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  1. Data quality, experimental artifacts, and the reactivity of the psychological subject matter.Uljana Feest - 2022 - European Journal for Philosophy of Science 12 (1):1-25.
    While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what are (...)
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  • Data Journeys in the Sciences.Sabina Leonelli & Niccolò Tempini (eds.) - 2020 - Springer.
    This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, challenges and concerns involved in (...)
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  • Radiocarbon Dating in Archaeology: Triangulation and Traceability.Alison Wylie - 2020 - In Sabina Leonelli & Niccolò Tempini (eds.), Data Journeys in the Sciences. Springer. pp. 285-301.
    When radiocarbon dating techniques were applied to archaeological material in the 1950s they were hailed as a revolution. At last archaeologists could construct absolute chronologies anchored in temporal data backed by immutable laws of physics. This would make it possible to mobilize archaeological data across regions and time-periods on a global scale, rendering obsolete the local and relative chronologies on which archaeologists had long relied. As profound as the impact of 14C dating has been, it has had a long and (...)
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  • Are bio-ontologies metaphysical theories?Oliver M. Lean - 2021 - Synthese 199 (3-4):11587-11608.
    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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  • 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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  • Objective data sets in qualitative research.Julie Zahle - 2020 - Synthese 199 (1-2):101-117.
    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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  • (1 other version)Dark Data as the New Challenge for Big Data Science and the Introduction of the Scientific Data Officer.Björn Schembera & Juan M. Durán - 2020 - Philosophy and Technology 33 (1):93-115.
    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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  • 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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  • Evidence Enriched.Nora Mills Boyd - 2018 - Philosophy of Science 85 (3):403-421.
    Traditionally, empiricism has relied on the specialness of human observation, yet science is rife with sophisticated instrumentation and techniques. The present article advances a conception of empirical evidence applicable to actual scientific practice. I argue that this conception elucidates how the results of scientific research can be repurposed across diverse epistemic contexts: it helps to make sense of how evidence accumulates across theory change, how different evidence can be amalgamated and used jointly, and how the same evidence can be used (...)
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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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  • Crystallizing techniques: sample preparations, technical knowledge, and the characterization of blood crystals, 1840–1909.Dana Matthiessen - 2025 - History and Philosophy of the Life Sciences 47 (1):1-32.
    Sample preparation is the process of altering a naturally occurring object into a representative form that is amenable to scientific inquiry. Preparation is an important preliminary to data collection, ubiquitous in the life sciences and elsewhere, yet relatively neglected in historical and philosophical literature. This paper presents a detailed historical case study involving the preparation and study of blood crystals in the nineteenth century. The case is used to highlight significant features of preparation, which aid our understanding of the epistemology (...)
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  • Value Capture.Christopher Nguyen - 2024 - Journal of Ethics and Social Philosophy 27 (3).
    Value capture occurs when an agent’s values are rich and subtle; they enter a social environment that presents simplified — typically quantified — versions of those values; and those simplified articulations come to dominate their practical reasoning. Examples include becoming motivated by FitBit’s step counts, Twitter Likes and Re-tweets, citation rates, ranked lists of best schools, and Grade Point Averages. We are vulnerable to value capture because of the competitive advantage that such crisp and clear expressions of value have in (...)
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  • Is Data Labor? Two Conceptions of Work and the User-Platform Relationship.Julian David Jonker - forthcoming - Business Ethics Quarterly:1-34.
    Some observers of the data economy have proposed that we treat data as labor. But are data contributions labor? Our folk conception of work emphasizes its importance and effort, such that work has a special interpersonal priority and deserves appreciation and compensation. The folk conception does not generally favor counting data as work, and so it serves as an error theory for reluctance to regulate data as labor. In contrast, labor regulation and policy focus on the political economy of labor, (...)
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  • Collecting human remains in nineteenth-century Paris: the case of the Société Anatomique de Paris and the Musée Dupuytren.Juliette Ferry-Danini - 2023 - History and Philosophy of the Life Sciences 45 (4):1-25.
    This paper describes the scientific practices of the anatomists from the Société Anatomique de Paris (1803–1873) who were collecting anatomical and pathological specimens in Nineteenth-Century Paris and which led to the building of the anatomy and pathology Musée Dupuytren (1835–2016). The framework introduced by Robert Kohler to describe collecting sciences (2007) is useful as a tool to identify the set of diverse practices within pathological anatomy in nineteenth-century Paris. However, I will argue that anatomy and pathology collecting had specific features (...)
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  • Using Paleoclimate Analogues to Inform Climate Projections.Aja Watkins - 2024 - Perspectives on Science 32 (4):415-459.
    Philosophers of science have paid close attention to climate simulations as means of projecting the severity and effects of climate change, but have neglected the full diversity of methods in climate science. This paper shows the philosophical richness of another method in climate science: the practice of using paleoclimate analogues to inform our climate projections. First, I argue that the use of paleoclimate analogues can offer important insights to philosophers of the historical sciences. Rather than using the present as a (...)
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  • COVID-19 Heightens the Imperative to Decolonize Global Health Research.Caesar Alimsinya Atuire & Susan Bull - 2022 - Global Justice: Theory Practice Rhetoric 13 (2):60-77.
    The COVID-19 pandemic has both highlighted and exacerbated global health inequities, leading for calls for responses to COVID to promote social justice and ensure that no one is left behind. One key lesson to be learnt from the pandemic is the critical importance of decolonizing global health and global health research so that African countries are better placed to address pandemic challenges in contextually relevant ways. This paper argues that to be successful, programmes of decolonization in complex global health landscapes (...)
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  • Data identity and perspectivism.Franklin Jacoby - 2020 - Synthese 198 (12):11695-11711.
    This paper uses several case studies to suggest that (1) two prominent definitions of data do not on their own capture how scientists use data and (2) a novel perspectival account of data is needed. It then outlines some key features of what this account could look like. Those prominent views, the relational and representational, do not fully capture what data are and how they function in science. The representational view is insensitive to the scientific context in which data are (...)
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  • Overcoming the underdetermination of specimens.Caitlin Donahue 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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  • The Time of Data: Timescales of Data Use in the Life Sciences.Sabina Leonelli - 2018 - Philosophy of Science 85 (5):741-754.
    This article considers the temporal dimension of data processing and use and the ways in which it affects the production and interpretation of knowledge claims. I start by distinguishing the time at which data collection, dissemination, and analysis occur from the time in which the phenomena for which data serve as evidence operate. Building on the analysis of two examples of data reuse from modeling and experimental practices in biology, I then argue that Dt affects how researchers select and interpret (...)
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  • The quantification of intelligence in nineteenth-century craniology: an epistemology of measurement perspective.Michele Luchetti - 2022 - European Journal for Philosophy of Science 12 (4):1-29.
    Craniology – the practice of inferring intelligence differences from the measurement of human skulls – survived the dismissal of phrenology and remained a widely popular research program until the end of the nineteenth century. From the 1970s, historians and sociologists of science extensively focused on the explicit and implicit socio-cultural biases invalidating the evidence and claims that craniology produced. Building on this literature, I reassess the history of craniological practice from a different but complementary perspective that relies on recent developments (...)
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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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  • ‘Models of’ and ‘Models for’: On the Relation between Mechanistic Models and Experimental Strategies in Molecular Biology.Emanuele Ratti - 2020 - British Journal for the Philosophy of Science 71 (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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  • 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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  • Psychopathy: Morally Incapacitated Persons.Heidi Maibom - 2017 - In Thomas Schramme & Steven Edwards (eds.), Handbook of the Philosophy of Medicine. 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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  • Race and indigeneity in human microbiome science: microbiomisation and the historiality of otherness.Andrea Núñez Casal - 2024 - History and Philosophy of the Life Sciences 46 (2):1-27.
    This article reformulates Stephan Helmreich´s the ¨microbiomisation of race¨ as the historiality of otherness in the foundations of human microbiome science. Through the lens of my ethnographic fieldwork of a transnational community of microbiome scientists that conducted a landmark human microbiome research on indigenous microbes and its affiliated and first personalised microbiome initiative, the American Gut Project, I follow and trace the key actors, experimental systems and onto-epistemic claims in the emergence of human microbiome science a decade ago. In doing (...)
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  • Tasks in cognitive science: mechanistic and nonmechanistic perspectives.Samuel D. Taylor - forthcoming - Phenomenology and the Cognitive Sciences:1-27.
    A tension exists between those who do—e.g. Meyer (The British Journal for the Philosophy of Science 71:959–985, 2020 ) and Chemero ( 2011 )—and those who do not—e.g. Kaplan and Craver (Philosophy of Science 78:601–627, 2011 ) Piccinini and Craver (Synthese 183:283–311, 2011 )—afford nonmechanistic explanations a role in cognitive science. Here, I argue that one’s perspective on this matter will cohere with one’s interpretation of the tasks of cognitive science; that is, of the actions for which cognitive scientists are (...)
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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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  • Simulated Data in Empirical Science.Aki Lehtinen & Jani Raerinne - forthcoming - Foundations of Science:1-22.
    This paper provides the first systematic epistemological account of simulated data in empirical science. We focus on the epistemic issues modelers face when they generate simulated data to solve problems with empirical datasets, research tools, or experiments. We argue that for simulated data to count as epistemically reliable, a simulation model does not have to mimic its target. Instead, some models take empirical data as a target, and simulated data may successfully mimic such a target even if the model does (...)
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  • Reactivity and good data in qualitative data collection.Julie Zahle - 2023 - European Journal for Philosophy of Science 13 (1):1-18.
    Reactivity in qualitative data collection occurs when a researcher generates data about a situation with reactivity, that is, a situation in which the ongoing research affects the research participants such that they, say, diverge from their routines when the researcher is present, or tell the researcher what they think she wants to hear. In qualitative research, there are two basic approaches to reactivity. The traditional position maintains that data should ideally be collected in situations without any reactivity. In other words, (...)
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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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  • (1 other version)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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  • 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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  • What is a data model?: An anatomy of data analysis in high energy physics.Antonis Antoniou - 2021 - European Journal for Philosophy of Science 11 (4):1-33.
    Many decades ago Patrick Suppes argued rather convincingly that theoretical hypotheses are not confronted with the direct, raw results of an experiment, rather, they are typically compared with models of data. What exactly is a data model however? And how do the interactions of particles at the subatomic scale give rise to the huge volumes of data that are then moulded into a polished data model? The aim of this paper is to answer these questions by presenting a detailed case (...)
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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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  • 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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