For a fixed q  ℕ and a given Σ1 definition φ(d,x), where d is a parameter, we construct a model M of 1 Δ0 + ¬ exp and a non standard d  M such that in M either φ has no witness smaller than d or phgr; is equivalent to a formula ϕ(d,x) having no more than q alternations of blocks of quantifiers.

Social media is a prominent communication platform. Its active usage permeates all generations and it is imperative that the platform be fully optimized for knowledge transfer and innovation diffusion. However, there are several considerations regarding platform usage, including media affordances. Social media affordances enable users to interact with the world around them through features of modality, agency, interactivity, and navigation. Previous studies have indicated that social media affordances significantly influence user behavior and usage. However, research exploring the effect of social (...) media affordances on knowledge acquisition and the reduction of decision-making complexities is limited. Therefore, focusing on 179 paddy farmers in Malaysia, this study examined the effect of social media affordances on information quality, knowledge acquisition, and complexity reduction regarding innovation adoption decisions using a quantitative approach. This study’s findings reveal that social media affordances have a significant effect on perceived information quality, knowledge acquisition, and complexity reduction. (shrink)

Some problems rarely discussed in traditional philosophy of science are mentioned: The empirical sciences using mathematico-quantitative theoretical models are frequently confronted with several types of computational problems posing primarily methodological limitations on explanatory and prognostic matters. Such limitations may arise from the appearances of deterministic chaos and (too) high computational complexity in general. In many cases, however, scientists circumvent such limitations by utilizing reductional approximations or complexity reductions for intractable problem formulations, thus constructing new models which are computationally (...) tractable. Such activities are compared with reduction types (more) established in philosophy of science. (shrink)

Some problems rarely discussed in traditional philosophy of science are mentioned: The empirical sciences using mathematico-quantitative theoretical models are frequently confronted with several types of computational problems posing primarily methodological limitations on explanatory and prognostic matters. Such limitations may arise from the appearances of deterministic chaos and high computational complexity in general. In many cases, however, scientists circumvent such limitations by utilizing reductional approximations or complexity reductions for intractable problem formulations, thus constructing new models which are computationally tractable. (...) Such activities are compared with reduction types established in philosophy of science. (shrink)

Taking the lead from complexity theory and complex systems methodology, the article argues that we are engaged in a contradictory process when encountering, analysing and dealing with complexity. We face opposite tendencies that indicate an in-built dynamic between the increase of complexity and its reduction. The increase partly comes through evolution, defined as the transmission of information and partly from the desire for a human-built world that functions more efficiently. The reduction of complexity is (...) due partly to the necessity of minimizing unwanted and unintended consequences of its increase, and partly due to the continued re-alignment between social systems and their environments. The article examines the public debate about human stem cell research, the debates in the 18th century about the free circulation of commodities and opinions, and the attempts to provide answers to the question debated between Einstein and Freud: why war? The article concludes by arguing that the plea for a re-alignment of scientific disciplines will not suffice. Instead, the study of the co-evolution between science and society offers itself as a strategic research site by focusing on the dynamic interplay between the increase of complexity and its reduction. (shrink)

This chapter describes the application of reduction concepts in emergence and self organization of complex dynamical system. Condition-dependent laws compress and dynamical equation sets provide implicit compressed representations even when most of that information is not explicitly available without decompression. And, paradoxically, there is still the determined march of fundamental analytical dynamics expanding its compression reach toward a Theory of Everything—even while the more rapidly expanding domain of complex systems dynamics confronts its assumptions and its monolithicity. Nor does science (...) fall apart into a disunified aggregate of particular cases since, with fundamental dynamics as a backbone, complex matching up of models across theoretical and empirical domains then articulates its model-structured skeleton. Discussion provides the delicately entwined dance of emergence and reduction providing constraints on compression that also permit its expansion. However, while the vision is not dead, it is currently substantially more complexly structured through model similarities and differences than that initially envisaged and individuals are left with deep questions about compression unresolved. (shrink)

Background: how mind functions is subject to continuing scientific discussion. A simplistic approach says that, since no convincing way has been found to model subjective experience, mind cannot exist. A second holds that, since mind cannot be described by classical physics, it must be described by quantum physics. Another perspective concerns mind's hypothesized ability to interact with the world of quanta: it should be responsible for reduction of quantum wave packets; physics producing 'Objective Reduction' is postulated to form (...) the basis for mind-matter interactions. This presentation describes results derived from a new approach to these problems. It is based on well-established biology involving physics not previously applied to the fields of mind, or consciousness studies, that of critical feedback instability. -/- Methods: 'self-organized criticality' in complexity biology places system loci of control at critical instabilities, physical properties of which, including information properties, are presented. Their elucidation shows that they can model hitherto unexplained properties of experience. -/- Results: All results depend on physical properties of critical instabilities. First, at least one feed-back or feed-forward loop must have feedback gain, g = 1: information flows round the loop impress perfect images of system states back on themselves: they represent processes of perfect self-observation. This annihilates system quanta: system excitations are instability fluctuations, which cannot be quantized. Major results follow: -/- 1. Information vectors representing criticality states must include at least one attached information loop denoting self-observation. -/- 2. Such loop structures are attributed a function, 'registering the state's own existence', explaining -/- a. Subjective 'awareness of one's own presence' -/- b. How content-free states of awareness can be remembered (Jon Shear) -/- c. Subjective experience of time duration (Immanuel Kant) -/- d. The 'witness' property of experience – often mentioned by athletes 'in the zone' -/- e. The natural association between consciousness and intelligence -/- This novel, physically and biologically sound approach seems to satisfactorily model subjectivity. -/- Further significant results follow: -/- 1. Registration of external information in excited states of systems at criticality reduces external wave-packets: the new model exhibits 'Objective Reduction' of wave packets. -/- 2. High internal coherence (postulated by Domash & Penrose) leading to a. Non-separable information vector bundles. b. Non-reductive states (Chalmers's criterion for experience). -/- 3. Information that is: a. encoded in coherence negentropy; b. non-digitizable, and therefore c. computationally without digital equivalent (posited by Penrose). -/- Discussion and Conclusions: instability physics implies anharmonic motion, preventing excitation quantization, and totally different from the quantum physics of simple harmonic motion at stability. Instability excitations are different from anything hitherto conceived in information science. They can model aspects of mind never previously treated, including genuine subjectivity, objective reduction of wave-packets, and inter alia all properties given above. (shrink)

A reduct of a first-order structure is another structure on the same set with perhaps fewer definable predicates. We consider reducts of the complex field which are proper but nontrivial in a sense to be made precise in the paper. Our main result lists seven kinds of reducts. The list is complete in the sense that every reduct is a finite cover of one of these. We also investigate when two items on our list can be the same, in a (...) couple of natural senses. (shrink)

Psychoneural reduction is under attack again, only this time from a former ally: cognitive neuroscience. It has become popular to think of the brain as a complex system whose theoretically important properties emerge from dynamic, non-linear interactions between its component parts. ``Emergence'' is supposed to replace reduction: the latter is thought to be incapable of explaining the brain qua complex system. Rather than engage this issue at the level of theories of reduction versus theories of emergence, I (...) here emphasize a role that reductionism plays – and will continue to play – even if neuroscience adopts this ``complex systems'' view. In detailed investigations into the function of complex neural circuits, certain questions can only be addressed by moving down levels and scales. This role for reduction also finds a place for approaches that dominate mainstream neuroscience, like the widespread use of experimental techniques and theories from molecular biology and biochemistry. These are difficult to reconcile with the anti-reductionist sentiments of the ``complex systems'' branch of cognitive neuroscience. (shrink)

The past two decades have seen an explosion in the methods and directions of neuroscience research. Along with many others, complexity research has rapidly gained traction as both an independent research field and a valuable subdiscipline in computational neuroscience. In the past decade alone, several studies have suggested that psychiatric disorders affect the spatiotemporal complexity of both global and region-specific brain activity (Liu et al., 2013; Adhikari et al., 2017; Li et al., 2018). However, many of these studies (...) have not accounted for the distributed nature of cognition in either the global or regional complexity estimates, which may lead to erroneous interpretations of both global and region-specific entropy estimates. To alleviate this concern, we propose a novel method for estimating complexity. This method relies upon projecting dynamic functional connectivity into a low-dimensional space which captures the distributed nature of brain activity. Dimension-specific entropy may be estimated within this space, which in turn allows for a rapid estimate of global signal complexity. Testing this method on a recently acquired obsessive-compulsive disorder dataset reveals substantial increases in the complexity of both global and dimension-specific activity versus healthy controls, suggesting that obsessive-compulsive patients may experience increased disorder in cognition. To probe the potential causes of this alteration, we estimate subject-level effective connectivity via a Hopf oscillator-based model dynamic model, the results of which suggest that obsessive-compulsive patients may experience abnormally high connectivity across a broad network in the cortex. These findings are broadly in line with results from previous studies, suggesting that this method is both robust and sensitive to group-level complexity alterations. (shrink)

Some theorists who emphasize the complexity of biological and cognitive systems and who advocate the employment of the tools of dynamical systems theory in explaining them construe complexity and reduction as exclusive alternatives. This paper argues that reduction, an approach to explanation that decomposes complex activities and localizes the components within the complex system, is not only compatible with an emphasis on complexity, but provides the foundation for dynamical analysis. Explanation via decomposition and localization is (...) nonetheless extremely challenging, and an analysis of recent cognitive neuroscience research on memory is used to illustrate what is involved. Memory researchers split between advocating memory systems and advocating memory processes, and I argue that it is the latter approach that provides the critical sort of decomposition and localization for explaining memory. The challenges of linking distinguishable functions with brain processes is illustrated by two examples: competing hypotheses about the contribution of the hippocampus and competing attempts to link areas in frontal cortex with memory processing. (shrink)

The unprecedented prowess of measurement techniques provides a detailed, multi‐scale look into the depths of living systems. Understanding these avalanches of high‐dimensional data—by distilling underlying principles and mechanisms—necessitates dimensional reduction. We propose that living systems achieve exquisite dimensional reduction, originating from their capacity to learn, through evolution and phenotypic plasticity, the relevant aspects of a non‐random, smooth physical reality. We explain how geometric insights by mathematicians allow one to identify these genuine hallmarks of life and distinguish them from (...) universal properties of generic data sets. We illustrate these principles in a concrete example of protein evolution, suggesting a simple general recipe that can be applied to understand other biological systems. (shrink)

Parallel attribute reduction is one of the most important topics in current research on rough set theory. Although some parallel algorithms were well documented, most of them are still faced with some challenges for effectively dealing with the complex heterogeneous data including categorical and numerical attributes. Aiming at this problem, a novel attribute reduction algorithm based on neighborhood multigranulation rough sets was developed to process the massive heterogeneous data in the parallel way. The MapReduce-based parallelization method for attribute (...) reduction was proposed in the framework of neighborhood multigranulation rough sets. To improve the reduction efficiency, the hashing Map/Reduce functions were designed to speed up the positive region calculation. Thereafter, a quick parallel attribute reduction algorithm using MapReduce was developed. The effectiveness and superiority of this parallel algorithm were demonstrated by theoretical analysis and comparison experiments. (shrink)

Modern science is, to a large extent, a model-building activity. But how are models contructed? How are they related to theories and data? How do they explain complex scientific phenomena, and which role do computer simulations play here? These questions have kept philosophers of science busy for many years, and much work has been done to identify modeling as the central activity of theoretical science. At the same time, these questions have been addressed by methodologically-minded scientists, albeit from a different (...) point of view. While philosophers typically have an eye on general aspects of scientific modeling, scientists typically take their own science as the starting point and are often more concerned with specific methodological problems. There is, however, also much common ground in middle, where philosophers and scientists can engage in a productive dialogue, as the present volume demonstrates. To do so, the editors of this volume have invited eight leading scientists from cosmology, climate science, social science, chemical engeneering and neuroscience to reflect upon their modeling work, and eight philosophers of science to provide a commentary. (shrink)

We give the first systematic study of strong isomorphism reductions, a notion of reduction more appropriate than polynomial time reduction when, for example, comparing the computational complexity of the isomorphim problem for different classes of structures. We show that the partial ordering of its degrees is quite rich. We analyze its relationship to a further type of reduction between classes of structures based on purely comparing for every n the number of nonisomorphic structures of cardinality at (...) most n in both classes. Furthermore, in a more general setting we address the question of the existence of a maximal element in the partial ordering of the degrees. (shrink)

Computable reducibility is a well-established notion that allows to compare the complexity of various equivalence relations over the natural numbers. We generalize computable reducibility by introducing degree spectra of reducibility and bi-reducibility. These spectra provide a natural way of measuring the complexity of reductions between equivalence relations. We prove that any upward closed collection of Turing degrees with a countable basis can be realised as a reducibility spectrum or as a bi-reducibility spectrum. We show also that there is (...) a reducibility spectrum of computably enumerable equivalence relations with no countable basis and a reducibility spectrum of computably enumerable equivalence relations which is downward dense, thus has no basis. (shrink)

Using appropriate notation systems for proofs, cut-reduction can often be rendered feasible on these notations. Explicit bounds can be given. Developing a suitable notation system for Bounded Arithmetic, and applying these bounds, all the known results on definable functions of certain such theories can be reobtained in a uniform way.

Resisting Reduction is a timely and insightful collection of prizewinning essays that seek to establish a viable paradigm for our approach to Artificial Intelligence (AI)—a phenomenon viewed throug...

Image denoising is one of the important problems in the research field of computer vision, artificial intelligence, 3D vision, and image processing, where the fundamental aim is to recover the original image features from a noisy contaminated image. The camera sensor additive noise present in the holographic recording process reduces the quality of the retrieved image. Even though various techniques have been developed to minimize the noise in digital holography, the noise reduction still remains a challenging task. This article (...) presents a compressive sensing technique to minimize the additive noise in the digital holographic reconstruction process. We demonstrate the reduction of additive noise using complex wave retrieval method as a sensing matrix in the CS model. The proposed CS method to suppress the noise during the reconstruction process is illustrated using numerical simulations. Only 50% of the pixel measurements are considered in the noisy hologram, which is far less than the original complex object pixels. The impact of additive gaussian noise in the recording plane on the reconstruction accuracy of both intensity and phase distribution is analysed. The CS method denoises and estimates the complex object information accurately. The numerical simulation results have shown that the proposed CS method has effectively minimized the noise in the reconstructed image and has greatly improved the quality of both intensity and phase information. (shrink)

A common belief is that evolution generally proceeds towards greater complexity at both the organismal and the genomic level, numerous examples of reductive evolution of parasites and symbionts notwithstanding. However, recent evolutionary reconstructions challenge this notion. Two notable examples are the reconstruction of the complex archaeal ancestor and the intron‐rich ancestor of eukaryotes. In both cases, evolution in most of the lineages was apparently dominated by extensive loss of genes and introns, respectively. These and many other cases of reductive (...) evolution are consistent with a general model composed of two distinct evolutionary phases: the short, explosive, innovation phase that leads to an abrupt increase in genome complexity, followed by a much longer reductive phase, which encompasses either a neutral ratchet of genetic material loss or adaptive genome streamlining. Quantitatively, the evolution of genomes appears to be dominated by reduction and simplification, punctuated by episodes of complexification. (shrink)

We consider the role of habits in human individual and social ordinary life and we move from the fact that habitual behavior is fundamental to organize our activities in individual as well as in social contexts. Instead of considering classical and revised versions of intentionality, we prefer to focus on habits that reduce the complexity of daily life, and also on their corresponding activity in social life where we take part to informal joint practices as well as to institutionalized (...) ones. (shrink)

This chapter discusses several kinds of reduction that are often found in the biomedical sciences, in contrast to reduction in fields such as physics. This includes reduction as a methodological assumption for how to investigate phenomena like complex diseases, and reduction as a conceptual tool for relating distinct models of the same phenomenon. The case of Parkinson’s disease illustrates a wide variety of ways in which reductionism is an important tool in medicine.

We study logical reduction (factorization) of relations into relations of lower arity by Boolean or relative products that come from applying conjunctions and existential quantifiers to predicates, i.e. by primitive positive formulas of predicate calculus. Our algebraic framework unifies natural joins and data dependencies of database theory and relational algebra of clone theory with the bond algebra of C.S. Peirce. We also offer new constructions of reductions, systematically study irreducible relations and reductions to them and introduce a new characteristic (...) of relations, ternarity, that measures their ‘complexity of relating’ and allows to refine reduction results. In particular, we refine Peirce’s controversial reduction thesis, and show that reducibility behaviour is dramatically different on finite and infinite domains. (shrink)

Unlike the overall framework of Ernest Nagel's work on reduction, his theory of intertheoretic connection still has life in it. It handles aptly cases where reduction requires complex representation of a target domain. Abandoning his formulation as too liberal was a mistake. Arguments that it is too liberal at best touch only Nagel's deductivist theory of explanation, not his condition of connectability. Taking this condition seriously gives a powerful view of reduction, but one which requires us to (...) index explanatory power to sciences as they are formulated at particular times. While we may thereby reduce more than philosophers have supposed, we must abandon hope (as Nagel did) of saying anything useful about reductionism. (shrink)

The idea of reduction has appeared in different forms throughout the history of science and philosophy. Thales took water to be the fundamental principle of all things; Leucippus and Democritus argued that everything is composed of small, indivisible atoms; Galileo and Newton tried to explain all motion with a few basic laws; 17th century mechanism conceived of everything in terms of the motions and collisions of particles of matter; British Empiricism held that all knowledge is, at root, experiential knowledge; (...) current physicists are searching for the GUT, the “grand unified theory,” that will show that at very high energies the electromagnetic and the weak and strong nuclear forces are fused into a single unified field. Some of these projects are clearly ontological in nature (Leucippus and Democritus), others are more methodological (mechanism), and still others strive for theoretical simplification (the projects of Galileo and Newton or the search for a GUT). Nevertheless, as they all aim at revealing some kind of unity or simplicity behind the appearance of plurality or complexity, they may all be regarded as (attempted) reductions. (shrink)

The main concepts of the free energy (FE) neuroscience developed by Karl Friston and colleagues parallel those of Freud's Project for a Scientific Psychology. In Hobson et al. ( 2014 ) these include an innate virtual reality generator that produces the fictive prior beliefs that Freud described as the primary process. This enables Friston's account to encompass a unified treatment—a complexity theory—of the role of virtual reality in both dreaming and mental disorder. In both accounts the brain operates to (...) minimize FE aroused by sensory impingements—including interoceptive impingements that report compliance with biological imperatives—and constructs a representation/model of the causes of impingement that enables this minimization. In Friston's account (variational) FE equals complexity minus accuracy, and is minimized by increasing accuracy and decreasing complexity. Roughly the brain (or model) increases accuracy together with complexity in waking. This is mediated by consciousness-creating active inference—by which it explains sensory impingements in terms of perceptual experiences of their causes. In sleep it reduces complexity by processes that include both synaptic pruning and consciousness/virtual reality/dreaming in REM. The consciousness-creating active inference that effects complexity-reduction in REM dreaming must operate on FE-arousing data distinct from sensory impingement. The most relevant source is remembered arousals of emotion, both recent and remote, as processed in SWS and REM on “active systems” accounts of memory consolidation/reconsolidation. Freud describes these remembered arousals as condensed in the dreamwork for use in the conscious contents of dreams, and similar condensation can be seen in symptoms. Complexity partly reflects emotional conflict and trauma. This indicates that dreams and symptoms are both produced to reduce complexity in the form of potentially adverse (traumatic or conflicting) arousals of amygdala-related emotions. Mental disorder is thus caused by computational complexity together with mechanisms like synaptic pruning that have evolved for complexity-reduction; and important features of disorder can be understood in these terms. Details of the consilience among Freudian, systems consolidation, and complexity-reduction accounts appear clearly in the analysis of a single fragment of a dream, indicating also how complexity reduction proceeds by a process resembling Bayesian model selection. (shrink)

All the major inter-theoretic relations of fundamental science are asymptotic ones, e.g. quantum theory as Planck's constant h 0, yielding (roughly) Newtonian mechanics. Thus asymptotics ultimately grounds claims about inter-theoretic explanation, reduction and emergence. This paper examines four recent, central claims by Batterman concerning asymptotics and reduction. While these claims are criticised, the discussion is used to develop an enriched, dynamically-based account of reduction and emergence, to show its capacity to illuminate the complex variety of inter-theory relationships (...) in physics, and to provide a principled resolution to such persistent philosophical problems as multiple realisability and the nature of the special sciences. Introduction Exposition Examination I: Claims (1) and (2), asymptotic explanation and reference Examination II: Claim (3), reduction and singular asymptotics Examination III: Claim (4), emergence and multiple realisability Conclusion. (shrink)

Reduction was once a central topic in philosophy of science. I claim that it remains important, especially when applied to problems and problem-solutions rather than only to large theory-complexes. Without attempting a comprehensive classification, I discuss various kinds of problem reductions and similar relations, illustrating them, inter alia, in terms of the blackbody problem and early quantization problems. Kuhn's early work is suggestive here both for structuralist theory of science and for the line I prefer to take. My central (...) claims in the paper are (1) that problem reduction is important in its own right and does not "reduce" to theory reduction and (2) that problem reduction is generally more important than theory reduction to methodology as the "control theory" of inquiry. (shrink)

Institutional ethics committees remain largely absent from the literature on error reduction and patient safety. This paper attempts to fill the gap. Healthcare professionals are on the front lines in the defense against medical error, but the changes that are needed to reduce medical errors and enhance patient safety are cultural and systemic in nature. As noted in the Hastings Centers recent report, Promoting Patient Safety, the occurrence of medical error involves a complex web of multiple factors. Human misstep (...) is certainly one such factor, but not the only one. In this paper, I build on the Hasting Centers report on patient safety in arguing that institutional ethics committees ought to play an integral role in the transformation of a culture of blame to a culture of safety in healthcare delivery. (shrink)

We study the computational complexity of the universal and quasi-equational theories of classes of bounded distributive lattices with a negation operation, i.e., a unary operation satisfying a subset of the properties of the Boolean negation. The upper bounds are obtained through the use of partial algebras. The lower bounds are either inherited from the equational theory of bounded distributive lattices or obtained through a reduction of a global satisfiability problem for a suitable system of propositional modal logic.

The world is complex, but acknowledging its complexity requires an appreciation for the many roles context plays in shaping natural phenomena. In _Unsimple Truths, _Sandra Mitchell argues that the long-standing scientific and philosophical deference to reductive explanations founded on simple universal laws, linear causal models, and predict-and-act strategies fails to accommodate the kinds of knowledge that many contemporary sciences are providing about the world. She advocates, instead, for a new understanding that represents the rich, variegated, interdependent fabric of many (...) levels and kinds of explanation that are integrated with one another to ground effective prediction and action. Mitchell draws from diverse fields including psychiatry, social insect biology, and studies of climate change to defend “integrative pluralism”—a theory of scientific practices that makes sense of how many natural and social sciences represent the multi-level, multi-component, dynamic structures they study. She explains how we must, in light of the now-acknowledged complexity and contingency of biological and social systems, revise how we conceptualize the world, how we investigate the world, and how we act in the world. Ultimately _Unsimple Truths _argues that the very idea of what should count as legitimate science itself should change. (shrink)

In this paper I shall discuss the concept of reduction—ontological, methodological, and epistemological or theoretical—in the biological sciences, with special emphasis on genetics and evolutionary biology. I suggest that perhaps, because the biological world has a form different from the non-biological world, it is appropriate to think of terms or metaphors different from those we would use when trying to understand the inorganic world. As such, the attempt to show that the biological is simply a deductive consequence of the (...) physicochemical is doomed to failure. The philosophical complexity of reductionism on the one hand and its potential for advancing the study of biology on the other thus requires continuing the ongoing dialogue between philosophers and biologists. (shrink)

Metaphor is commonly taken to be an elliptical simile. This article offers a rational reconstruction of two types of simile theories of metaphor: reductive and non-reductive. Careful analysis shows the differences between these theories, but in the end, neither does the explanatory work it sets out to do. In assimilating metaphor to simile and simile to literal comparison, the reductive simile theory obscures what is most important to an account of metaphor: an account of what it is to interpret a (...) bit of discourse metaphorically. The reductive simile theory fails because the reduction to literal comparison fails. The non-reductive simile theory faces most of the same problems that undermine the simile theory, particularly problems generating a corresponding simile when the metaphor contains quantificational terms and other linguistic complexities. Analysis of the non-reductive simile theory highlights the troublesome assumption (inherent in all simile theories) that metaphor and simile play the same linguistic role: making or prompting us to make comparisons. In both guises, the simile theory mistakes the task of explaining what a metaphor means with how metaphor (in general) has meaning; it confuses explanation with explication. In diagnosing and arguing against the simile theory, this article sets out a framework for understanding the difference between literal and metaphorical interpretation. (shrink)

I attribute to Aristotle a theory of sensible qualities that straddles the modern debate between reductive physicalist and primitivist theories of color. On the interpretation I defend, Aristotle identifies sensible qualities with the physical properties of sensibly qualified bodies in virtue of which they move and affect perceivers and sense media. Nevertheless, I argue, Aristotle thinks that the essential nature of these qualities is revealed in ordinary sense experience. From a modern perspective, the resulting picture of sensible qualities as simultaneously (...) causes and manifest features of sense experience appears naive. But as I hope to show, it is in fact the product of an explanatorily sophisticated scientific theory, one which Aristotle finds necessary to meet the complex demands that, for him, make sensible qualities an ontological problem. (shrink)

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)

So far, the sciences of complexity have received less attention from philosophers than from scientists. Responding to Salthe’s (Found Sci 15, 4(6):357–367, 2010a ) model of evolution, I focus on its metaphysical implications, asking whether the implications of his canonical developmental trajectory (CDT) must be materialistic as his reading proposes.

In Molecular Models: Philosophical Papers on Molecular Biology, Sahotra Sarkar presents a historical and philosophical analysis of four important themes in philosophy of science that have been influenced by discoveries in molecular biology. These are: reduction, function, information and directed mutation. I argue that there is an important difference between the cases of function and information and the more complex case of scientific reduction. In the former cases it makes sense to taxonomise important variations in scientific and philosophical (...) usage of the terms function and information . However, the variety of usage of reduction across scientific disciplines (and across philosophy of science) makes such taxonomy inappropriate. Sarkar presents reduction as a set of facts about the world that science has discovered, but the facts in question are remarkably disparate; variously semantic, epistemic and ontological. I argue that the more natural conclusion of Sarkar’s analysis is eliminativism about reduction as a scientific concept. (shrink)

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations (...) that appeal to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (shrink)