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About this topic
Summary In Philosophy of Science, 'scientific practice' refers to activities whose aim is the achievement of scientific goals. More specifically, the category of scientific practice covers everything scientists do when they engage in the production of scientific knowledge. These activities include discovering, experimenting, measuring, modeling, observing, predicting, simulating, and so on, as well as using instruments in the pursuit of scientific goals. In recent years, there has been a shift in Philosophy of Science from an emphasis on scientific theories to an emphasis on actual scientific practices (see, for example, the mission statement of the Society for Philosophy of Science in Practice at
Key works Some key works include Kuhn 1962, Hacking 1983, Longino 1990, Solomon 1994, Wylie 2002, Baird 2002, Chang 2004, and Douglas 2009.
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3454 found
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  1. Allan Franklin, Right or Wrong.Robert Ackermann - 1990 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1990:451-457.
    Franklin and Pickering agree that scientists in an experimental sequence, like the one to be discussed here, choose to accept certain experiments and their results as crucial, but disagree as to whether such choice can be justified in terms of an on-line estimate of evidential reliability. This paper suggests that it is possible to define a position between Franklin 's Bayesian objectivism and Pickering's social constructivism. This position depends on considering the sequence of improvement in material technique and instrumentation as (...)
  2. Book Review:An Introduction to Scientific Research E. Bright Wilson, Jr. [REVIEW]Russel L. Ackoff - 1954 - Philosophy of Science 21 (4):354-.
  3. Editorial: Formal and Informal Representations of Science. [REVIEW]Diederik Aerts, Jan Broekaert & Liane Gabora - 1999 - Foundations of Science 4 (1):1-2.
  4. III. The Cheapening of Science∗.Joseph Agassi - 1984 - Inquiry: An Interdisciplinary Journal of Philosophy 27 (1-4):166-172.
  5. Between Science and Technology.Joseph Agassi - 1980 - Philosophy of Science 47 (1):82-99.
    Basic research or fundamental research is distinct from both pure and applied research, in that it is pure research with expected useful results. The existence of basic or fundamental research is problematic, at least for both inductivists and instrumentalists, but also for Popper. Assuming scientific research to be the search for explanatory conjectures and for refutations, and assuming technology to be the search of conjectures and some corroborations, we can easily place basic or fundamental research between science and technology as (...)
  6. No More Discovery in Physics? [REVIEW]Joseph Agassi - 1968 - Synthese 18 (1):103-108.
  7. Discussion: Analogies as Generalizations.Joseph Agassi - unknown
    Analogies have been traditionally recognized as a proper part of inductive procedures, akin to generalizations. Seldom, however, have they been presented as superior to generalizations, in the attainability of a higher degree of certitude for their conclusions or in other respects. Though Bacon definitely preferred analogy to generalization1, the tradition seems to me to go the other way-until the recent publication of works by Mary B. Hesse ([2], pp.21-28 and passim) and, perhaps, R. Harr6 ([1], pp.23-28 and passim). The aim (...)
  8. Rethinking Philosophy of Science Today.Evandro Agazzi - 2012 - Journal of Philosophical Research 37 (Supplement):85-101.
    Modern philosophy of science was, initially, an epistemology of science based on the logical analysis of the language of science. It was superseded by a “sociological epistemology,” according to which the acceptance of scientific statements and theories depends on conditioningscoming from the social context and powers, and this view has fueled anti-scientific attitudes.This happened because the sociological turn still expressed an epistemology of science. Science, however, is not only a system of knowledge, but also a complex human activity. Hence, ethical, (...)
  9. Logics in Scientific Discovery.Atocha Aliseda - 2004 - Foundations of Science 9 (3):339-363.
    In this paper I argue for a place for logic inscientific methodology, at the same level asthat of computational and historicalapproaches. While it is well known that a awhole generation of philosophers dismissedLogical Positivism (not just for the logicthough), there are at least two reasons toreconsider logical approaches in the philosophyof science. On the one hand, the presentsituation in logical research has gone farbeyond the formal developments that deductivelogic reached last century, and new researchincludes the formalization of several othertypes of (...)
  10. Toxic Funding? Conflicts of Interest and Their Epistemological Significance.Ben Almassi - 2016 - Journal of Applied Philosophy 33 (3).
    Conflict of interest disclosure has become a routine requirement in communication of scientific information. Its advocates defend COI disclosure as a sensible middle path between the extremes of categorical prohibition on for-profit research and anything-goes acceptance of research regardless of origin. To the extent that COI information is meant to aid reviewer and reader evaluation of research, COIs must be epistemologically significant. While some commentators treat COIs as always relevant to research credibility, others liken the demand for disclosure to an (...)
  11. Model Validation: Perspectives in Hydrological Science.Malcolm G. Anderson & Paul D. Bates (eds.) - 2001 - Wiley.
  12. Methodology and Statistics in Single‐Subject Experiments.Norman H. Anderson - 2002 - In J. Wixted & H. Pashler (eds.), Stevens' Handbook of Experimental Psychology. Wiley.
  13. Functional Measurement and Psychophysical Judgment.Norman H. Anderson - 1970 - Psychological Review 77 (3):153-170.
  14. Is Measurement Itself an Emergent Property?Philip W. Anderson - 1997 - Complexity 3 (1):14-16.
  15. Simulations, D Iagnostics and Recent Results of the Visa II Experiment.G. Andonian, A. Murokh, C. Pellegrini, S. Reiche, J. Rosenzweig & J. Huang - 2005 - In Alan F. Blackwell & David MacKay (eds.), Power. Cambridge University Press. pp. 600.
  16. Explanation and Prediction: A Plea for Reason.R. B. Angel - 1967 - Philosophy of Science 34 (3):276-282.
  17. Locke on Measurement.Peter R. Anstey - 2016 - Studies in History and Philosophy of Science Part A 60:70-81.
  18. Data-Phenomena-Theories: What’s the Notion of a Scientific Phenomenon Good For?Jochen Apel, Monika Dullstein & Pawel Radchenko - 2009 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 40 (1):125-128.
  19. Schets Voor Een Algemene Theorie van Het Experiment.Leo Apostel - 1969 - Philosophica 7.
  20. On the Inextricability of the Context of Discovery and the Context of Justification.Theodore Arabatzis - 2006 - In Jutta Schickore & Friedrich Steinle (eds.), Revisiting Discovery and Justification. Springer. pp. 215--230.
  21. Remarks on the Historiography of Scientific Discovery: The Case of the Electron.Theodore Arabatzis - 1996 - Neusis 5:33-53.
  22. Review of Metaphysics and the Philosophy of Science. [REVIEW]G. W. R. Ardley - 1971 - Philosophical Studies 20:287-288.
  23. Tools for Evaluating the Consequences of Prior Knowledge, but No Experiments. On the Role of Computer Simulations in Science.Eckhart Arnold - manuscript
  24. What’s Wrong with Social Simulations?Eckhart Arnold - 2014 - The Monist 97 (3):359-377.
    This paper tries to answer the question why the epistemic value of so many social simulations is questionable. I consider the epistemic value of a social simulation as questionable if it contributes neither directly nor indirectly to the understanding of empirical reality. To examine this question, two classical social simulations are analyzed with respect to their possible epistemic justification: Schelling’s neighborhood segregation model and Axelrod’s reiterated Prisoner’s Dilemma simulations of the evolution of cooperation. It is argued that Schelling’s simulation is (...)
  25. The Dark Side of the Force. When Computer Simulations Lead Us Astray and Model Think Narrows Our Imagination.Eckhart Arnold - 2006 - In Homepage Eckhart Arnold. Preprint.
  26. Atomic-Scale Computer Simulation Study of the Interaction of Cu-Rich Precipitates with Irradiation-Produced Defects in Α-Fe.A. C. Arokiam, A. V. Barashev, D. J. Bacon & Y. N. Osetsky - 2007 - Philosophical Magazine 87 (6):925-943.
  27. The Discovery of Resistance Historical Accounts and Scientific Careers.Naomi Aronson - 1986 - Isis 77 (4):630-646.
  28. Au Risque de la Science les Conséquences Éducatives Et Sociales du Développement Scientifique Et Technique. Annales 1999-2000.Jacques Arsac & Académie D'éducation Et D'études Sociales - 2000
  29. Causality: An Empirically Informed Plea for Pluralism. [REVIEW]Christopher J. Austin - 2016 - Metascience 25 (2):293-296.
    Phyllis Illari & Federica Russo: Causality: Philosophical Theory Meets Scientific Practice. Oxford: Oxford University Press, 2014, 310pp, £29.99 HB.
  30. Computer Simulation of Reactions Between an Edge Dislocation and Glissile Self-Interstitial Clusters in Iron.D. J. Bacon, Y. N. Osetsky & Z. Rong - 2006 - Philosophical Magazine 86 (25-26):3921-3936.
  31. Science and McCarthyism.Lawrence Badash - 2000 - Minerva 38 (1):53-80.
    Students of the `long' McCarthy period in the United States – fromthe late 1940s through the 1950s – have paid inadequate attentionto the effects of this oppressive time upon science. Visa andpassport denials, loyalty oaths, security investigations, andother problems placed in the paths of scientists no doubthindered science. But they also increased the political maturityof its practitioners, a fact of which recent events make usparticularly aware.
  32. The End of Pure Science: Science Policy From Bayh-Dole to the NNI.D. Baird - 2004 - In Baird D. (ed.), Discovering the Nanoscale. Ios. pp. 217.
  33. Facts-Well-Put.Davis Baird & Alfred Nordmann - 1994 - British Journal for the Philosophy of Science 45 (1):37-77.
    In this paper we elucidate a particular type of instrument. Striking-phenomenon instruments assume their striking profile against the shifting backdrop of theoretical uncertainties. While technologically stable, the phenomena produced by these instruments are linguistically fuzzy, subject to a variety of conceptual representations. But in virtue of their technological stability alone, they can provide a foundation for further technological as well as conceptual development. Sometimes, as in the case of the pulse glass, the phenomenon is taken to confirm conflicting theoretical views; (...)
  34. Structures, Fictions, and the Explanatory Epistemology of Mathematics in Science.Mark Balaguer, Elaine Landry, Sorin Bangu & Christopher Pincock - 2013 - Metascience 22 (2):247-273.
  35. On the Grammatical Aspects of Radical Scientific Discovery.Aristides Baltas - 2004 - Philosophia Scientae 8:169-201.
  36. Ordinary Least Squares as a Method of Measurement.W. Balzer & E.-W. Haendler - 1989 - Erkenntnis 30 (1-2):129 - 146.
  37. Scientific Simulation as Experiment in Social Science.Wolfgang Balzer - 2015 - Philosophical Inquiry 39 (1):26-37.
  38. The Mind of the Noble Ape in Three Simulations.Tom Barbalet - 2013 - In Liz Swan (ed.), Origins of Mind. pp. 383--397.
  39. Big ScienceLittle Science, Big Science... And Beyond. Derek J. De Solla Price.Bernard Barber - 1987 - Isis 78 (4):589-591.
  40. Collaborative Computer Simulations in Climate Science.Anouk Barberousse, Henri Galinon & Marion Vorms - unknown
  41. Philosophy as Continuous with Social Science? [REVIEW]Robert Barnard - 2014 - Metascience 23 (1):153-156.
  42. A Ciência E o Projeto Crítico Kantiano.Eduardo Salles de Oliveira Barra - 2013 - Scientiae Studia 11 (4):937-962.
  43. Science in Society.Ditta Bartels - 1985 - Metascience 3:3.
  44. Just Before Nature: The Purposes of Science and the Purposes of Popularization in Some English Popular Science Journals of the 1860s.Ruth Barton - 1998 - Annals of Science 55 (1):1-33.
    Summary Popular science journalism flourished in the 1860s in England, with many new journals being projected. The time was ripe, Victorian men of science believed, for an ?organ of science? to provide a means of communication between specialties, and between men of science and the public. New formats were tried as new purposes emerged. Popular science journalism became less recreational and educational. Editorial commentary and reviewing the progress of science became more important. The analysis here emphasizes those aspects of popular (...)
  45. Theory and Experiment Recent Insights and New Perspectives on Their Relation.Diderik Batens, Jean Paul van Bendegem & International Union of the History and Philosophy of Science - 1988
  46. Essays in the Study of Scientific Discourse Methods, Practice, and Pedagogy.John T. Battalio - 1998
  47. The Transit in the Tower: English Astronomical Instruments in Colonial America.Silvio A. Bedini - 1997 - Annals of Science 54 (2):161-196.
    Summary Although by the mid-eighteenth century colonial American makers of mathematical instruments were producing many of the scientific instruments required in the British Colonies of North America for surveying and navigation, it was not until after the first quarter of the nineteenth century that American makers had the capability to produce sophisticated precision optical instruments for astronomy and microscopy. Until then, these had to be imported from overseas, chiefly England, at considerable cost and after long delays. Included among them were (...)
  48. How Can Computer Simulations Produce New Knowledge?Claus Beisbart - 2012 - European Journal for Philosophy of Science 2 (3):395-434.
    It is often claimed that scientists can obtain new knowledge about nature by running computer simulations. How is this possible? I answer this question by arguing that computer simulations are arguments. This view parallels Norton’s argument view about thought experiments. I show that computer simulations can be reconstructed as arguments that fully capture the epistemic power of the simulations. Assuming the extended mind hypothesis, I furthermore argue that running the computer simulation is to execute the reconstructing argument. I discuss some (...)
  49. Why Monte Carlo Simulations Are Inferences and Not Experiments.Claus Beisbart & John D. Norton - 2012 - International Studies in the Philosophy of Science 26 (4):403-422.
    Monte Carlo simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the inference by ordinary argumentation of conclusions from assumptions built into the simulations. We show that Monte Carlo simulations cannot produce knowledge other than by inference, and that they resemble other computer simulations in the manner in which they derive their conclusions. Simple examples of Monte Carlo simulations (...)
  50. Inevitability, Inseparability and Gedanken Measurement.Mara Beller - 2003 - In A. Ashtekar (ed.), Revisiting the Foundations of Relativistic Physics. pp. 439--450.
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