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  1. Objective data sets in qualitative research.Julie Zahle - forthcoming - Synthese:1-17.
    Qualitative researchers sometimes talk about objectivity in relation to qualitative data sets. In this paper, I defend a reconstructed notion of objective qualitative data sets that may serve as a useful and reachable guiding ideal in qualitative data generation. In the first part of the paper, I develop the ideal. According to it, a qualitative data set is objective to the extent that it, in conjunction with true assumptions, possesses a combination of good-making features in virtue of which the data (...)
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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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  • Arche-Writing and Data-Production in Theory-Oriented Scientific Practice: The Case of Free-Viewing as Experimental System to Test the Temporal Correlation Hypothesis.Juan Felipe Espinosa Cristia, Carla Fardella & Juan Manuel Garrido Wainer - 2021 - History and Philosophy of the Life Sciences 43 (2):1-27.
    Data production in experimental sciences depends on localised experimental systems, but the epistemic properties of data transcend the contingencies of the processes that produce them. Philosophers often believe that experimental systems instantiate but do not produce the epistemic properties of data. In this paper, we argue that experimental systems' local functioning entails intrinsic capacities to produce the epistemic properties of data. We develop this idea by applying Derrida's model of arche-writing to study a case of theory-oriented experimental practice. Derrida's model (...)
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  • Are bio-ontologies metaphysical theories?Oliver M. Lean - forthcoming - Synthese:1-22.
    Bio-ontologies are digital frameworks for handling biological and biomedical data. They consist of theoretical entities and relations with explicitly defined logical structures and precise definitions, whose purpose is to provide a shared language for representing information to be distributed and integrated across diverse scientific contexts. It is tempting to view bio-ontologies as clear and formal expressions of a scientific community’s ontological commitments about their domain of inquiry, and to view their integration as tantamount to the metaphysical unification of science that (...)
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  • Psychopathy: Morally Incapacitated Persons.Heidi Maibom - 2017 - In Thomas Schramme & Steven Edwards (eds.), Handbook of the Philosophy of Medicine. Dordrecht: Springer. pp. 1109-1129.
    After describing the disorder of psychopathy, I examine the theories and the evidence concerning the psychopaths’ deficient moral capacities. I first examine whether or not psychopaths can pass tests of moral knowledge. Most of the evidence suggests that they can. If there is a lack of moral understanding, then it has to be due to an incapacity that affects not their declarative knowledge of moral norms, but their deeper understanding of them. I then examine two suggestions: it is their deficient (...)
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  • ‘Models of’ and ‘Models For’: On the Relation Between Mechanistic Models and Experimental Strategies in Molecular Biology.Emanuele Ratti - 2018 - British Journal for the Philosophy of Science (2):773-797.
    Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. This (...)
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  • Open Data: Accountability and Transparency.Matthew S. Mayernik - 2017 - Big Data and Society 4 (2).
    The movements by national governments, funding agencies, universities, and research communities toward “open data” face many difficult challenges. In high-level visions of open data, researchers’ data and metadata practices are expected to be robust and structured. The integration of the internet into scientific institutions amplifies these expectations. When examined critically, however, the data and metadata practices of scholarly researchers often appear incomplete or deficient. The concepts of “accountability” and “transparency” provide insight in understanding these perceived gaps. Researchers’ primary accountabilities are (...)
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  • Critical Data Studies: An Introduction.Federica Russo & Andrew Iliadis - 2016 - Big Data and Society 3 (2).
    Critical Data Studies explore the unique cultural, ethical, and critical challenges posed by Big Data. Rather than treat Big Data as only scientifically empirical and therefore largely neutral phenomena, CDS advocates the view that Big Data should be seen as always-already constituted within wider data assemblages. Assemblages is a concept that helps capture the multitude of ways that already-composed data structures inflect and interact with society, its organization and functioning, and the resulting impact on individuals’ daily lives. CDS questions the (...)
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  • Algorithmic Rationality: Epistemology and Efficiency in the Data Sciences.Ian Lowrie - 2017 - Big Data and Society 4 (1).
    Recently, philosophers and social scientists have turned their attention to the epistemological shifts provoked in established sciences by their incorporation of big data techniques. There has been less focus on the forms of epistemology proper to the investigation of algorithms themselves, understood as scientific objects in their own right. This article, based upon 12 months of ethnographic fieldwork with Russian data scientists, addresses this lack through an investigation of the specific forms of epistemic attention paid to algorithms by data scientists. (...)
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  • Scientific Phenomena and Patterns in Data.Pascal Ströing - 2018 - Dissertation, LMU München
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  • Evaluating Evidential Pluralism in Epidemiology: Mechanistic Evidence in Exposome Research.Stefano Canali - 2019 - History and Philosophy of the Life Sciences 41 (1):4.
    In current philosophical discussions on evidence in the medical sciences, epidemiology has been used to exemplify a specific version of evidential pluralism. According to this view, known as the Russo–Williamson Thesis, evidence of both difference-making and mechanisms is produced to make causal claims in the health sciences. In this paper, I present an analysis of data and evidence in epidemiological practice, with a special focus on research on the exposome, and I cast doubt on the extent to which evidential pluralism (...)
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  • Reasoning, Science, and the Ghost Hunt.W. John Koolage & Timothy Hansel - 2017 - Teaching Philosophy 40 (2):201-229.
    This paper details how ghost hunting, as a set of learning activities, can be used to enhance critical thinking and philosophy of science classes. We describe in some detail our own work with ghost hunting, and reflect on both intended and unintended consequences of this pedagogical choice. This choice was partly motivated by students’ lack of familiarity with science and philosophic questions about it. We offer reflections on our three different implementations of the ghost hunting activities. In addition, we discuss (...)
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  • Epistemic Challenges: Engaging Philosophically in Cognitive Science.Przemysław R. Nowakowski - 2019 - Ruch Filozoficzny 75 (2):237.
    In this article, I show the role that the philosopher of cognitive science can cur-rently play in cognitive science research. I argue for the important, and not yet considered, role of the philosophy of cognitive science in cognitive science, that is, the importance of cooperation between philosophers of science with cogni-tive scientists in investigating the research methods and theoretical assump-tions of cognitive science. At the beginning of the paper I point out, how the philosopher of science, here, the philosopher of (...)
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  • Overcoming the Underdetermination of Specimens.Caitlin Wylie - 2019 - Biology and Philosophy 34 (2):24.
    Philosophers of science are well aware that theories are underdetermined by data. But what about the data? Scientific data are selected and processed representations or pieces of nature. What is useless context and what is valuable specimen, as well as how specimens are processed for study, are not obvious or predetermined givens. Instead, they are decisions made by scientists and other research workers, such as technicians, that produce different outcomes for the data. Vertebrate fossils provide a revealing case of this (...)
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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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  • Evidential Reasoning in Historical Sciences: Applying Toulmin Schemes to the Case of Archezoa.Thomas Bonnin - 2019 - Biology and Philosophy 34 (2):30.
    This article is a study of the role and use of evidence in the evaluation of claims in the historical sciences. In order to do this, I develop a “snapshot” approach to Toulmin schemas. This framework is applied to the case of Archezoa, an initially supported then eventually rejected hypothesis in evolutionary biology. From this case study, I criticize Cleland’s “smoking gun” account of the methodology of the historical sciences. I argue that Toulmin schemas are conceptually precise tools that allow (...)
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  • Between Scylla and Charybdis: Reconciling Competing Data Management Demands in the Life Sciences.Louise M. Bezuidenhout & Michael Morrison - 2016 - BMC Medical Ethics 17 (1):29.
    BackgroundThe widespread sharing of biological and biomedical data is recognised as a key element in facilitating translation of scientific discoveries into novel clinical applications and services. At the same time, twenty-first century states are increasingly concerned that this data could also be used for purposes of bioterrorism. There is thus a tension between the desire to promote the sharing of data, as encapsulated by the Open Data movement, and the desire to prevent this data from ‘falling into the wrong hands’ (...)
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  • Dark Data as the New Challenge for Big Data Science and the Introduction of the Scientific Data Officer.Björn Schembera & Juan M. Durán - 2019 - Philosophy and Technology:1-23.
    Many studies in big data focus on the uses of data available to researchers, leaving without treatment data that is on the servers but of which researchers are unaware. We call this dark data, and in this article, we present and discuss it in the context of high-performance computing facilities. To this end, we provide statistics of a major HPC facility in Europe, the High-Performance Computing Center Stuttgart. We also propose a new position tailor-made for coping with dark data and (...)
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