Research on animal behavior is typically organized according to a combination of two influential frameworks: Ernst Mayr’s distinction between proximate and ultimate causes, and Niko Tinbergen’s “four questions”. My aim is to debunk two common interpretive misconceptions about Mayr’s proximate–ultimate distinction and its relationship to Tinbergen’s four questions, and to offer a new interpretation that avoids both. The first misconception is that the proximate–ultimate distinction maps cleanly onto Tinbergen’s four questions, marking a boundary between Tinbergen’s evolutionary and survival value questions (...) versus developmental and mechanistic questions. The second is that Mayr’s proximate–ultimate distinction is meant to rule out the relevance of proximate causes to evolutionary explanations. I argue that neither is plausible given the text and Mayr’s philosophical aims, namely, to argue that evolutionary biology cannot be reduced to either the physical sciences or to other areas of biology. Through a reconstruction of Mayr’s anti-reductionist argument, I develop an interpretation according to which the proximate–ultimate distinction marks two ways that teleological reasoning can be naturalistically grounded in biology, corresponding to Mayr’s distinction between teleonomic and adapted systems. Mayr distinguishes reduction, which the proximate–ultimate distinction is meant to block, from analysis, through which he allows that proximate causes, causes that are neither proximate nor ultimate, and chance can all contribute to evolutionary explanations. I conclude by suggesting some ways in which the interpretation defended here reframes our understanding of Mayr’s disagreements with some evolutionary-developmental biologists. (shrink)

Research on animal behavior is typically organized according to a combination of two influential frameworks: Ernst Mayr’s distinction between proximate and ultimate causes, and Niko Tinbergen’s “four questions”. My aim is to debunk two common interpretive misconceptions about Mayr’s proximate–ultimate distinction and its relationship to Tinbergen’s four questions, and to offer a new interpretation that avoids both. The first misconception is that the proximate–ultimate distinction maps cleanly onto Tinbergen’s four questions, marking a boundary between Tinbergen’s evolutionary and survival value questions (...) versus developmental and mechanistic questions. The second is that Mayr’s proximate–ultimate distinction is meant to rule out the relevance of proximate causes to evolutionary explanations. I argue that neither is plausible given the text and Mayr’s philosophical aims, namely, to argue that evolutionary biology cannot be reduced to either the physical sciences or to other areas of biology. Through a reconstruction of Mayr’s anti-reductionist argument, I develop an interpretation according to which the proximate–ultimate distinction marks two ways that teleological reasoning can be naturalistically grounded in biology, corresponding to Mayr’s distinction between teleonomic and adapted systems. Mayr distinguishes reduction, which the proximate–ultimate distinction is meant to block, from analysis, through which he allows that proximate causes, causes that are neither proximate nor ultimate, and chance can all contribute to evolutionary explanations. I conclude by suggesting some ways in which the interpretation defended here reframes our understanding of Mayr’s disagreements with some evolutionary-developmental biologists. (shrink)

It is commonly assumed that the concept of mechanism is a keytool for the scientific understanding of observable phenomena. However, there is no single definition of mechanism in the current philosophy of science. In fact, philosophers have developed several characterizations of what seemed to be a clear intuitive concept for scientists. In this paper, I will analyze these philosophical conceptions of mechanism, highlighting their problematic aspects and proposing a new mechanistic approach based on the idea that the pertinent levels of (...) organization for a mechanistic explanation can be identified with intervals of quasi-decompositionality. I argue that this approach allows us to consider that activities are directly derived from the entities’ structure. Consequently, a mechanistic explanation implies an arbitrary but not capricious choice of an organizational level. According to this approach, inter-level causation is merely apparent and there is no place for emergent properties. (shrink)

The terms “perspectivism” and “perspectivalism” have been the focus of an intense philosophical discussion with important repercussions for the debate about the role of mechanisms in scientific explanations. However, leading exponents of the new mechanistic philosophy have conceded more than was necessary to the radically subjectivistic perspectivalism, and fell into the opposite error, by retaining not negligible residues of objectivistic views about mechanisms. In order to remove this vacillation between the subjective-cultural and the objective-natural sides of mechanisms, we shall raise (...) the question about theory-ladenness over again and interpret it in its connection with the technical–experimental nature of scientific knowledge, as affirming the perspectival character of scientific knowledge: It is because of the character at once theory-laden and practice-laden, i.e. technique-laden, of our putting questions to nature that empirical reality must be investigated from particular perspectives: nature can be known scientifically only from a potentially infinite number of perspectives or theoretical points of view, concretely exemplified by mechanisms or experimental ‘machines’ that allow specific access to specific aspects of sensible reality. (shrink)

One of the central tasks for naturalistic theories of representation is to say what it takes for something to be a representation, and some leading theories have been criticised for being too liberal. Prominent discussions of this problem have proposed a producer-oriented solution; it is argued that representations must be produced by systems employing perceptual constancy mechanisms. However, representations may be produced by simple transducers if they are consumed in the right way. It is characteristic of representations to be consumed (...) by systems which are capable of independent action. This paper defends this claim; discusses more precise, naturalistic formulations; and shows how it can illuminate the explanatory payoffs which science achieves by appealing to representation. (shrink)

Nowadays, philosophers and scientists tend to agree that, even though human and artificial intelligence work quite differently, they can still illuminate aspects of each other, and knowledge in one domain can inspire progress in the other. For instance, the notion of “artificial” or “synthetic” phenomenology has been gaining some traction in recent AI research. In this paper, we ask the question: what (if anything) is the use of thinking about phenomenology in the context of AI, and in particular machine learning? (...) We will isolate one sense of “phenomenology”, namely the sense in which it is commonly understood within analytic philosophy of perception. Then, we will give examples of projects within sensory substitution and restoration science that rely heavily on machine learning and to which, according to us, phenomenology in the sense specified makes a relevant contribution. Finally, we will shed some light on what this contribution looks like and why it is important. (shrink)

The Hard Question of memory is the following: how are memory representations stored and organized so as to be made available for retrieval in the appropriate circumstances and format? In this essay, I argue that philosophical theories of memory should engage with the Hard Question directly and seriously. I propose that declarative memory is a faculty performing a kind of cognitive triage: management of information for a variety of uses under significant computational constraints. In such triage, memory representations are preferentially (...) selected and stabilized, but also systematically modified and integrated into generalized, model-like representational structures. Further, I propose a hybrid theory of remembering, which takes into account both the nature of the cognitive processes underlying remembering and the norms that govern representational success in relevant cognitive/epistemic contexts. (shrink)

Debates about causation have dominated recent philosophy of memory. While causal theorists have argued that an appropriate causal connection to a past experience is necessary for remembering, their opponents have argued that this necessity condition needs to be relaxed. Recently, Jordi Fernández has attempted to provide such a relaxation. On his functionalist theory of remembering, a given state need not be caused by a past experience to qualify as a memory; it only has to realize the relevant functional role in (...) the subject’s mental economy. In this comment, I argue that Fernández’s theory doesn’t advance the debate about memory causation. I propose that this debate is best understood as being about the existence of systems, which support kinds of interactions that map onto the relations dictated by theories. Since Fernández’s functionalism tells us very little about this empirical question, the theoretical gains from endorsing it are minimal. (shrink)

How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences.

Multiple realizability (MR) is traditionally conceived of as the feature of computational systems, and has been used to argue for irreducibility of higher-level theories. I will show that there are several ways a computational system may be seen to display MR. These ways correspond to (at least) five ways one can conceive of the function of the physical computational system. However, they do not match common intuitions about MR. I show that MR is deeply interest-related, and for this reason, difficult (...) to pin down exactly. I claim that MR is of little importance for defending computationalism, and argue that it should rather appeal to organizational invariance or substrate neutrality of computation, which are much more intuitive but cannot support strong antireductionist arguments. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.

In this paper, I argue that what counts as the proper function of a trait is a matter of the de facto perspective that the biological system, itself, possesses on what counts as proper functioning for that trait. Unlike non-perspectival accounts, internal perspectivalism does not succumb to generality problems. But unlike external perspectivalism, internal perspectivalism can provide a fully naturalistic, mind-independent grounding of proper function and natural norms. The attribution of perspectives to biological systems is intended to be neither metaphorical (...) nor anthropomorphic: I do not mean to imply that such systems thereby must possess agency, cognition, intentions, concepts, or mental or psychological states. Instead, such systems provide the grounding for norms of performance when they internally enforce their own standard of (i.e., their own perspective on) what constitutes proper functioning or malfunctioning. By operating with a fixed, determinate level of generality, such systems provide the basis for an account of proper function that is immune to generality problems. (shrink)

Building on self-professed perspectival approaches to both scientific knowledge and causation, I explore the potentially radical suggestion that perspectivalism can be extended to account for a type of objectivity in science. Motivated by recent claims from quantum foundations that quantum mechanics must admit the possibility of observer-dependent facts, I develop the notion of ‘perspectival objectivity’, and suggest that an easier pill to swallow, philosophically speaking, than observer-dependency is perspective-dependency, allowing for a notion of observer-independence indexed to an agent perspective. Working (...) through the case studies of colour perception and causal perspectivalism, I identify two places within which I claim perspectival objectivity is already employed, and make the connection to quantum mechanics through Bohr’s philosophy of quantum theory. I contend that perspectival objectivity can ensure, despite the possibility of perspective-dependent scientific facts, the objectivity of scientific inquiry. (shrink)

Computational perspectivalism has been recently proposed as an alternative to mainstream accounts of physical computation, and especially to the teleologically-based mechanistic view. It takes physical computation to be partly dependent on explanatory perspectives and eschews appeal to teleology in helping individuate computational systems. I assess several varieties of computational perspectivalism, showing that they either collapse into existing non-perspectival views or end up with unsatisfactory or implausible accounts of physical computation. Computational perspectivalism fails, therefore, to be a compelling alternative to perspective-independent (...) theories of computation in physical systems. I conclude that a teleologically-based, non-perspectival mechanistic account of physical computation is to be preferred. 1Introduction 2The Mechanistic View of Computation 2.1Teleological functions and meeting the desiderata 3Varieties of Perspectivalism 4Computational Perspectivalism 4.1Computational perspectivalism and pancomputationalism 4.2Computational perspectivalism and miscomputation 5The Varieties of Computational Perspectivalism Assessed 5.1Innocuous computational perspectivalism 5.2Non-innocuous computational perspectivalism 5.2.1Computational instrumentalism 5.2.2Ontic perspectivalism 6Concluding Remarks. (shrink)

Any successful account of the metaphysics of mechanistic causation must satisfy at least five key desiderata. In this article, I lay out these five desiderata and explain why existing accounts of the metaphysics of mechanistic causation fail to satisfy them. I then present an alternative account that does satisfy the five desiderata. According to this alternative account, we must resort to a type of ontological entity that is new to metaphysics, but not to science: constraints. In this article, I explain (...) how a constraints-based metaphysics fits best with the emerging consensus on the nature of mechanistic explanation. 1Introduction2Renormalizability2.1The first two desiderata: Intrinsicness and productivity2.2The third desideratum: Scientific validity or non-mysteriousness2.3The fourth desideratum: Directionality2.4The fifth desideratum: Perspectival nature of mechanisms3Constraints and Causation3.1Multi-perspectival realism and causal structure3.2Causal structure as laws3.3Causal structures in analytical mechanics: Constraints3.4A metaphysics inspired by analytical mechanics: Constraints as ontologically primitive modal structures4Constraints and Mechanistic Causal Powers 4.1Inter- versus intra-perspectival categories4.2Mechanistic causal powers are grounded by constraints4.3Intrinsicness and constraints4.4Constraints and productiveness4.5Constraints and directionality5Conclusion. (shrink)

Recent years have seen a surge of interest in applying mechanistic thinking to computational accounts of implementation and individuation. One recent extension of this work involves so-called ‘wide’ approaches to computation, the view that computational processes spread out beyond the boundaries of the individual. These ‘mechanistic accounts of wide computation’ maintain that computational processes are wide in virtue of being part of mechanisms that extend beyond the boundary of the individual. This paper aims to further develop the mechanistic account of (...) wide computationalism by responding to two outstanding worries, what are called the parsimony and testability challenges. The first is based on considerations about wide computation’s ontological cost; the second the view’s experimental testability. The argument is that wide mechanistic computationalism can gain the necessary conceptual resources to address the challenges by embracing two further aspects of the mechanistic approach: i) the structural aspect of mechanistic explanation and ii) the notion of constitutive relevance. (shrink)

Teleological terms such as "function" and "design" appear frequently in the biological sciences. Examples of teleological claims include: A (biological) function of stotting by antelopes is to communicate to predators that they have been detected. Eagles' wings are (naturally) designed for soaring. Teleological notions were commonly associated with the pre-Darwinian view that the biological realm provides evidence of conscious design by a supernatural creator. Even after creationist viewpoints were rejected by most biologists there remained various grounds for concern about the (...) role of teleology in biology, including whether such terms are: 1. vitalistic (positing some special "life-force"); 2. requiring backwards causation (because future outcomes explain present traits); 3. incompatible with mechanistic explanation (because of 1 and 2); 4. mentalistic (attributing the action of mind where there is none); 5. empirically untestable (for all the above reasons). Opinions divide over whether Darwin's theory of evolution provides a means of eliminating teleology from biology, or whether it provides a naturalistic account of the role of teleological notions in the science. Many contemporary biologists and philosophers of biology believe that teleological notions are a distinctive and ineliminable feature of biological explanations but that it is possible to provide a naturalistic account of their role that avoids the concerns above. Terminological issues sometimes serve to obscure some widely-accepted distinctions. (shrink)

The crucial problem in the philosophy of psychiatry is to determine under which conditions certain behaviors, mental states, and personality traits should be regarded as symptoms of mental illnesses. Participants in the debate can be placed on a continuum of positions. On the one side of the continuum, there are naturalists who maintain that the concept of mental illness can be explained by relying on the conceptual apparatus of the natural sciences, such as biology and neuroscience. On the other side (...) of the continuum, there are normativists who maintain that the appropriate characterization of the concept of mental illness cannot avoid reference to epistemic, moral and other social values. Although, this article is primarily an introduction to the debate, we stress the importance of the normativist positions. (shrink)

In this paper, I discuss the question whether objective criteria could be provided for judging something to be a mental illness. I consider the two most prominent objectivist or naturalistic accounts of mental illness, evolutionary and bio-statistical account, which offer such a criterion by relying on the notion of biological function. According to such suggestions, illness is a condition in which there is dysfunciton in some feature of an organism. In this context, I consider different accounts for ascribing functions in (...) biologyand their relationship with the suggested accounts of illnesses. Special focus is placed on the objections according to which the ascription of functions, as envisaged in naturalistic accounts of illness, is incompatible with actual medical and psychiatric practice. I conclude that these objections are legitimate insofar we want to an account of illness that preserves the current practice of ascribing illness. However, the question remains, could a theory that tries to capture the actual medical practice be value-neutral, since our ordinary conception of illness is permeated with value judgments that indirectly enter into medical practice. In that respect, it seems that the requirement for pure objectivity is too strong and thus, it is not reasonable to expect that naturalistic accounts can satisfy it. (shrink)

This chapter subsumes David Marr’s levels of analysis account of explanation in cognitive science under the framework of mechanistic explanation: Answering the questions that define each one of Marr’s three levels is tantamount to describing the component parts and operations of mechanisms, as well as their organization, behavior, and environmental context. By explicating these questions and showing how they are answered in several different cognitive science research programs, this chapter resolves some of the ambiguities that remain in Marr’s account, and (...) shows that many different areas and traditions of cognitive scientific research can be unified under the mechanistic framework. (shrink)

This article presents a distinct sense of ‘mechanism’, which I call the functional sense of mechanism. According to this sense, mechanisms serve functions, and this fact places substantive restrictions on the kinds of system activities ‘for which’ there can be a mechanism. On this view, there are no mechanisms for pathology; pathologies result from disrupting mechanisms for functions. Second, on this sense, natural selection is probably not a mechanism for evolution because it does not serve a function. After distinguishing this (...) sense fromsimilar explications of ‘mechanism’, I argue that it is ubiquitous in biology and has valuable epistemic benefits. (shrink)

I examine a major objection to the mechanistic view of concrete computation, stemming from an apparent tension between the abstract nature of computational explanation and the tenets of the mechanistic framework: while computational explanation is medium-independent, the mechanistic framework insists on the importance of providing some degree of structural detail about the systems target of the explanation. I show that a common reply to the objection, i.e. that mechanistic explanation of computational systems involves only weak structural constraints, is not enough (...) to save the standard mechanistic view of computation—it trivialises the appeal to mechanism, and thus makes the account collapse into a purely functional view. I claim, however, that the objection can be put to rest once the account is appropriately amended: computational individuation is indeed functional, while mechanistic explanation plays a role in accounting for computational implementation. Since individuation and implementation are crucial elements in a satisfying account of computation in physical systems, mechanism keeps its central importance in the theory of concrete computation. Finally, I argue that my version of the mechanistic view helps to provide a convincing reply to a powerful objection against non-semantic theories of concrete computation: the argument from the multiplicity of computations. (shrink)

This paper considers the way mathematical and computational models are used in network neuroscience to deliver mechanistic explanations. Two case studies are considered: Recent work on klinotaxis by Caenorhabditis elegans, and a longstanding research effort on the network basis of schizophrenia in humans. These case studies illustrate the various ways in which network, simulation and dynamical models contribute to the aim of representing and understanding network mechanisms in the brain, and thus, of delivering mechanistic explanations. After outlining this mechanistic construal (...) of network neuroscience, two concerns are addressed. In response to the concern that functional network models are non-explanatory, it is argued that functional network models are in fact explanatory mechanism sketches. In response to the concern that models which emphasize a network’s organization over its composition do not explain mechanistically, it is argued that this emphasis is both appropriate and consistent with the principles of mechanistic explanation. What emerges is an improved understanding of the ways in which mathematical and computational models are deployed in network neuroscience, as well as an improved conception of mechanistic explanation in general. (shrink)

Some recent accounts of constitutive relevance have identified mechanism components with entities that are causal intermediaries between the input and output of a mechanism. I argue that on such accounts there is no distinctive inter-level form of mechanistic explanation and that this highlights an absence in the literature of a compelling argument that there are such explanations. Nevertheless, the entities that these accounts call ‘components’ do play an explanatory role. Studying causal intermediaries linking variables Xand Y provides knowledge of the (...) counterfactual conditions under which X will continue to bring about Y. This explanatory role does not depend on whether intermediate variables count as components. The question of whether there are distinctively mechanistic explanations remains open. (shrink)

In this paper we consider mechanistic explanations for biologic malfunctions. Drawing on Lipton’s work on difference making, we offer three reasons why one should distinguish i) mechanistic features that only make a difference to the malfunction one aims to explain, from ii) features that make a difference to both the malfunction and normal functioning. Recognition of the distinction is important for a) repair purposes, b) mechanism discovery, and c) understanding. This analysis extends current mechanistic thinking, which fails to appreciate the (...) distinction. We illustrate our contribution with a case on sleeping disorders as arising from disruptions of circadian rhythms. (shrink)

Social machines are a prominent focus of attention for those who work in the field of Web and Internet science. Although a number of online systems have been described as social machines, there is, as yet, little consensus as to the precise meaning of the term “social machine.” This presents a problem for the scientific study of social machines, especially when it comes to the provision of a theoretical framework that directs, informs, and explicates the scientific and engineering activities of (...) the social machine community. The present paper outlines an approach to understanding social machines that draws on recent work in the philosophy of science, especially work in so-called mechanical philosophy. This is what might be called a mechanistic view of social machines. According to this view, social machines are systems whose phenomena are explained via an appeal to socio-technical mechanisms. We show how this account is able to accommodate a number of existing attempts to define the social machine concept, thereby yielding an important opportunity for theoretical integration. (shrink)

Much contemporary debate on the nature of mechanisms centers on the issue of modulating negative causes. One type of negative causability, which I refer to as "causation by absence," appears difficult to incorporate into modern accounts of mechanistic explanation. This paper argues that a recent attempt to resolve this problem, proposed by Benjamin Barros, requires improvement as it overlooks the fact that not all absences qualify as sources of mechanism failure. I suggest that there are a number of additional types (...) of effects caused by absences that need to be incorporated to account for the diversity of causal connections in the biological sciences. Furthermore, it is argued that recognizing natural variability in mechanisms, such as attenuation, leads to some interesting line-drawing issues for contemporary philosophy of mechanisms. (shrink)

Mechanistic information is used in the field of risk assessment in order to clarify two controversial methodological issues, the selection of inference guides and the definition of standards of evidence. In this paper we present an analysis of the concept of mechanistic information in risk assessment by recurring to previous philosophical analyses of mechanistic explanation. Our conclusion is that the conceptual analysis of mechanistic explanation facilitates a better characterization of the concept of mechanistic information. However, it also shows that the (...) use of this kind of information in risk assessment is heavily influenced by pragmatic factors, which have not been sufficiently taken into account in philosophical analysis. Mechanistic models are like hypothesis that have to be validated empirically. Due to their dependence on the standards of evidence, they are subject to the same pragmatic factors. Therefore, recurring to mechanistic information does not lead to closure of the methodological controversies in risk assessment. (shrink)

The distinction between causal role and selected effect functions is typically framed in terms of their respective explanatory roles. However, much of the controversy over functions in genomics takes place in an investigative, not an explanatory context. Specifically, the process of component-driven functional investigation begins with the designation of some genetic or epigenetic element as functional —i.e. not junk— because it possesses properties that, arguably, suggest some biologically interesting organismal effect. The investigative process then proceeds, in a bottom-up fashion, to (...) search for those effects. I argue that this process encounters a problem reminiscent of one that Gould and Lewontin associated with the adaptationist program. Just as their stereotypical adaptationst became trapped in the myopic pursuit of one selectionist hypothesis after another, so can the investigation of CR functions in genomics lead to an unending series putative organism-level CR functions for junk DNA. This is an acute problem for genomics, because eukaryotic genomes are littered with transposable elements and their deactivated descendants which often masquerade as interesting CR-functional components and it is experimentally onerous to determine whether they lack such a function. I further argue that selectionist reasoning about TE-host coevolutionary dynamics can greatly streamline the investigative process. Importantly, selectionist hypotheses need not be well confirmed to be illuminating in this context. Informed selectionist reasoning about the strategic roles of TEs in the genome offers a corrective to the idea that most of our DNA is somehow CR functional for the organism. (shrink)

It is generally acknowledged by proponents of ‘new mechanism’ that mechanistic explanation involves adopting a perspective, but there is less agreement on how we should understand this perspective-taking or what its implications are for practising science. This paper examines the perspectival nature of mechanistic explanation through the lens of the ‘mechanistic stance’, which falls somewhere between Dennett’s more familiar physical and design stance. We argue this approach implies three distinct and significant ways in which mechanistic explanation can be interpreted as (...) perspectival: ‘phenomenon perspectivism’, ‘pattern perspectivism’ and ‘hierarchy perspectivism’. We evaluate the strength of the perspective-dependency implied by each of these, and along the way, discuss their significance for wider debates within the new mechanism literature, such as the nature of function attribution and an ontic vs epistemic understanding of explanation. (shrink)

A promising strategy for defending the role that representation plays in explanations of cognition frames the concept in terms of internal models or map‐like mechanisms. “Structural representation” offers an account of representation that is grounded in well‐specified, empirical criteria. However, anti‐representationalists continue to press the issue of how to account for the paradigmatic semantic properties of representation at the subpersonal level. In this paper, I offer an account of how the proponent of structural representation should think about content. There are (...) really two problems of content any account of representation must overcome: the “hard problem of content” and the “content determination problem.” I argue that the structural representation account has the resources to provide a naturalistically respectable notion of content that overcomes both problems. (shrink)

In recent years, the ‘mechanistic view’ has developed as a popular alternative to the ‘semantic view’ concerning the identity of physical computation. However, semanticists have provided powerful arguments that suggest the mechanistic view fails to deliver essential distinctions between paradigmatic computational operations. This article reviews responses on behalf of the mechanist and uses this opportunity to propose a type of pluralism about computational identity. This pluralism contends that there are multiple ‘levels’ of properties and relations pertaining to computation that can (...) inform different kinds of individuation. As such, for the pluralist, there are multiple legitimate ways of classifying computation, depending on the nature of the system in question, and one’s own epistemic priorities. (shrink)

Advocates of the New Mechanicism in philosophy of science argue that scientific explanation often consists in describing mechanisms responsible for natural phenomena. Despite its successes, one might think that this approach does not square with the ontological strictures of quantum mechanics. New Mechanists suppose that mechanisms are composed of objects with definite properties, which are interconnected via local causal interactions. Quantum mechanics calls these suppositions into question. Since mechanisms are hierarchical it appears that even macroscopic mechanisms must supervene on a (...) set of “objects” that behave non-classically. In this paper we argue, in part by appeal to the theory of quantum decoherence, that the universal validity of quantum mechanics does not undermine neo-mechanistic ontological and explanatory claims as they occur within in classical domains. Additionally, we argue that by relaxation of certain classical assumptions, mechanistic explanatory strategies can sometimes be carried over into the quantum domain. (shrink)

In this paper, I argue that the newly developed network approach in neuroscience and biology provides a basis for formulating a unique type of realization, which I call topological realization. Some of its features and its relation to one of the dominant paradigms of realization and explanation in sciences, i.e. the mechanistic one, are already being discussed in the literature. But the detailed features of topological realization, its explanatory power and its relation to another prominent view of realization, namely the (...) semantic one, have not yet been discussed. I argue that topological realization is distinct from mechanistic and semantic ones because the realization base in this framework is not based on local realisers, regardless of the scale but on global realizers. In mechanistic approach, the realization base is always at the local level, in both ontic and epistemic accounts. The explanatory power of realization relation in mechanistic approach comes directly from the realization relation-either by showing how a model is mapped onto a mechanism, or by describing some ontic relations that are explanatory in themselves. Similarly, the semantic approach requires that concepts at different scales logically satisfy microphysical descriptions, which are at the local level. In topological framework the realization base can be found at different scales, but whatever the scale the realization base is global, within that scale, and not local. Furthermore, topological realization enables us to answer the “why” questions, which according to Polger 2010 make it explanatory. The explanatoriness of topological realization stems from understanding mathematical consequences of different topologies, not from the mere fact that a system realizes them. (shrink)

In the last 20 years or so, since the publication of a seminal paper by Watts and Strogatz :440–442, 1998), an interest in topological explanations has spread like a wild fire over many areas of science, e.g. ecology, evolutionary biology, medicine, and cognitive neuroscience. The topological approach is still very young by all standards, and even within special sciences it still doesn’t have a single methodological programme that is applicable across all areas of science. That is why this special issue (...) is important as a first systematic philosophical study of topological explanations and their relation to a well understood and widespread explanatory strategy, such as mechanistic one. (shrink)

We provide three innovations to recent debates about whether topological or “network” explanations are a species of mechanistic explanation. First, we more precisely characterize the requirement that all topological explanations are mechanistic explanations and show scientific practice to belie such a requirement. Second, we provide an account that unifies mechanistic and non-mechanistic topological explanations, thereby enriching both the mechanist and autonomist programs by highlighting when and where topological explanations are mechanistic. Third, we defend this view against some powerful mechanist objections. (...) We conclude from this that topological explanations are autonomous from their mechanistic counterparts. (shrink)

This paper is aimed at identifying how a model’s explanatory power is constructed and identified, particularly in the practice of template-based modeling (Humphreys, Philos Sci 69:1–11, 2002; Extending ourselves: computational science, empiricism, and scientific method, 2004), and what kinds of explanations models constructed in this way can provide. In particular, this paper offers an account of non-causal structural explanation that forms an alternative to causal–mechanical accounts of model explanation that are currently popular in philosophy of biology and cognitive science. Clearly, (...) defences of non-causal explanation are far from new (e.g. Batterman, Br J Philos Sci 53:21–38, 2002a; The devil in the details: asymptotic reasoning in explanation, reduction, and emergence, 2002b; Pincock, Noûs 41:253–275, 2007; Mathematics and scientific representation 2012; Rice, Noûs. doi:10.1111/nous.12042, 2013; Biol Philos 27:685–703, 2012), so the targets here are focused on a particular type of robust phenomenon and how strong invariance to interventions can block a range of causal explanations. By focusing on a common form of model construction, the paper also ties functional or computational style explanations found in cognitive science and biology more firmly with explanatory practices across model-based science in general. (shrink)

The concept of scaffolding has wide resonance in several scientific fields. Here we attempt to adopt it for the study of development. In this perspective, the embryo is conceived as an integral whole, comprised of several hierarchical modules as in a recurrent circularity of emerging patterns. Within the developmental hierarchy, each module yields an inter-level relationship that makes it possible for the scaffolding to mediate the production of selectable variations. A wide range of genetic, cellular and morphological mechanisms allows the (...) scaffolding to integrate these modular variations into a functionally coordinate unit. A genetic scaffolding accounts for the inherited invariance of pattern formation during the embryo’s growth. At higher level, cells behave as agents endowed with the capacity to interpret any scaffolding variation as signs. The full hierarchy of a multi-level scaffolding is eventually attained when the embryo acquires the capacity to impose a number of developmental constraints on its constituting parts in a top-down direction. The acquisition of this capacity allows a semiotic threshold to emerge between the living cellular world and the underlying non-living molecular world. As this boundary is gradually defined during development, cells enter into new functional relationships, while, at the same time, are relieved from their physical determinism. The resulting constraints can thus become the driving forces that upgrade embryonic scaffolding from the simple molecular signalling to the complexity of sign recognition proper of a cellular community. In this semiotic perspective, the apparent goal directness of any developmental strategy should no longer be accounted for by a predetermined genetic program, but by the gradual definition of the relationships selected amongst the ones historically explored. (shrink)

Theories of function are conventionally divided up into historical and ahistorical ones. Proponents of ahistorical theories often cite the ahistoricity of their accounts as a major virtue. Here, I argue that none of the mainstream “ahistorical” accounts are actually ahistorical. All of them embed, implicitly or explicitly, an appeal to history. In Boorse’s goal-contribution account, history is latent in the idea of statistical-typicality. In the propensity theory, history is implicit in the idea of a species’ natural habitat. In the causal (...) role theory, history is required for making sense of dysfunction. I elaborate some consequences for the functions debate. (shrink)

Despite the voluminous literature on biological functions produced over the last 40 years, few philosophers have studied the concept of function as it is used in neuroscience. Recently, Craver (forthcoming; also see Craver 2001) defended the causal role theory against the selected effects theory as the most appropriate theory of function for neuroscience. The following argues that though neuroscientists do study causal role functions, the scope of that theory is not as universal as claimed. Despite the strong prima facie superiority (...) of the causal role theory, the selected effects theory (when properly developed) can handle many cases from neuroscience with equal facility. It argues this by presenting a new theory of function that generalizes the notion of a ‘selection process’ to include processes such as neural selection, antibody selection, and some forms of learning—that is, to include structures that have been differentially retained as well as those that have been differentially reproduced. This view, called the generalized selected effects theory of function, will be defended from criticism and distinguished from similar views in the literature. (shrink)

Mechanisms, in the prominent biological sense of the term, are historical entities. That is, whether or not something is a mechanism for something depends on its history. Put differently, while your spontaneously-generated molecule-for-molecule double has a heart, and its heart pumps blood around its body, its heart does not have a mechanism for pumping, since it does not have the right history. My argument for this claim is that mechanisms have proper functions; proper functions are historical entities; so, mechanisms are (...) historical entities, too. This thesis runs against the mainstream new mechanist way of thinking about mechanisms, where mechanisms are generally thought of in an ahistorical way. After arguing for this thesis, I draw out some consequences for philosophy of science and metaphysics. (shrink)

I distinguish two forms of pluralism about biological functions, between-discipline pluralism and within-discipline pluralism. Between-discipline pluralism holds that different theories of function are appropriate for different subdisciplines of biology and psychology. I provide reasons for rejecting this view. Instead, I recommend within-discipline pluralism, which emphasizes the plurality of function concepts at play within any given subdiscipline of biology and psychology.

Ovaj je zbornik nastao kao rezultat istraživanja provedenog unutar istoimenoga znanstveno-istraživačkoga projekta na kojemu su urednici istovremeno bili i glavni istraživači, a ostali autori članovi istraživačke skupine. Kao svjedoci različitih vrsta otklona od prevladavajućeg, uobičajenoga, normalnoga, pozitivnog ili ponašanja koje se karakterizira kao asocijalno, zapitali smo se – što postojeće čini normom, treba li odstupanje od norme nužno smatrati devijacijom i kakvi su poželjni društveni odgovori na odstupanja od normi. Često se smatra ispravnim upravo ono što je prevladavajuće, a ono (...) što predstavlja otklon označava se kao devijacija u negativnome značenju onoga što nije ispravno, nije posve ispravno, ili čak onoga što treba sankcionirati. Naš je početni stav bio da ono što prevladava ne smije biti neupitna norma, kao što ni ono što je otklon nije po automatizmu devijacija. Međutim, ne smatramo ni da prevladavajuću normu, samom tom činjenicom što je prevladavajuća, nužno treba kritizirati te da je svaki otklon po sebi poželjan. Cilj našeg istraživanja bio je istražiti različite oblike deficita i devijacijau u domeni formiranja vjerovanja individualnih, grupnih, kolektivnih i institucijskih epistemičkih aktera (socijalna epistemologija) i u domeni društvenog i institucijskoga djelovanja (filozofija politike i filozofija psihijatrije). Nastavno na to, pokušali smo identificirati vrijednosti postojećih normi, koliko odgovaraju poželjnim vrijednostima te koji su poželjni društveni odgovori na otklone od normi. (shrink)

The central task of cognitive neuroscience to map cognitive capacities to neural mechanisms faces three interlocking conceptual problems that together frame the problem of cognitive ontology. First, they must establish which tasks elicit which cognitive capacities, and specifically when different tasks elicit the same capacity. To address this operationalization problem, scientists often assess whether the tasks engage the same neural mechanisms. But to determine whether mechanisms are of the same or different kinds, we need to solve the abstraction problem by (...) determining which mechanistic differences are and are not relevant, and also the boundary problem by distinguishing the mechanism from its background conditions. Solving these problems, in turn, requires understanding how cognitive capacities are elicited in tasks. These three problems, which have been noted and discussed elsewhere in the literature, together form a ‘cycle of kinds’ that frames the central problem-space of cognitive ontology. We describe this cycle to clarify the intellectual challenges facing the cognitive ontologist and to reveal the kind of iterative process by which ontological revision in cognitive neuroscience is likely to unfold. (shrink)

It is widely assumed that mechanistic explanations are causal explanations. Many prominent new mechanists endorse interventionism as the correct analysis of explanatory causal models in biology and other fields. This article argues that interventionism is not entirely satisfactory in this regard. A case study of Jacob and Monod’s operon model shows that at least some important mechanistic explanations in biology present significant contrasts with the interventionist account. This result motivates a more inclusive approach to mechanistic explanation, allowing for noncausal aspects.

Mechanism realists assert the existence of mechanisms as objective structures in the world, but their exact metaphysical commitments are unclear. We introduce Local Hierarchy Realism (LHR) as a substantive and plausible form of mechanism realism. The limits of LHR reveal a deep tension between two aspects of mechanists’ explanatory strategy. Functional decomposition identifies locally relevant entities and activities, while these same entities and activities are also embedded in a nested hierarchy of levels. In principle, a functional decomposition may identify entities (...) engaging in causal interactions that crosscut the hierarchical structure of composition relations, violating the mechanist’s injunction against interlevel causation. We argue that this possibility is realized in the example of ephaptic coupling, a subsidiary process of neural computation that crosscuts the hierarchy derived from synaptic transmission. These considerations undermine the plausibility of LHR as a general view, yet LHR has the advantages that (i) its metaphysical implications are precisely stateable; (ii) the structure it identifies is not reducible to mere aggregate causation; and (iii) it clearly satisfies intuitive and informal definitions of mechanism. We conclude by assessing the prospects for a form of mechanism realism weaker than LHR that nevertheless satisfies all three of these requirements. (shrink)

The target article criticises reductionist programs in cognitive science for failing to take into account important explanatory features of the organism's physical embodiment and task environment. My aim in this commentary is to show how such features are increasingly being taken seriously by (some) researchers in cognitive neuroscience, who describe the functional activity of neural structures in terms that are context-sensitive rather than intrinsic. This approach can allow us to take seriously the concerns presented in Gallagher’s [2019] target article without (...) having to completely give up on neuroscientific explanations of human behaviour. (shrink)