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  1. The mind, the lab, and the field: Three kinds of populations in scientific practice.Rasmus Grønfeldt Winther, Ryan Giordano, Michael D. Edge & Rasmus Nielsen - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 52:12-21.
    Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R.A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: the notion (...)
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  • Multilevel Research Strategies and Biological Systems.Maureen A. O’Malley, Ingo Brigandt, Alan C. Love, John W. Crawford, Jack A. Gilbert, Rob Knight, Sandra D. Mitchell & Forest Rohwer - 2014 - Philosophy of Science 81 (5):811-828.
    Multilevel research strategies characterize contemporary molecular inquiry into biological systems. We outline conceptual, methodological, and explanatory dimensions of these multilevel strategies in microbial ecology, systems biology, protein research, and developmental biology. This review of emerging lines of inquiry in these fields suggests that multilevel research in molecular life sciences has significant implications for philosophical understandings of explanation, modeling, and representation.
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  • The Structure of Scientific Theories.Rasmus Grønfeldt Winther - 2015 - Stanford Encyclopedia of Philosophy.
    Scientific inquiry has led to immense explanatory and technological successes, partly as a result of the pervasiveness of scientific theories. Relativity theory, evolutionary theory, and plate tectonics were, and continue to be, wildly successful families of theories within physics, biology, and geology. Other powerful theory clusters inhabit comparatively recent disciplines such as cognitive science, climate science, molecular biology, microeconomics, and Geographic Information Science (GIS). Effective scientific theories magnify understanding, help supply legitimate explanations, and assist in formulating predictions. Moving from their (...)
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  • Brains, Neuroscience, and Animalism: On the Implications of Thinking Brains.Carl Gillett - 2014 - Southern Journal of Philosophy 52 (S1):41-52.
    The neuroscience revolution has led many scientists to posit “expansive” or “thinking” brains that instantiate rich psychological properties. As a result, some scientists now even claim you are identical to such a brain. However, Eric Olson has offered new arguments that thinking brains cannot exist due to their intuitively “abominable” implications. After situating the commitment to thinking brains in the wider scientific discussions in which they are posited, I then critically assess Olson's arguments against such entities. Although highlighting an important (...)
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  • The normative structure of mathematization in systematic biology.Beckett Sterner & Scott Lidgard - 2014 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 46 (1):44-54.
    We argue that the mathematization of science should be understood as a normative activity of advocating for a particular methodology with its own criteria for evaluating good research. As a case study, we examine the mathematization of taxonomic classification in systematic biology. We show how mathematization is a normative activity by contrasting its distinctive features in numerical taxonomy in the 1960s with an earlier reform advocated by Ernst Mayr starting in the 1940s. Both Mayr and the numerical taxonomists sought to (...)
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  • Reliability and External Validity of Neurobiological Experiments.Wong Muk Yan - 2013 - International Studies in the Philosophy of Science 27 (4):429-446.
    Reliability and external validity are two fundamental values that pose incompatible constraints on neurobiological experiments. The more reliability an experimental result achieves, the less external validity it earns, and vice versa. In this article, I propose an externalist interpretation of external validity: the external validity of an experimental result depends not only on how much complexity is built into an experimental design, but also on the relationship between the experimental result and other related experiments. This externalist interpretation, which explains how (...)
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  • Levels, Individual Variation and Massive Multiple Realization in Neurobiology.Kenneth Aizawa & Carl Gillett - 2009 - In John Bickle (ed.), The Oxford handbook of philosophy and neuroscience. New York: Oxford University Press. pp. 539--582.
    Biologists seems to hold two fundamental beliefs: Organisms are organized into levels and the individuals at these levels differ in their properties. Together these suggest that there will be massive multiple realization, i.e. that many human psychological properties are multiply realized at many neurobiological levels. This paper provides some documentation in support of this suggestion.
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  • Models and truth.Uskali Mäki - 2010 - In M. Dorato M. Suàrez (ed.), Epsa Epistemology and Methodology of Science. Springer. pp. 177--187.
    In what follows, I will give examples of the sorts of step that can be taken towards spelling out the intuition that, after all, good models might be true. Along the way, I provide an outline of my account of models as ontologically and pragmatically constrained representations. And I emphasize the importance of examining models as functionally composed systems in which different components play different roles and only some components serve as relevant truth bearers. This disputes the standard approach that (...)
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  • Sculpting the space of actions. Explaining human action by integrating intentions and mechanisms.Machiel Keestra - 2014 - Dissertation, University of Amsterdam
    How can we explain the intentional nature of an expert’s actions, performed without immediate and conscious control, relying instead on automatic cognitive processes? How can we account for the differences and similarities with a novice’s performance of the same actions? Can a naturalist explanation of intentional expert action be in line with a philosophical concept of intentional action? Answering these and related questions in a positive sense, this dissertation develops a three-step argument. Part I considers different methods of explanations in (...)
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  • Sens et neurosciences. Étude critique de Paul Thagard, The Brain and the Meaning of Life, Princeton University Press, 2010, 274 pagesÉtude critique de Paul Thagard, The Brain and the Meaning of Life, Princeton University Press, 2010, 274 pages. [REVIEW]Jean-Frédéric de Pasquale - 2011 - Philosophiques 38 (2):579-595.
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  • Distributed Cognition in Sports Teams: Explaining successful and expert performance.Kellie Williamson & Rochelle Cox - 2014 - Educational Philosophy and Theory 46 (6):1-15.
    In this article we use a hybrid methodology to better understand the skilful performance of sports teams as an exemplar of distributed cognition. We highlight key differences between a team of individual experts and an expert team, and outline the kinds of shared characteristics likely to be found in an expert team. We focus on the way that shared knowledge contributes to expert team performance. In particular, we suggest that certain kinds of shared knowledge and shared skill, potentially developed through (...)
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  • Intentional Models as Essential Scientific Tools.Eric Hochstein - 2013 - International Studies in the Philosophy of Science 27 (2):199-217.
    In this article, I argue that the use of scientific models that attribute intentional content to complex systems bears a striking similarity to the way in which statistical descriptions are used. To demonstrate this, I compare and contrast an intentional model with a statistical model, and argue that key similarities between the two give us compelling reasons to consider both as a type of phenomenological model. I then demonstrate how intentional descriptions play an important role in scientific methodology as a (...)
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  • Linking chemistry with physics: arguments and counterarguments. [REVIEW]Olimpia Lombardi - 2013 - Foundations of Chemistry 16 (3):181-192.
    The many-faced relationship between chemistry and physics is one of the most discussed topics in the philosophy of chemistry. In his recent book Reducing Chemistry to Physics. Limits, Models, Consequences, Hinne Hettema conceives this relationship as a reduction link, and devotes his work to defend this position on the basis of a “naturalized” concept of reduction. In the present paper I critically review three kinds of issues stemming from Hettema’s argumentation: philosophical, scientific and methodological.
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  • False beliefs and naive beliefs: They can be good for you.Roberto Casati & Marco Bertamini - 2009 - Behavioral and Brain Sciences 32 (6):512-513.
    Naive physics beliefs can be systematically mistaken. They provide a useful test-bed because they are common, and also because their existence must rely on some adaptive advantage, within a given context. In the second part of the commentary we also ask questions about when a whole family of misbeliefs should be considered together as a single phenomenon.
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  • On a paradox of truth, or how not to obscure the issue of whether explanatory models can be true.Uskali Mäki - 2013 - Journal of Economic Methodology 20 (3):268 - 279.
    It is argued that Reiss (2012) fails to refute attempts to resolve the paradox of false explanatory models. His article fails to provide an articulate conception of what exactly the presumed paradox is, it suffers from uncontrolled ambiguities and inconsistencies, and it fails to adequately address accounts of economic models that might contribute to reconciling their apparent falsehood and explanatoriness. Some details in my account of how apparently false models may explain are clarified.
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  • Stabilizing Mental Disorders: Prospects and Problems.Jacqueline Anne Sullivan - 2014 - In H. Kincaid & J. Sullivan (eds.), Mental Kinds and Natural Kinds. MIT Press. pp. 257-281.
    In this chapter I investigate the kinds of changes that psychiatric kinds undergo when they become explanatory targets of areas of sciences that are not “mature” and are in the early stages of discovering mechanisms. The two areas of science that are the targets of my analysis are cognitive neuroscience and cognitive neurobiology.
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  • Experiments, Intuitions and Images of Philosophy and Science.Alan C. Love - 2013 - Analysis 73 (4):785-797.
    According to Joshua Alexander, philosophers use intuitions routinely as a form of evidence to test philosophical theories but experimental philosophy demonstrates that these intuitions are unreliable and unrepresentative.1 According to Herman Cappelen, philosophers never use intuitions as evidence (despite the vacuous sentential leader ‘intuitively’) and experimental philosophy lacks a rationale for its much-touted existence.2 That two books are diametrically opposed on methodology in philosophy is not noteworthy. But eyebrows might be raised at such contradictory accounts of the phenomenology of philosophical (...)
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  • Towards the Methodological Turn in the Philosophy of Science.Hsiang-Ke Chao, Szu-Ting Chen & Roberta L. Millstein - 2013 - In Hsiang-Ke Chao, Szu-Ting Chen & Roberta L. Millstein (eds.), Mechanism and Causality in Biology and Economics. Dordrecht: Springer.
    This chapter provides an introduction to the study of the philosophical notions of mechanisms and causality in biology and economics. This chapter sets the stage for this volume, Mechanism and Causality in Biology and Economics, in three ways. First, it gives a broad review of the recent changes and current state of the study of mechanisms and causality in the philosophy of science. Second, consistent with a recent trend in the philosophy of science to focus on scientific practices, it in (...)
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  • Well-Structured Biology: Numerical Taxonomy's Epistemic Vision for Systematics.Beckett Sterner - 2014 - In Andrew Hamilton (ed.), Patterns in Nature. University of California Press. pp. 213-244.
    What does it look like when a group of scientists set out to re-envision an entire field of biology in symbolic and formal terms? I analyze the founding and articulation of Numerical Taxonomy between 1950 and 1970, the period when it set out a radical new approach to classification and founded a tradition of mathematics in systematic biology. I argue that introducing mathematics in a comprehensive way also requires re-organizing the daily work of scientists in the field. Numerical taxonomists sought (...)
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  • Learning, evolvability and exploratory behaviour: extending the evolutionary reach of learning.Rachael L. Brown - 2013 - Biology and Philosophy 28 (6):933-955.
    Traditional accounts of the role of learning in evolution have concentrated upon its capacity as a source of fitness to individuals. In this paper I use a case study from invasive species biology—the role of conditioned taste aversion in mitigating the impact of cane toads on the native species of Northern Australia—to highlight a role for learning beyond this—as a source of evolvability to populations. This has two benefits. First, it highlights an otherwise under-appreciated role for learning in evolution that (...)
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  • Causal and Constitutive Explanation Compared.Petri Ylikoski - 2013 - Erkenntnis 78 (2):277-297.
    This article compares causal and constitutive explanation. While scientific inquiry usually addresses both causal and constitutive questions, making the distinction is crucial for a detailed understanding of scientific questions and their interrelations. These explanations have different kinds of explananda and they track different sorts of dependencies. Constitutive explanations do not address events or behaviors, but causal capacities. While there are some interesting relations between building and causal manipulation, causation and constitution are not to be confused. Constitution is a synchronous and (...)
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  • Systems biology and the integration of mechanistic explanation and mathematical explanation.Ingo Brigandt - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):477-492.
    The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation have failed to address how a mathematical model could contribute to such explanations. I discuss how mathematical (...)
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  • Mechanistic Explanations and Models in Molecular Systems Biology.Fred C. Boogerd, Frank J. Bruggeman & Robert C. Richardson - 2013 - Foundations of Science 18 (4):725-744.
    Mechanistic models in molecular systems biology are generally mathematical models of the action of networks of biochemical reactions, involving metabolism, signal transduction, and/or gene expression. They can be either simulated numerically or analyzed analytically. Systems biology integrates quantitative molecular data acquisition with mathematical models to design new experiments, discriminate between alternative mechanisms and explain the molecular basis of cellular properties. At the heart of this approach are mechanistic models of molecular networks. We focus on the articulation and development of mechanistic (...)
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  • Multiple realization by compensatory differences.Kenneth Aizawa - 2013 - European Journal for Philosophy of Science 3 (1):69-86.
    One way that scientifically recognized properties are multiply realized is by “compensatory differences” among realizing properties. If a property G is jointly realized by two properties F1 and F2, then G can be multiply realized by having changes in the property F1 offset changes in the property F2. In some cases, there are scientific laws that articulate how distinct combinations of physical quantities can determine one and the same value of some other physical quantity. One moral to draw is that (...)
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  • Explanatory power of extended cognition.Samuli Pöyhönen - 2014 - Philosophical Psychology 27 (5):735-759.
    I argue that examining the explanatory power of the hypothesis of extended cognition (HEC) offers a fruitful approach to the problem of cognitive system demarcation. Although in the discussions on HEC it has become common to refer to considerations of explanatory power as a means for assessing the plausibility of the extended cognition approach, to date no satisfying account of explanatory power has been presented in the literature. I suggest that the currently most prominent theory of explanation in the special (...)
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  • (1 other version)Emergence and Reduction.Shaun Le Boutillier - 2013 - Journal for the Theory of Social Behaviour 43 (2):205-225.
    The question of the ontological status of social wholes has been formative to the development of key positions and debates within modern social theory. Intrinsic to this is the contested meaning of the concept of emergence and the idea that the collective whole is in some way more than the sum of its parts. This claim, in its contemporary form, gives exaggerated importance to a simple truism of re-description that concerns all wholes. In this paper I argue that a better (...)
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  • Causal graphs and biological mechanisms.Alexander Gebharter & Marie I. Kaiser - 2014 - In Marie I. Kaiser, Oliver R. Scholz, Daniel Plenge & Andreas Hüttemann (eds.), Explanation in the special science: The case of biology and history. Dordrecht: Springer. pp. 55-86.
    Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological research practice (...)
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  • Transactive Memory Systems: A Mechanistic Analysis of Emergent Group Memory.Georg Theiner - 2013 - Review of Philosophy and Psychology 4 (1):65-89.
    Wegner, Giuliano, and Hertel (1985) defined the notion of a transactive memory system (TMS) as a group level memory system that “involves the operation of the memory systems of the individuals and the processes of communication that occur within the group (p. 191). Those processes are the collaborative procedures (“transactions”) by which groups encode, store, and retrieve information that is distributed among their members. Over the past 25+ years, the conception of a TMS has progressively garnered an increased interest among (...)
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  • Rendering Interventionism and Non‐Reductive Physicalism Compatible.Michael Baumgartner - 2013 - Dialectica 67 (1):1-27.
    In recent years, the debate on the problem of causal exclusion has seen an ‘interventionist turn’. Numerous non-reductive physicalists (e.g. Shapiro and Sober 2007) have argued that Woodward's (2003) interventionist theory of causation provides a means to empirically establish the existence of non-reducible mental-to-physical causation. By contrast, Baumgartner (2010) has presented an interventionist exclusion argument showing that interventionism is in fact incompatible with non-reductive physicalism. In response, a number of revised versions of interventionism have been suggested that are compatible with (...)
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  • Philosophy and Complexity.Gil C. Santos - 2013 - Foundations of Science 18 (4):681-686.
    Some relevant distinctions between the notions of complexity, non-linearity, self-organization and emergence are addressed.
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  • Towards a processual microbial ontology.Eric Bapteste & John Dupre - 2013 - Biology and Philosophy 28 (2):379-404.
    Standard microbial evolutionary ontology is organized according to a nested hierarchy of entities at various levels of biological organization. It typically detects and defines these entities in relation to the most stable aspects of evolutionary processes, by identifying lineages evolving by a process of vertical inheritance from an ancestral entity. However, recent advances in microbiology indicate that such an ontology has important limitations. The various dynamics detected within microbiological systems reveal that a focus on the most stable entities (or features (...)
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  • (1 other version)The self as a system of multilevel interacting mechanisms.Paul Thagard - 2012 - Philosophical Psychology (2):1-19.
    This paper proposes an account of the self as a multilevel system consisting of social, individual, neural, and molecular mechanisms. It argues that the functioning of the self depends on causal relations between mechanisms operating at different levels. In place of reductionist and holistic approaches to cognitive science, I advocate a method of multilevel interacting mechanisms. This method is illustrated by showing how self-concepts operate at several different levels.
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  • The Limits of Reductionism in the Life Sciences.Marie I. Kaiser - 2011 - History and Philosophy of the Life Sciences 33 (4):453-476.
    In the contemporary life sciences more and more researchers emphasize the “limits of reductionism” (e.g. Ahn et al. 2006a, 709; Mazzocchi 2008, 10) or they call for a move “beyond reductionism” (Gallagher/Appenzeller 1999, 79). However, it is far from clear what exactly they argue for and what the envisioned limits of reductionism are. In this paper I claim that the current discussions about reductionism in the life sciences, which focus on methodological and explanatory issues, leave the concepts of a reductive (...)
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  • Robustness analysis disclaimer: please read the manual before use!Jaakko Kuorikoski, Aki Lehtinen & Caterina Marchionni - 2012 - Biology and Philosophy 27 (6):891-902.
    Odenbaugh and Alexandrova provide a challenging critique of the epistemic benefits of robustness analysis, singling out for particular criticism the account we articulated in Kuorikoski et al.. Odenbaugh and Alexandrova offer two arguments against the confirmatory value of robustness analysis: robust theorems cannot specify causal mechanisms and models are rarely independent in the way required by robustness analysis. We address Odenbaugh and Alexandrova’s criticisms in order to clarify some of our original arguments and to shed further light on the properties (...)
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  • Mathematical Modeling in Biology: Philosophy and Pragmatics.Rasmus Grønfeldt Winther - 2012 - Frontiers in Plant Evolution and Development 2012:1-3.
    Philosophy can shed light on mathematical modeling and the juxtaposition of modeling and empirical data. This paper explores three philosophical traditions of the structure of scientific theory—Syntactic, Semantic, and Pragmatic—to show that each illuminates mathematical modeling. The Pragmatic View identifies four critical functions of mathematical modeling: (1) unification of both models and data, (2) model fitting to data, (3) mechanism identification accounting for observation, and (4) prediction of future observations. Such facets are explored using a recent exchange between two groups (...)
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  • Object spaces: An organizing strategy for biological theorizing.Beckett Sterner - 2009 - Biological Theory 4 (3):280-286.
    A classic analytic approach to biological phenomena seeks to refine definitions until classes are sufficiently homogenous to support prediction and explanation, but this approach founders on cases where a single process produces objects with similar forms but heterogeneous behaviors. I introduce object spaces as a tool to tackle this challenging diversity of biological objects in terms of causal processes with well-defined formal properties. Object spaces have three primary components: (1) a combinatorial biological process such as protein synthesis that generates objects (...)
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  • The Limitations of Hierarchical Organization.Angela Potochnik & Brian McGill - 2012 - Philosophy of Science 79 (1):120-140.
    The concept of hierarchical organization is commonplace in science. Subatomic particles compose atoms, which compose molecules; cells compose tissues, which compose organs, which compose organisms; etc. Hierarchical organization is particularly prominent in ecology, a field of research explicitly arranged around levels of ecological organization. The concept of levels of organization is also central to a variety of debates in philosophy of science. Yet many difficulties plague the concept of discrete hierarchical levels. In this paper, we show how these difficulties undermine (...)
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  • Scientific Models.Stephen M. Downes - 2011 - Philosophy Compass 6 (11):757-764.
    This contribution provides an assessment of the epistemological role of scientific models. The prevalent view that all scientific models are representations of the world is rejected. This view points to a unified way of resolving epistemic issues for scientific models. The emerging consensus in philosophy of science that models have many different epistemic roles in science is presented and defended.
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  • Mechanistic social probability : how individual choices and varying circumstances produce stable social patterns.Marshall Abrams - 2012 - In Harold Kincaid (ed.), The Oxford Handbook of Philosophy of Social Science. Oxford University Press.
    This chapter explores a philosophical hypothesis about the nature of (some) probabilities encountered in social sciences. It should be of interest to those with philosophical concerns about the foundations of probability, and to social scientists and philosophers of science who are somewhat puzzled by the nature of probability in social domains. As will become clear below, the chapter is not intended as a contribution to an empirical methodology such as a particular way of applying statistics.
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  • Evo-Devo as a Trading Zone.Rasmus Grønfeldt Winther - 2014 - In Alan C. Love (ed.), Conceptual Change in Biology: Scientific and Philosophical Perspectives on Evolution and Development. Berlin: Springer Verlag, Boston Studies in the Philosophy of Science.
    Evo-Devo exhibits a plurality of scientific “cultures” of practice and theory. When are the cultures acting—individually or collectively—in ways that actually move research forward, empirically, theoretically, and ethically? When do they become imperialistic, in the sense of excluding and subordinating other cultures? This chapter identifies six cultures – three /styles/ (mathematical modeling, mechanism, and history) and three /paradigms/ (adaptationism, structuralism, and cladism). The key assumptions standing behind, under, or within each of these cultures are explored. Characterizing the internal structure of (...)
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  • (1 other version)Ceteris Paribus Laws.Alexander Reutlinger, Gerhard Schurz, Andreas Hüttemann & Siegfried Jaag - 2011 - Stanford Encyclopedia of Philosophy.
    Laws of nature take center stage in philosophy of science. Laws are usually believed to stand in a tight conceptual relation to many important key concepts such as causation, explanation, confirmation, determinism, counterfactuals etc. Traditionally, philosophers of science have focused on physical laws, which were taken to be at least true, universal statements that support counterfactual claims. But, although this claim about laws might be true with respect to physics, laws in the special sciences (such as biology, psychology, economics etc.) (...)
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  • Explanation in Biology: Reduction, Pluralism, and Explanatory Aims.Ingo Brigandt - 2011 - Science & Education 22 (1):69-91.
    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 (...)
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  • (1 other version)Understanding human action: integrating meanings, mechanisms, causes, and contexts.Machiel Keestra - 2011 - In Repko Allen, Szostak Rick & Newell William (eds.), Interdisciplinary Research: Case Studies of Integrative Understandings of Complex Problems. Sage Publications. pp. 201-235.
    Humans are capable of understanding an incredible variety of actions performed by other humans. Even though these range from primary biological actions, like eating and fleeing, to acts in parliament or in poetry, humans generally can make sense of each other’s actions. Understanding other people’s actions is called action understanding, and it can transcend differences in race, gender, culture, age, and social and historical circumstances. Action understanding is the cognitive ability to make sense of another person’s action by integrating perceptual (...)
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  • Is Captain Kirk a natural blonde? Do X-ray crystallographers dream of electron clouds? Comparing model-based inferences in science with fiction.Ann-Sophie Barwich - 2017 - In Otávio Bueno, Steven French, George Darby & Dean Rickles (eds.), Thinking About Science, Reflecting on Art: Bringing Aesthetics and Philosophy of Science Together. New York: Routledge.
    Scientific models share one central characteristic with fiction: their relation to the physical world is ambiguous. It is often unclear whether an element in a model represents something in the world or presents an artifact of model building. Fiction, too, can resemble our world to varying degrees. However, we assign a different epistemic function to scientific representations. As artifacts of human activity, how are scientific representations allowing us to make inferences about real phenomena? In reply to this concern, philosophers of (...)
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  • Making Knowledge in Synthetic Biology: Design Meets Kludge.Maureen A. O’Malley - 2009 - Biological Theory 4 (4):378-389.
    Synthetic biology is an umbrella term that covers a range of aims, approaches, and techniques. They are all brought together by common practices of analogizing, synthesizing, mechanicizing, and kludging. With a focus on kludging as the connection point between biology, engineering, and evolution, I show how synthetic biology’s successes depend on custom-built kludges and a creative, “make-it-work” attitude to the construction of biological systems. Such practices do not fit neatly, however, into synthetic biology’s celebration of rational design. Nor do they (...)
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  • Approaching the truth via belief change in propositional languages.Gustavo Cevolani & Francesco Calandra - 2009 - In M. Suàrez, M. Dorato & M. Rèdei (eds.), EPSA Epistemology and Methodology of Science: Launch of the European Philosophy of Science Association. Springer. pp. 47--62.
    Starting from the sixties of the past century theory change has become a main concern of philosophy of science. Two of the best known formal accounts of theory change are the post-Popperian theories of verisimilitude (PPV for short) and the AGM theory of belief change (AGM for short). In this paper, we will investigate the conceptual relations between PPV and AGM and, in particular, we will ask whether the AGM rules for theory change are effective means for approaching the truth, (...)
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  • Two Conceptions of Fundamentality.Mariam Thalos - 2011 - Philosophy of the Social Sciences 41 (2):151-177.
    This article aims to show that fundamentality is construed differently in the two most prominent strategies of analysis we find in physical science and engineering today: (1) atomistic, reductive analysis and (2) Systems analysis. Correspondingly, atomism is the conception according to which the simplest (smallest) indivisible entity of a certain kind is most fundamental; while systemism, as will be articulated here, is the conception according to which the bonds that structure wholes are most fundamental, and scale and/or constituting entities are (...)
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  • Two concepts of mechanism: Componential causal system and abstract form of interaction.Jaakko Kuorikoski - 2009 - International Studies in the Philosophy of Science 23 (2):143 – 160.
    Although there has been much recent discussion on mechanisms in philosophy of science and social theory, no shared understanding of the crucial concept itself has emerged. In this paper, a distinction between two core concepts of mechanism is made on the basis that the concepts correspond to two different research strategies: the concept of mechanism as a componential causal system is associated with the heuristic of functional decomposition and spatial localization and the concept of mechanism as an abstract form of (...)
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  • Emergence: logical, functional and dynamical. [REVIEW]Sandra D. Mitchell - 2012 - Synthese 185 (2):171-186.
    Philosophical accounts of emergence have been explicated in terms of logical relationships between statements (derivation) or static properties (function and realization). Jaegwon Kim is a modern proponent. A property is emergent if it is not explainable by (or reducible to) the properties of lower level components. This approach, I will argue, is unable to make sense of the kinds of emergence that are widespread in scientific explanations of complex systems. The standard philosophical notion of emergence posits the wrong dichotomies, confuses (...)
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  • (1 other version)Prediction in selectionist evolutionary theory.Rasmus Gr⊘Nfeldt Winther - 2009 - Philosophy of Science 76 (5):889-901.
    Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.
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