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  1. Big Data, epistemology and causality: Knowledge in and knowledge out in EXPOsOMICS.Stefano Canali - 2016 - Big Data and Society 3 (2).
    Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal knowledge is necessary for (...)
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  • Bacterial species pluralism in the light of medicine and endosymbiosis.Javier Suárez - 2016 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 31 (1):91-105.
    This paper aims to offer a new argument in defence bacterial species pluralism. To do so, I shall first present the particular issues derived from the conflict between the non-theoretical understanding of species as units of classification and the theoretical comprehension of them as units of evolution. Secondly, I shall justify the necessity of the concept of species for the bacterial world, and show how medicine and endosymbiotic evolutionary theory make use of different concepts of bacterial species due to their (...)
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  • Complexity begets crosscutting, dooms hierarchy.Joyce C. Havstad - 2021 - Synthese 198 (8):7665-7696.
    There is a perennial philosophical dream of a certain natural order for the natural kinds. The name of this dream is ‘the hierarchy requirement’. According to this postulate, proper natural kinds form a taxonomy which is both unique and traditional. Here I demonstrate that complex scientific objects exist: objects which generate different systems of scientific classification, produce myriad legitimate alternatives amongst the nonetheless still natural kinds, and make the hierarchical dream impossible to realize, except at absurdly great cost. Philosophical hopes (...)
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  • Fuzzy-set representation and processing of fuzzy images: non-linguistic vagueness as representation, approximation and scientific practice.Jordi Cat - 2015 - Archives for the Philosophy and History of Soft Computing 2015 (1).
    This is the first part of a two-part paper in which I conclude the process, initiated elsewhere, of tracking objective conditions of vagueness of representation from language to pictures, from philosophy to imaging science, from vagueness to approximation, from representation to reasoning, with a focus on the application of fuzzy set theory and its challenges.
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  • Building Simulations from the Ground Up: Modeling and Theory in Systems Biology.Miles MacLeod & Nancy J. Nersessian - 2013 - Philosophy of Science 80 (4):533-556.
    In this article, we provide a case study examining how integrative systems biologists build simulation models in the absence of a theoretical base. Lacking theoretical starting points, integrative systems biology researchers rely cognitively on the model-building process to disentangle and understand complex biochemical systems. They build simulations from the ground up in a nest-like fashion, by pulling together information and techniques from a variety of possible sources and experimenting with different structures in order to discover a stable, robust result. Finally, (...)
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  • Evidence in Neuroimaging: Towards a Philosophy of Data Analysis.Jessey Wright - 2017 - Dissertation, The University of Western Ontario
    Neuroimaging technology is the most widely used tool to study human cognition. While originally a promising tool for mapping the content of cognitive theories onto the structures of the brain, recently developed tools for the analysis, handling and sharing of data have changed the theoretical landscape of cognitive neuroscience. Even with these advancements philosophical analyses of evidence in neuroimaging remain skeptical of the promise of neuroimaging technology. These views often treat the analysis techniques used to make sense of data produced (...)
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  • Taxa hold little information about organisms: Some inferential problems in biological systematics.Thomas A. C. Reydon - 2019 - History and Philosophy of the Life Sciences 41 (4):40.
    The taxa that appear in biological classifications are commonly seen as representing information about the traits of their member organisms. This paper examines in what way taxa feature in the storage and retrieval of such information. I will argue that taxa do not actually store much information about the traits of their member organisms. Rather, I want to suggest, taxa should be understood as functioning to localize organisms in the genealogical network of life on Earth. Taxa store information about where (...)
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