Preprint

Allen, Colin and Murdock, Jaimie (2020) LDA Topic Modeling: Contexts for the History & Philosophy of Science. [Preprint]

Alvarado, Ramón (2022) AI as an Epistemic Technology. [Preprint]

Andrews, Mel (2023) The Devil in the Data: Machine Learning & the Theory-Free Ideal. [Preprint]

Antoniou, Antonis (2021) What is a data model? An anatomy of data analysis in High Energy Physics. [Preprint]

Bocchi, Federica and Bokulich, Alisa and Castillo Brache, Leticia and Grand-Pierre, Gloria and Watkins, Aja (2022) Are We in a Sixth Mass Extinction? The Challenges of Answering and Value of Asking. [Preprint]

Bokulich, Alisa (2019) Calibration, Coherence, and Consilience in Radiometric Measures of Geologic Time. [Preprint]

Bokulich, Alisa (2019) Towards a Taxonomy of the Model-Ladenness of Data. [Preprint]

Bokulich, Alisa (2018) Using Models to Correct Data: Paleodiversity and the Fossil Record. [Preprint]

Bokulich, Alisa and Bocchi, Federica (2022) Kuhn’s ‘5th Law of Thermodynamics’: Measurement, Data, and Anomalies. [Preprint]

Bokulich, Alisa and Parker, Wendy (2021) Data Models, Representation, and Adequacy-for-Purpose. [Preprint]

Bonnin, Thomas (2019) Evidential Reasoning in the Historical Sciences: Applying Toulmin Schemas to the case of Archezoa. [Preprint]

Boon, Mieke (2020) The role of disciplinary perspectives in an epistemology of scientific models. [Preprint]

Boyd, Nora Mills (2018) Evidence Enriched. [Preprint]

Browning, Heather and Veit, Walter (2023) Animal Welfare Science, Performance Metrics, and Proxy Failure: A Commentary on John et al. [Preprint]

Buchholz, Oliver (2023) The Deep Neural Network Approach to the Reference Class Problem. [Preprint]

Bystranowski, Piotr and Dranseika, Vilius and Żuradzki, Tomasz (2022) The Disconnection That Wasn't: Philosophy in Modern Bioethics from a Quantitative Perspective. [Preprint]

Canali, Stefano (2023) Which Integration for Health? Comparing Integrative Approaches for Epidemiology. [Preprint]

Canali, Stefano and Ratti, Emanuele (2023) Between quantity and quality: competing views on the role of Big Data for causal inference. [Preprint]

Climenhaga, Nevin and DesAutels, Lane and Ramsey, Grant (2019) Causal Inference from Noise. [Preprint]

Curiel, Erik (2018) Framework Confirmation by Newtonian Abduction. [Preprint]

Curiel, Erik (2019) Framework Confirmation by Newtonian Abduction. [Preprint]

Curiel, Erik (2020) Schematizing the Observer and the Epistemic Content of Theories. [Preprint]

Currie, Adrian (2019) Paleobiology and Philosophy. [Preprint]

Currie, Adrian (2020) Stepping Forwards by Looking Back: Underdetermination, Epistemic Scarcity & Legacy Data. [Preprint]

Céspedes, Esteban and Fuentes, Miguel (2019) Effective complexity: In which sense is it informative? [Preprint]

De Baerdemaeker, Siska and Boyd, Nora Mills (2020) Jump Ship, Shift Gears, or Just Keep on Chugging: Assessing the Responses to Tensions between Theory and Evidence in Contemporary Cosmology. [Preprint]

De Haro, Sebastian (2020) Book Review: Visual Representations in Science. [Preprint]

Dellsén, Finnur (2021) An Epistemic Advantage of Accommodation over Prediction. [Preprint]

Elder, Jamee (2024) Independent Evidence in Multi-messenger Astrophysics. [Preprint]

Elder, Jamee (2023) On the “Direct Detection” of Gravitational Waves. [Preprint]

Elliott, Steve and MacCord, Kate and Maienschein, Jane (2021) Help with Data Management for the Novice and Experienced Alike. [Preprint]

Esanu, Andreea (2024) Scrutinizing the foundations: could large Language Models be solipsistic? [Preprint]

Evangelidis, Basil (2023) Impacts, symmetries and decisions: the quest for habitable worlds. [Preprint]

Facchini, Alessandro and Termine, Alberto (2022) Towards a Taxonomy for the Opacity of AI Systems. [Preprint]

Facchini, Alessandro and Termine, Alberto (2021) Towards a Taxonomy of Pragmatic Opacity. [Preprint]

Feest, Uljana (2023) What is the Replication Crisis a Crisis Of? [Preprint]

Fletcher, Samuel C. and Jones, Galin and Rothman, Alexander (2021) Discussion: What Is a Replication? [Preprint]

Frigg, Roman and Nguyen, James (2017) Models and Representation. [Preprint]

Gardiner, Georgi and Zaharatos, Brian (2022) The Safe, the Sensitive, and the Severely Tested: A Unified Account. [Preprint]

Garrido Wainer, Juan Manuel and Fardella Cisternas, Carla and Espinosa Cristia, Juan Felipe (2021) Arche-writing and data production in theory-oriented scientific practice. The case of free-viewing as experimental system to test the temporal correlation hypothesis. [Preprint]

Green, Sara and Hillersdal, Line and Holt, Jette and Hoeyer, Klaus and Wadmann, Sarah (2022) The practical ethics of repurposing health data: how to acknowledge invisible data work and the need for prioritization. [Preprint]

Guralp, Genco (2020) Calibrating the Universe: the Beginning and End of the Hubble Wars. [Preprint]

Guralp, Genco (2020) The Evidence for the Accelerating Universe: Endorsement and Robust Consistency. [Preprint]

Guttinger, Stephan and Love, Alan C. (2020) modENCODE and the elaboration of functional genomic methodology. [Preprint]

Han, HyeJeong (2023) Taking model pursuit seriously. [Preprint]

Healey, Richard A. (2021) Scientific Objectivity and its Limits. [Preprint]

Jacoby, Franklin (2020) Data Identity and Perspectivism. [Preprint]

Johnson, Gabbrielle (2020) Algorithmic Bias: On the Implicit Biases of Social Technology. [Preprint]

Jones, Elizabeth (2019) Ancient Genetics to Ancient Genomics: Celebrity and Credibility in Data-Driven Practice. [Preprint]

Karaca, Koray (2017) Lessons from the Large Hadron Collider for model-based experimentation: The concept of a model of data acquisition and the scope of the hierarchy of models. [Preprint]

Khalifa, Kareem and Goldberg, Sanford (2023) Socio-Functional Foundations In Science: The Case Of Measurement. [Preprint]

Kostic, Daniel and Halffman, Willem (2023) Mapping Explanatory Language in Neuroscience. [Preprint]

Kostic, Daniel and Hilgetag, Claus and Tittgemeyer, Marc (2020) Unifying the essential concepts of biological networks: biological insights and philosophical foundations. [Preprint]

Kästner, Lena and Crook, Barnaby (2023) Explaining AI Through Mechanistic Interpretability. [Preprint]

Lean, Oliver M (2021) Are Bio-ontologies Metaphysical Theories? [Preprint]

Leonelli, Sabina (2023) Is Data Science Transforming Biomedical Research? Evidence, Expertise and Experiments in COVID-19 Science. [Preprint]

Leonelli, Sabina (2018) Re-Thinking Reproducibility as a Criterion for Research Quality. [Preprint]

Leonelli, Sabina (2017) The Time of Data: Time-Scales of Data Use in the Life Sciences. [Preprint]

Leonelli, Sabina (2018) What Distinguishes Data from Models? [Preprint]

Leonelli, Sabina and Tempini, Niccolo (2018) Where Health and Environment Meet: The Use of Invariant Parameters for Big Data Analysis. [Preprint]

López-Rubio, Ezequiel (2020) The Big Data razor. [Preprint]

MARTINEZ ORDAZ, MARIA DEL ROSARIO (2023) Scientific understanding through big data: From ignorance to insights to understanding. [Preprint]

Machery, Edouard (2021) A mistaken confidence in data. [Preprint]

Martínez-Ordaz, María del Rosario (2021) Is there anything special about the ignorance involved in big data practices? [Preprint]

Matthiessen, Dana (2022) Empirical Techniques and the Accuracy of Scientific Representations. [Preprint]

Mizrahi, Moti (2019) The Case Study Method in Philosophy of Science: An Empirical Study. [Preprint]

Mizrahi, Moti (2020) Conceptions of Scientific Progress in Scientific Practice: An Empirical Study. [Preprint]

Mizrahi, Moti (2020) Hypothesis Testing in Scientific Practice: An Empirical Study. [Preprint]

Mizrahi, Moti (2020) Proof, Explanation, and Justification in Mathematical Practice. [Preprint]

Mizrahi, Moti (2020) Theoretical Virtues in Scientific Practice: An Empirical Study. [Preprint]

Mizrahi, Moti (2021) What is the Basic Unit of Scientific Progress? A Quantitative, Corpus-Based Study. [Preprint]

Mizrahi, Moti (2017) What’s so bad about Scientism? [Preprint]

Mizrahi, Moti and Dickinson, Mike (2022) Is Philosophy Exceptional? A Corpus-Based, Quantitative Study. [Preprint]

Mizrahi, Moti and Dickinson, Mike (2022) Philosophical Reasoning about Science: A Quantitative, Digital Study. [Preprint]

Mussgnug, Alexander (2022) The Predictive Reframing of Machine Learning Applications: Good Predictions and Bad Measurements. [Preprint]

Noichl, Maximilian (2023) How localized are computational templates? A machine learning approach. [Preprint]

Northcott, Robert (2019) Big data and prediction: four case studies. [Preprint]

Pence, Charles H. and Ramsey, Grant (2018) How to do digital philosophy of science. [Preprint]

Pietsch, Wolfgang (2017) A Causal Approach to Analogy. [Preprint]

Plutynski, Anya (2021) The Cancer Genome Atlas Project: Natural History, Experiment, or Something In-Between? [Preprint]

Ratti, Emanuele and Stoeger, Thomas (2021) Large-scale Biology: Philosophical, Historical, and Computational Perspectives. [Preprint]

Reuter, Kevin and Baumgartner, Lucien and Willemsen, Pascale (2022) Tracing Thick and Thin Concepts Through Corpora. [Preprint]

Reutlinger, Alexander (2020) What is Epistemically Wrong with Research Affected by Sponsorship Bias? The Evidential Account. [Preprint]

Rochefort-Maranda, Guillaume (2017) The Principle of Total Evidence and Classical Statistical Tests. [Preprint]

Rochefort-Maranda, Guillaume (2013) Statistical Power and P-values: An Epistemic Interpretation Without Power Approach Paradoxes. [Preprint]

Rubin, Mark (2024) Type I Error Rates are Not Usually Inflated. [Preprint]

Räz, Tim (2020) Understanding Deep Learning With Statistical Relevance. [Preprint]

Schubbach, Arno (2019) Judging Machines. Philosophical Aspects of Deep Learning. [Preprint]

Sterner, Beckett and Elliott, Steve (2023) How Data Governance Principles Influence Participation in Biodiversity Science. [Preprint]

Sterner, Beckett and Elliott, Steve and Gilbert, Ed and Franz, Nico (2020) Data Integration without Unification. [Preprint]

Sterner, Beckett and Witteveen, Joeri and Franz, Nico (2019) Alternatives to Realist Consensus in Bio-Ontologies: Taxonomic Classification as a Basis for Data Discovery and Integration. [Preprint]

Sullivan, Emily (2022) Inductive Risk, Understanding, and Opaque Machine Learning Models. [Preprint]

Suñé, Abel and Martínez, Manolo (2019) Real patterns and indispensability. [Preprint]

Tempini, N and Leonelli, Sabina (2018) Concealment and Discovery: The Role of Information Security in Biomedical Data Re-Use. [Preprint]

Trappes, Rose (2023) Data Synthesis for Big Questions: From Animal Tracks to Ecological Models. [Preprint]

Wylie, Caitlin D. (2019) Overcoming the underdetermination of specimens. [Preprint]

Yee, Adrian K. (2023) Machine Learning, Misinformation, and Citizen Science. [Preprint]

Zach, Martin (2022) A Complementary Account of Scientific Modelling: Modelling Mechanisms in Cancer Immunology. [Preprint]

Conference or Workshop Item

Lawler, Insa and Zimmermann, Georg (2019) Misalignment between research hypotheses and statistical hypotheses – A threat to evidence-based medicine? In: UNSPECIFIED.

Napoletani, Domenico and Panza, Marco and Struppa, Daniele (2018) The Agnostic Structure of Data Science Methods. In: UNSPECIFIED.

Ray, Faron (2022) Two Types of Explainability for Machine Learning Models. In: UNSPECIFIED.

Rosenstock, Sarita (2020) Learning from the Shape of Data. In: UNSPECIFIED.

Souto-Maior, Caetano (2022) Extraordinarily corrupt or statistically commonplace? Reproducibility crises may stem from a lack of understanding of outcome probabilities. In: UNSPECIFIED.

Sprenger, Jan and Stegenga, Jacob (2017) Three Arguments for Absolute Outcome Measures. In: UNSPECIFIED.

Waszek, David and Imbert, Cyrille (2022) Are larger studies always better? Sample size and data pooling effects in research communities. In: UNSPECIFIED.

Weinberger, Naftali (2022) The Insufficiency of Statistics for Detecting Racial Discrimination by Police. In: UNSPECIFIED.

Published Article or Volume

Barton, Adrien and Rosier, Arnaud (2016) Ontologies appliquées biomédicales et ontologie philosophique : un développement complémentaire. Lato Sensu, revue de la Société de philosophie des sciences, 3 (1). pp. 1-8. ISSN 2295-8029

Cabrera, Frank (2020) Correlation Isn’t Good Enough: Causal Explanation and Big Data. Metascience. ISSN 0815-0796

Cabrera, Frank (2020) The Fate of Explanatory Reasoning in the Age of Big Data. Philosophy and Technology.

Canali, Stefano (2022) A Pragmatic Approach to Scientific Change: Transfer, Alignment, Influence. European Journal for Philosophy of Science, 12 (48). ISSN 1879-4912

Canali, Stefano and Leonelli, Sabina (2022) Reframing the Environment in Data-Intensive Health Sciences. Studies in History and Philosophy of Science, 93. pp. 203-214. ISSN 00393681

Canali, Stefano and Piroddi, Corrado (2021) Introduction: The philosophy, ethics, and politics of epidemiology today. MEFISTO. Rivista di Medicina, Filosofia, Storia, 5 (1). pp. 55-64. ISSN 2532-8255

Canali, Stefano and Schiaffonati, Viola and Aliverti, Andrea (2022) Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness. PLOS Digital Health, 1 (10).

Ding, Chao and Liu, Chuang (2022) Kripke’s Gödel case: Descriptive ambiguity and its experimental interpretation. THEORIA. An International Journal for Theory, History and Foundations of Science, 37 (3). pp. 291-308. ISSN 2171-679X

Fletcher, Samuel C. (2021) How (not) to measure replication. European Journal for Philosophy of Science, 11 (57). pp. 1-27. ISSN 1879-4912

Fletcher, Samuel C. (2019) Of War or Peace? Essay Review of Statistical Inference as Severe Testing. Philosophy of Science, 87 (4). ISSN 1539-767X

Frapolli, Maria J. and San Ginés, Aránzazu (2017) Stop beating the donkey! A fresh interpretation of conditional donkey sentences. THEORIA. An International Journal for Theory, History and Foundations of Science, 32 (1). pp. 7-24. ISSN 2171-679X

Graves, Mark and Ratti, Emanuele (2022) Who Is a Good Data Scientist? A Reply to Curzer and Epstein. Philosophy & Technology, 35.

Jurjako, Marko and Malatesti, Luca and Brazil, Inti (2018) Some Ethical Considerations About the Use of Biomarkers for the Classification of Adult Antisocial Individuals. International Journal of Forensic Mental Health. ISSN 1499-9013

Karaca, Koray (2018) Two Senses of Experimental Robustness: Result Robustness and Procedure Robustness. The British Journal for the Philosophy of Science.

Kubiak, Adam P. and Kawalec, Paweł (2022) Prior Information in Frequentist Research Designs: The Case of Neyman’s Sampling Theory. Journal for General Philosophy of Science. ISSN 0925-4560

Larroulet Philippi, Cristian (2021) Valid for What? On the Very Idea of Unconditional Validity. Philosophy of the Social Sciences, 51 (2). pp. 151-175.

Leonelli, Sabina (2021) Data Science in Times of Pan(dem)ic. Harvard Data Science Review.

Leonelli, Sabina (2022) Process-Sensitive Naming: Trait Descriptors and the Shifting Semantics of Plant (Data) Science. Philosophy, theory and practice in biology, 14.

Napoletani, Domenico and Panza, Marco and Struppa, Daniele (2021) The Agnostic Structure of Data Science Methods. Lato Sensu, revue de la Société de philosophie des sciences, 8 (2). pp. 44-57. ISSN 2295-8029

Nguyen, James (2016) On the Pragmatic Equivalence between Representing Data and Phenomena. Philosophy of Science, 83 (2). pp. 171-191.

Plutniak, Sébastien (2020) The Effects of Publishing Processes on Scientific Thought. Typography and Typology in Prehistoric Archaeology (1950s–1990s). Science in Context, 33 (3). pp. 273-297. ISSN 1474-0664

Pérez Otero, Manuel (2017) Theories of Reference, Experimental Philosophy, and the Calibration of Intuitions. THEORIA. An International Journal for Theory, History and Foundations of Science, 32 (1). pp. 41-62. ISSN 2171-679X

Ratti, Emanuele (2020) Big Data in the Experimental Life Sciences. Metascience. ISSN 0815-0796

Ratti, Emanuele and Graves, Mark (2021) Cultivating Moral Attention: A Virtue-oriented Approach to Responsible Data Science in Healthcare. Philosophy & Technology.

Ratti, Emanuele and Graves, Mark (2022) Explainable machine learning practices: opening another black box for reliable medical AI. AI and Ethics.

Rochefort-Maranda, Guillaume (2016) How we load our data sets with theories and why we do so purposefully. Studies in History and Philosophy of Science Part A.

Rochefort-Maranda, Guillaume (2016) Simplicity and model selection. European Journal for Philosophy of Science. ISSN 1879-4912

Rubin, Mark (2020) Does preregistration improve the credibility of research findings? The Quantitative Methods in Psychology, 16 (4). pp. 376-390.

Räz, Tim (2024) ML interpretability: Simple isn't easy. Studies in History and Philosophy of Science. ISSN 00393681

Räz, Tim (2023) Methods for identifying emergent concepts in deep neural networks. Patterns, 4. pp. 1-7.

Sullivan, Emily (2022) Link Uncertainty, Implementation, and ML Opacity: A Reply to Tamir and Shech. Scientific Understanding and Representation (Eds) Insa Lawler, Kareem Khalifa & Elay Shech. pp. 341-345.

Vessonen, Elina (2018) The Complementarity of Psychometrics and the Representational Theory of Measurement. The British Journal for the Philosophy of Science.

Votsis, Ioannis (2016) Ad Hoc Hypotheses and the Monsters within. Fundamental Issues of Artificial Intelligence. pp. 299-313.

Votsis, Ioannis (2014) Objectivity in Confirmation: Post Hoc Monsters and Novel Predictions. Studies in History and Philosophy of Science, 45 (1). pp. 70-78.

Votsis, Ioannis (2016) Philosophy of Science and Information. The Routledge Handbook of Philosophy of Information. pp. 249-262.

Ward, Zina B. (2022) Cognitive Variation: The Philosophical Landscape. Philosophy Compass.

Ward, Zina B. (2019) Registration Pluralism and the Cartographic Approach to Data Aggregation Across Brains. The British Journal for the Philosophy of Science. ISSN 1464-3537

Open Access Book

Leonelli, Sabina and Tempini, N (2020) Data Journeys in the Sciences. Springer.

Williamson, Hugh and Leonelli, Sabina (2022) Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development. UNSPECIFIED.