition”—an apparently abrupt increase in the complexity and disparity of our material culture—was thought to signal the arrival of the fully human mind. While the idea of a direct relationship between material complexity and cognitive sophistication still has some defenders, this view has largely been abandoned. It is now (...) widely appreciated that aspects of ancient hominins’ demographic and social organization have a powerful influence both on the material culture they need and the material culture they can sustain. But if this more nuanced view is right, what does the deep material record tell us about the evolution of hominin cognition? I explore that question in this article. (shrink)

Scientific realists have suggested that changes in our scientific communities over the course of their history have rendered those communities progressively less vulnerable to the problem of unconcieved alternatives over time. I argue in response not only that the most fundamental historical transformations of the scientific enterprise have generated steadily mounting obstacles to revolutionary, transformative, or unorthodox scientific theorizing, but also that we have substantial independent evidence that the institutional apparatus of contemporary scientific inquiry fosters an exceedingly and increasingly theoretically (...) conservative form of that inquiry. I conclude that contemporary scientific communities are actually more vulnerable to the problem of unconceived alternatives than their historical predecessors, and I briefly suggest how we might seek to pursue scientific inquiry in a less theoretically conservative way. (shrink)

Scientific realists have suggested that changes in our scientific communities over the course of their history have rendered those communities progressively less vulnerable to the problem of unconcieved alternatives over time. I argue in response not only that the most fundamental historical transformations of the scientific enterprise have generated steadily mounting obstacles to revolutionary, transformative, or unorthodox scientific theorizing, but also that we have substantial independent evidence that the institutional apparatus of contemporary scientific inquiry fosters an exceedingly and increasingly theoretically (...) conservative form of that inquiry. I conclude that contemporary scientific communities are actually more vulnerable to the problem of unconceived alternatives than their historical predecessors, and I briefly suggest how we might seek to pursue scientific inquiry in a less theoretically conservative way. (shrink)

Currie (2019) has introduced a novel account of creativity within the social epistemology of science. The account is intended to capture how conservatism can be detrimental to the health of inquiry within certain scientific communities, given the aims of research there. I argue that recent remarks by Rovelli (2018) put pressure on the applicability of the account. Altogether, it seems we do not yet well understand the relationship between creativity, conservatism, and the health of inquiry in science.

The value of optimality modeling has long been a source of contention amongst population biologists. Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on external sources of confirmation. Optimality models are not alone in facing this tension between their explanatory value and their dependence on other approaches; I suspect that the scenario is quite common in science. This investigation of the optimality approach thus serves as a case (...) study, on the basis of which I suggest that there is a widely felt tension in science between explanatory independence and broad epistemic interdependence, and that this tension influences scientific methodology. (shrink)

This paper examines the inferential framework employed by Palaeolithic cognitive archaeologists, using the work of Wynn and Coolidge as a case study. I begin by distinguishing minimal-capacity inferences from cognitive-transition inferences. Minimal-capacity inferences attempt to infer the cognitive prerequisites required for the production of a technology. Cognitive-transition inferences use transitions in technological complexity to infer transitions in cognitive evolution. I argue that cognitive archaeology has typically used cognitive-transition inferences informed by minimal-capacity inferences, and that this reflects a tendency to favour (...) cognitive explanations for transitions in technological complexity. Next I look at two alternative explanations for transitions in technological complexity: the demographic hypothesis and the environmental hypothesis. This presents us with a dilemma: either reject these alternative explanations or reject traditional cognitive-transition inferences. Rejecting the former is unappealing as there is strong evidence that demographic and environmental influences play some causal role in technological transitions. Rejecting the latter is unappealing as it means abandoning the idea that technological transitions tell us anything about transitions in hominin cognitive evolution. I finish by briefly outlining some conceptual tools from the philosophical literature that might help shed some light on the problem. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

It is a common complaint that antireductionist arguments are primarily negative. Here I describe an alternative nonreductionist epistemology based on considerations taken from multidisciplinary research in biology. The core of this framework consists in seeing investigation as coordinated around sets of problems (problem agendas) that have associated criteria of explanatory adequacy. These ideas are developed in a case study, the explanation of evolutionary innovations and novelties, which demonstrates the applicability and fruitfulness of this nonreductionist epistemological perspective. This account also bears (...) on questions of conceptual change and theory structure in philosophy of science. †To contact the author, please write to: Department of Philosophy, University of Minnesota, 831 Heller Hall, 271 19th Ave. S., Minneapolis, MN 55455; e‐mail: [email protected]. (shrink)

According to a causal model of explanation, we explain phenomena by giving their causes or, where the phenomena are themselves causal regularities, we explain them by giving a mechanism linking cause and effect. If we explain why smoking causes cancer, we do not give the cause of this causal connection, but we do give the causal mechanism that makes it. The claim that to explain is to give a cause is not only natural and plausible, but it also avoids many (...) of the objections to other accounts of explanation, such as the views that to explain is to give a reason to believe the phenomenon occurred, to somehow make the phenomenon familiar, or to give a Deductive-Nomological argument. Unlike the reason for belief account, a causal model makes a clear distinction between understanding why a phenomenon occurs and merely knowing that it does, and the model does so in a way that makes understanding unmysterious and objective. Understanding is not some sort of super-knowledge, but simply more knowledge: knowledge of the phenomenon and knowledge of its causal history. A causal model makes it clear how something can explain without itself being explained, and so avoids the regress of whys, since we can know a phenomenon's cause without knowing the cause of the cause. It also accounts for legitimate self-evidencing explanations, explanations where the phenomenon is an essential part of the evidence that the explanation is correct, so the explanation can not supply a non-circular reason for believing the phenomenon occurred. There is no barrier to knowing a cause through its effects and also knowing that it is their cause. The speed of recession of a star explains its observed red-shift, even though the shift is an essential part of the evidence for its speed of recession. The model also avoids the most serious objection to the familiarity view, which is that some phenomena are familiar yet not understood, since a phenomenon can be perfectly familiar, such as the blueness of the sky or the fact that the same side of the moon always faces the earth, even if we do not know its cause. Finally, a causal model avoids many of the objections to the Deductive-Nomological model. Ordinary explanations do not have to meet the requirements of the Deductive-Nomological model, because one does not need to give a law to give a cause, and one does not need to know a law to have good reason to believe that a cause is a cause. As for the notorious over-permissiveness of the Deductive-Nomological model, the reason recession explains red-shift but not conversely, is simply that causes explain effects but not conversely, and the reason a conjunction of laws does not explain its conjuncts is that conjunctions do not cause their conjuncts. (shrink)

Cognitive archaeologists attempt to infer the cognitive and cultural features of past hominins and their societies from the material record. This task faces the problem of _minimum necessary competence_: as the most sophisticated thinking of ancient hominins may have been in domains that leave no archaeological signature, it is safest to assume that tool production and use reflects only the lower boundary of cognitive capacities. Cognitive archaeology involves selecting a model from the cognitive sciences and then assessing some aspect of (...) the material record through that lens. We give examples to show that background theoretical commitments in cognitive science that inform those models lead to different minimum necessary competence results. This raises an important question: what principles should guide us in selecting a model from the cognitive sciences? We outline two complementary responses to this question. The first involves using _independent_ lines of evidence to converge on a particular capacity. This can then influence model choice. The second is a broader suggestion. Theoretical diversity is a good thing in science, but is only beneficial over a limited amount of time. According to recent modelling work, one way of limiting diversity is to introduce extreme priors. We argue that having a broad spectrum of views in the philosophy of cognitive science may actually help cognitive archaeologists address the problem of minimum necessary competence. (shrink)

Explanation is a perennially hot topic in philosophy of science. Yet philosophers have exhibited a curious blind spot to the questions of how explanatory projects develop over time, as well as what processes are involved in generating their developmental trajectories. This paper examines these questions using research into the end-Permian mass extinction as a case study. It takes as its jumping-off point the observation that explanations of historical events tend to grow more complex over time, but it goes beyond this (...) observation by scrutinizing the processes responsible for generating this pattern. Surveying several decades of research into the end-Permian extinction, I suggest that the principal “driver” of explanation in geohistory is non-explanatory work: work that is undertaken to increase our descriptive understanding of a phenomenon, not to test a particular explanatory claim. Non-explanatory work drives explanation by imposing or eliminating demands on explanation, and by furnishing new resources for constructing explanatory models. Explanations grow more complex because the demands on explanation tend to increase with ongoing characterization of the target phenomenon, and characterization tends grows the roster of explanatory resources. However, the fact that non-explanatory work sometimes eliminates demands on explanation means that this trend is not irreversible. I suggest that to achieve a more rounded view of the dynamics of explanation, philosophers should ask how research into complex phenomena is organized, as well as how explanatory progress depends upon the coordination of different kinds of material and epistemic resources. (shrink)

This book exhibits deep philosophical quandaries and intricacies of the historical development of science lying behind a simple and fundamental item of common sense in modern science, namely the composition of water as H2O. Three main phases of development are critically re-examined, covering the historical period from the 1760s to the 1860s: the Chemical Revolution, early electrochemistry, and early atomic chemistry. In each case, the author concludes that the empirical evidence available at the time was not decisive in settling the (...) central debates and therefore the consensus that was reached was unjustified or at least premature. This leads to a significant re-examination of the realism question in the philosophy of science and a unique new advocacy for pluralism in science. Each chapter contains three layers, allowing readers to follow various parts of the book at their chosen level of depth and detail. The second major study in "complementary science", this book offers a rare combination of philosophy, history and science in a bid to improve scientific knowledge through history and philosophy of science. (shrink)

This fine collection of essays by a leading philosopher of science presents a defence of integrative pluralism as the best description for the complexity of scientific inquiry today. The tendency of some scientists to unify science by reducing all theories to a few fundamental laws of the most basic particles that populate our universe is ill-suited to the biological sciences, which study multi-component, multi-level, evolved complex systems. This integrative pluralism is the most efficient way to understand the different and complex (...) processes - historical and interactive - that generate biological phenomena. This book will be of interest to students and professionals in the philosophy of science. (shrink)

Demography plays a large role in cultural evolution through its effects on the effective rate of innovation. If we assume that useful inventions are rare, then small isolated societies will have low rates of invention. In small populations, complex technology will tend to be lost as a result of random loss or incomplete transmission (the Tasmanian effect). Large populations have more inventors and are more resistant to loss by chance. If human populations can grow freely, then a population-technology-population positive feedback (...) should occur such that human societies reach a stable growth path on which the rate of growth of technology is limited by the rate of invention. This scenario fits the Holocene to a first approximation, but the late Pleistocene is a great puzzle. Large-brained hominins existed in Africa and west Eurasia for perhaps 50,000 years with, at best, slow rates of technical innovation. The most sophisticated societies of the last glacial period appear after 50,000 years ago and were apparently restricted to west and north-central Eurasia and North Africa. These patterns have no simple, commonly accepted explanation. We argue that increased high-frequency climate change around 70,000–50,000 years ago may have tipped the balance between humans and their competitor-predators, such as lions and wolves, in favor of humans. At the same time, technically sophisticated hunters would tend to overharvest their prey. Perhaps the ephemeral appearance of complex tools and symbolic artifacts in Africa after 00,000 years ago resulted from hunting inventions that allowed human populations to expand temporarily before prey overexploitation led to human population and technology collapse. Sustained human populations of moderate size using distinctively advanced Upper Paleolithic artifacts may have existed in west Eurasia because cold, continental northeastern Eurasia–Beringia acted as a protected reserve for prey populations. (shrink)