This category needs an editor. We encourage you to help if you are qualified.
Volunteer, or read more about what this involves.
Related

Contents
142 found
Order:
1 — 50 / 142
  1. (1 other version)Technological revolutions and the problem of prediction.Nick Bostrom - forthcoming - Nanoethics: The Ethical and Social Implications of Nanotechnology. Wiley-Interscience, Hoboken, Nj.
  2. An Epistemic Advantage of Accommodation over Prediction.Finnur Dellsén - forthcoming - Philosophers' Imprint.
    Many philosophers have argued that a hypothesis is better confirmed by some data if the hypothesis was not specifically designed to fit the data. ‘Prediction’, they argue, is superior to ‘accommodation’. Others deny that there is any epistemic advantage to prediction, and conclude that prediction and accommodation are epistemically on a par. This paper argues that there is a respect in which accommodation is superior to prediction. Specifically, the information that the data was accommodated rather than predicted suggests that the (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  3. Fast Science.Jacob Stegenga - forthcoming - The British Journal for the Philosophy of Science.
    If scientists violate principles and practices of routine science to quickly develop interventions against catastrophic threats, they are engaged in what I call fast science. The magnitude, imminence, and plausibility of a threat justify engaging in and acting on fast science. Yet, that justification is incomplete. I defend two principles to assess fast science, which say: fast science should satisfy as much as possible the reliability-enhancing features of routine science, and the fast science developing an intervention against a threat should (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  4. The Ideals Program in Algorithmic Fairness.Rush T. Stewart - forthcoming - AI and Society.
    I consider statistical criteria of algorithmic fairness from the perspective of the _ideals_ of fairness to which these criteria are committed. I distinguish and describe three theoretical roles such ideals might play. The usefulness of this program is illustrated by taking Base Rate Tracking and its ratio variant as a case study. I identify and compare the ideals of these two criteria, then consider them in each of the aforementioned three roles for ideals. This ideals program may present a way (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  5. An Impossibility Theorem for Base Rate Tracking and Equalized Odds.Rush T. Stewart, Benjamin Eva, Shanna Slank & Reuben Stern - forthcoming - Analysis.
    There is a theorem that shows that it is impossible for an algorithm to jointly satisfy the statistical fairness criteria of Calibration and Equalised Odds non-trivially. But what about the recently advocated alternative to Calibration, Base Rate Tracking? Here, we show that Base Rate Tracking is strictly weaker than Calibration, and then take up the question of whether it is possible to jointly satisfy Base Rate Tracking and Equalised Odds in non-trivial scenarios. We show that it is not, thereby establishing (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  6. New Possibilities for Fair Algorithms.Michael Nielsen & Rush Stewart - 2024 - Philosophy and Technology 37 (4):1-17.
    We introduce a fairness criterion that we call Spanning. Spanning i) is implied by Calibration, ii) retains interesting properties of Calibration that some other ways of relaxing that criterion do not, and iii) unlike Calibration and other prominent ways of weakening it, is consistent with Equalized Odds outside of trivial cases.
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark  
  7. The deep neural network approach to the reference class problem.Oliver Buchholz - 2023 - Synthese 201 (3):1-24.
    Methods of machine learning (ML) are gradually complementing and sometimes even replacing methods of classical statistics in science. This raises the question whether ML faces the same methodological problems as classical statistics. This paper sheds light on this question by investigating a long-standing challenge to classical statistics: the reference class problem (RCP). It arises whenever statistical evidence is applied to an individual object, since the individual belongs to several reference classes and evidence might vary across them. Thus, the problem consists (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  8. Measurement invariance, selection invariance, and fair selection revisited.Remco Heesen & Jan-Willem Romeijn - 2023 - Psychological Methods 28 (3):687-690.
    This note contains a corrective and a generalization of results by Borsboom et al. (2008), based on Heesen and Romeijn (2019). It highlights the relevance of insights from psychometrics beyond the context of psychological testing.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  9. Self-fulfilling Prophecy in Practical and Automated Prediction.Owen C. King & Mayli Mertens - 2023 - Ethical Theory and Moral Practice 26 (1):127-152.
    A self-fulfilling prophecy is, roughly, a prediction that brings about its own truth. Although true predictions are hard to fault, self-fulfilling prophecies are often regarded with suspicion. In this article, we vindicate this suspicion by explaining what self-fulfilling prophecies are and what is problematic about them, paying special attention to how their problems are exacerbated through automated prediction. Our descriptive account of self-fulfilling prophecies articulates the four elements that define them. Based on this account, we begin our critique by showing (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  10. An account of conserved functions and how biologists use them to integrate cell and evolutionary biology.Jeremy G. Wideman, Steve Elliott & Beckett Sterner - 2023 - Biology and Philosophy 38 (5):1-23.
    We characterize a type of functional explanation that addresses why a homologous trait originating deep in the evolutionary history of a group remains widespread and largely unchanged across the group’s lineages. We argue that biologists regularly provide this type of explanation when they attribute conserved functions to phenotypic and genetic traits. The concept of conserved function applies broadly to many biological domains, and we illustrate its importance using examples of molecular sequence alignments at the intersection of evolution and cell biology. (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  11. How Should We Think About Implicit Measures and Their Empirical “Anomalies”?Bertram Gawronski, Michael Brownstein & Alex Madva - 2022 - WIREs Cognitive Science:1-7.
    Based on a review of several “anomalies” in research using implicit measures, Machery (2021) dismisses the modal interpretation of participant responses on implicit measures and, by extension, the value of implicit measures. We argue that the reviewed findings are anomalies only for specific—influential but long-contested—accounts that treat responses on implicit measures as uncontaminated indicators of trait-like unconscious representations that coexist with functionally independent conscious representations. However, the reviewed findings are to-be-expected “normalities” when viewed from the perspective of long-standing alternative frameworks (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  12. Why is Information Retrieval a Scientific Discipline?Robert W. P. Luk - 2022 - Foundations of Science 27 (2):427-453.
    It is relatively easy to state that information retrieval is a scientific discipline but it is rather difficult to understand why it is science because what is science is still under debate in the philosophy of science. To be able to convince others that IR is science, our ability to explain why is crucial. To explain why IR is a scientific discipline, we use a theory and a model of scientific study, which were proposed recently. The explanation involves mapping the (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  13. The Predictive Turn in Neuroscience.Daniel A. Weiskopf - 2022 - Philosophy of Science 89 (5):1213-1222.
    Neuroscientists have in recent years turned to building models that aim to generate predictions rather than explanations. This “predictive turn” has swept across domains including law, marketing, and neuropsychiatry. Yet the norms of prediction remain undertheorized relative to those of explanation. I examine two styles of predictive modeling and show how they exemplify the normative dynamics at work in prediction. I propose an account of how predictive models, conceived of as technological devices for aiding decision-making, can come to be adequate (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark  
  14. Hybrid Knowledge and the Historiography of Science: Rethinking the History of Astronomy between Second-Century CE Alexandria, Ninth-Century Baghdad, and Fourteenth-Century Constantinople.Alberto Bardi - 2021 - Transversal: International Journal for the Historiography of Science 11 (2021).
    Originating in the field of biology, the concept of the hybrid has proved to be influential and effective in historical studies, too. Until now, however, the idea of hybrid knowledge has not been fully explored in the historiography of pre-modern science. This article examines the history of pre-Copernican astronomy and focuses on three case studies—Alexandria in the second century CE; Baghdad in the ninth century; and Constantinople in the fourteenth century—in which hybridization played a crucial role in the development of (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  15. Two Dimensions of Opacity and the Deep Learning Predicament.Florian J. Boge - 2021 - Minds and Machines 32 (1):43-75.
    Deep neural networks have become increasingly successful in applications from biology to cosmology to social science. Trained DNNs, moreover, correspond to models that ideally allow the prediction of new phenomena. Building in part on the literature on ‘eXplainable AI’, I here argue that these models are instrumental in a sense that makes them non-explanatory, and that their automated generation is opaque in a unique way. This combination implies the possibility of an unprecedented gap between discovery and explanation: When unsupervised models (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   22 citations  
  16. The Fate of Explanatory Reasoning in the Age of Big Data.Frank Cabrera - 2021 - Philosophy and Technology 34 (4):645-665.
    In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are in tension with a (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  17. Correlation Isn’t Good Enough: Causal Explanation and Big Data. [REVIEW]Frank Cabrera - 2021 - Metascience 30 (2):335-338.
    A review of Gary Smith and Jay Cordes: The Phantom Pattern Problem: The Mirage of Big Data. New York: Oxford University Press, 2020.
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark  
  18. The past of predicting the future: A review of the multidisciplinary history of affective forecasting.Maya A. Pilin - 2021 - History of the Human Sciences 34 (3-4):290-306.
    Affective forecasting refers to the ability to predict future emotions, a skill that is essential to making decisions on a daily basis. Studies of the concept have determined that individuals are often inaccurate in making such affective forecasts. However, the mechanisms of these errors are not yet clear. In order to better understand why affective forecasting errors occur, this article seeks to trace the theoretical roots of this theory with a focus on its multidisciplinary history. The roots of affective forecasting (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  19. How to Interpret Covid-19 Predictions: Reassessing the IHME’s Model.S. Andrew Schroeder - 2021 - Philosophy of Medicine 1 (2).
    The IHME Covid-19 prediction model has been one of the most influential Covid models in the United States. Early on, it received heavy criticism for understating the extent of the epidemic. I argue that this criticism was based on a misunderstanding of the model. The model was best interpreted not as attempting to forecast the actual course of the epidemic. Rather, it was attempting to make a conditional projection: telling us how the epidemic would unfold, given certain assumptions. This misunderstanding (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  20. Evidence and explanation in Cicero's On Divination.Frank Cabrera - 2020 - Studies in History and Philosophy of Science Part A 82 (C):34-43.
    In this paper, I examine Cicero’s oft-neglected De Divinatione, a dialogue investigating the legitimacy of the practice of divination. First, I offer a novel analysis of the main arguments for divination given by Quintus, highlighting the fact that he employs two logically distinct argument forms. Next, I turn to the first of the main arguments against divination given by Marcus. Here I show, with the help of modern probabilistic tools, that Marcus’ skeptical response is far from the decisive, proto-naturalistic assault (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  21. The Value of Imprecise Prediction.Alkistis Elliott-Graves - 2020 - Philosophy Theory and Practice in Biology 4 (12).
    The traditional philosophy of science approach to prediction leaves little room for appreciating the value and potential of imprecise predictions. At best, they are considered a stepping stone to more precise predictions, while at worst they are viewed as detracting from the scientific quality of a discipline. The aim of this paper is to show that imprecise predictions are undervalued in philosophy of science. I review the conceptions of imprecise predictions and the main criticisms levelled against them: (i) that they (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   2 citations  
  22. Philosophical Perspectives on Earth System Modeling: Truth, Adequacy and Understanding.G. Gramelsberger, J. Lenhard & Wendy Parker - 2020 - Journal of Advances in Modeling Earth Systems 12 (1):e2019MS001720.
    We explore three questions about Earth system modeling that are of both scientific and philosophical interest: What kind of understanding can be gained via complex Earth system models? How can the limits of understanding be bypassed or managed? How should the task of evaluating Earth system models be conceptualized?
    Remove from this list  
     
    Export citation  
     
    Bookmark   1 citation  
  23. Big data and prediction: Four case studies.Robert Northcott - 2020 - Studies in History and Philosophy of Science Part A 81:96-104.
    Has the rise of data-intensive science, or ‘big data’, revolutionized our ability to predict? Does it imply a new priority for prediction over causal understanding, and a diminished role for theory and human experts? I examine four important cases where prediction is desirable: political elections, the weather, GDP, and the results of interventions suggested by economic experiments. These cases suggest caution. Although big data methods are indeed very useful sometimes, in this paper’s cases they improve predictions either limitedly or not (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   7 citations  
  24. The meta-inductive justification of induction.Tom F. Sterkenburg - 2020 - Episteme 17 (4):519-541.
    I evaluate Schurz's proposed meta-inductive justification of induction, a refinement of Reichenbach's pragmatic justification that rests on results from the machine learning branch of prediction with expert advice. My conclusion is that the argument, suitably explicated, comes remarkably close to its grand aim: an actual justification of induction. This finding, however, is subject to two main qualifications, and still disregards one important challenge. The first qualification concerns the empirical success of induction. Even though, I argue, Schurz's argument does not need (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark   12 citations  
  25. What do implicit measures measure?Michael Brownstein, Alex Madva & Bertram Gawronski - 2019 - WIREs Cognitive Science:1-13.
    We identify several ongoing debates related to implicit measures, surveying prominent views and considerations in each debate. First, we summarize the debate regarding whether performance on implicit measures is explained by conscious or unconscious representations. Second, we discuss the cognitive structure of the operative constructs: are they associatively or propositionally structured? Third, we review debates whether performance on implicit measures reflects traits or states. Fourth, we discuss the question of whether a person’s performance on an implicit measure reflects characteristics of (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   18 citations  
  26. The Future of Predictive Ecology.Alkistis Elliott-Graves - 2019 - Philosophical Topics 47 (1):65-82.
    Prediction is an important aspect of scientific practice, because it helps us to confirm theories and effectively intervene on the systems we are investigating. In ecology, prediction is a controversial topic: even though the number of papers focusing on prediction is constantly increasing, many ecologists believe that the quality of ecological predictions is unacceptably low, in the sense that they are not sufficiently accurate sufficiently often. Moreover, ecologists disagree on how predictions can be improved. On one side are the ‘theory-driven’ (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  27. (1 other version)The Coming Emptiness: On the Meaning of the Emptiness of the Universe in Natural Philosophy.Gregor Schiemann - 2019 - Philosophies 4 (1).
    The cosmological relevance of emptiness—that is, space without bodies—is not yet sufficiently appreciated in natural philosophy. This paper addresses two aspects of cosmic emptiness from the perspective of natural philosophy: the distances to the stars in the closer cosmic environment and the expansion of space as a result of the accelerated expansion of the universe. Both aspects will be discussed from both a historical and a systematic perspective. Emptiness can be interpreted as “coming” in a two-fold sense: whereas in the (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark  
  28. Beyond Belief: Randomness, Prediction and Explanation in Science.John L. Casti & Anders Karlqvist (eds.) - 2018 - Crc-Press.
    How can we predict and explain the phenomena of nature? What are the limits to this knowledge process? The central issues of prediction, explanation, and mathematical modeling, which underlie all scientific activity, were the focus of a conference organized by the Swedish Council for the Planning and Coordination of Research, held at the Abisko Research Station in May of 1989. At this forum, a select group of internationally known scientists in physics, chemistry, biology, economics, sociology and mathematics discussed and debated (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  29. To Explain or to Predict: Which One is Mandatory?Robert W. P. Luk - 2018 - Foundations of Science 23 (2):411-414.
    Recently, Luk mentioned that scientific knowledge both explains and predicts. Do these two functions of scientific knowledge have equal significance, or is one of the two functions more important than the other? This commentary explains why prediction may be mandatory but explanation may be only desirable and optional.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  30. Twierdzenie Bayesa w projektowaniu strategii diagnostycznych w medycynie.Tomasz Rzepiński - 2018 - Diametros 57:39-60.
    The paper will compare two methods used in the design of diagnostic strategies. The first one is a method that precises predictive value of diagnostic tests. The second one is based on the use of Bayes’ theorem. The main aim of this article is to identify the epistemological assumptions underlying both of these methods. For the purpose of this objective, example projects of one and multi-stage diagnostic strategy developed using both methods will be considered.
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   2 citations  
  31. What to make of Mendeleev’s predictions?K. Brad Wray - 2018 - Foundations of Chemistry 21 (2):139-143.
    I critically examine Stewart’s suggestion that we should weigh the various predictions Mendeleev made differently. I argue that in his effort to justify discounting the weight of some of Mendeleev’s failures, Stewart invokes a principle that will, in turn, reduce the weight of some of the successful predictions Mendeleev made. So Stewart’s strategy will not necessarily lead to a net gain in Mendeleev’s favor.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  32. Prediction in General Relativity.C. D. McCoy - 2017 - Synthese 194 (2):491-509.
    Several authors have claimed that prediction is essentially impossible in the general theory of relativity, the case being particularly strong, it is said, when one fully considers the epistemic predicament of the observer. Each of these claims rests on the support of an underdetermination argument and a particular interpretation of the concept of prediction. I argue that these underdetermination arguments fail and depend on an implausible explication of prediction in the theory. The technical results adduced in these arguments can be (...)
    Remove from this list   Direct download (8 more)  
     
    Export citation  
     
    Bookmark  
  33. When does HARKing hurt? Identifying when different types of undisclosed post hoc hypothesizing harm scientific progress.Mark Rubin - 2017 - Review of General Psychology 21:308-320.
    Hypothesizing after the results are known, or HARKing, occurs when researchers check their research results and then add or remove hypotheses on the basis of those results without acknowledging this process in their research report (Kerr, 1998). In the present article, I discuss three forms of HARKing: (1) using current results to construct post hoc hypotheses that are then reported as if they were a priori hypotheses; (2) retrieving hypotheses from a post hoc literature search and reporting them as a (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   7 citations  
  34. Do We Know Whether Researchers and Reviewers are Estimating Risk and Benefit Accurately?Spencer Phillips Hey & Jonathan Kimmelman - 2016 - Bioethics 30 (8):609-617.
    Accurate estimation of risk and benefit is integral to good clinical research planning, ethical review, and study implementation. Some commentators have argued that various actors in clinical research systems are prone to biased or arbitrary risk/benefit estimation. In this commentary, we suggest the evidence supporting such claims is very limited. Most prior work has imputed risk/benefit beliefs based on past behavior or goals, rather than directly measuring them. We describe an approach – forecast analysis – that would enable direct and (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   5 citations  
  35. The Curious Case of the Self-Refuting Straw Man: Trafimow and Earp’s Response to Klein (2014).Stan Klein - 2016 - Theory and Psychology 26:549– 556.
    In their critique of Klein (2014a), Trafimow and Earp present two theses. First, they argue that, contra Klein, a well-specified theory is not a necessary condition for successful replication. Second, they contend that even when there is a well-specified theory, replication depends more on auxiliary assumptions than on theory proper. I take issue with both claims, arguing that (a) their first thesis confuses a material conditional (what I said) with a modal claim (T&E’s misreading of what I said), and (b) (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  36. Are climate models credible worlds? Prospects and limitations of possibilistic climate prediction.Gregor Betz - 2015 - European Journal for Philosophy of Science 5 (2):191-215.
    Climate models don’t give us probabilistic forecasts. To interpret their results, alternatively, as serious possibilities seems problematic inasmuch as climate models rely on contrary-to-fact assumptions: why should we consider their implications as possible if their assumptions are known to be false? The paper explores a way to address this possibilistic challenge. It introduces the concepts of a perfect and of an imperfect credible world, and discusses whether climate models can be interpreted as imperfect credible worlds. That would allow one to (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   13 citations  
  37. Prediction in epidemiology and medicine.Jonathan Fuller, Alex Broadbent & Luis J. Flores - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 54:45-48.
  38. The Risk GP Model: The standard model of prediction in medicine.Jonathan Fuller & Luis J. Flores - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 54:49-61.
    With the ascent of modern epidemiology in the Twentieth Century came a new standard model of prediction in public health and clinical medicine. In this article, we describe the structure of the model. The standard model uses epidemiological measures-most commonly, risk measures-to predict outcomes (prognosis) and effect sizes (treatment) in a patient population that can then be transformed into probabilities for individual patients. In the first step, a risk measure in a study population is generalized or extrapolated to a target (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark   14 citations  
  39. Prediction and Novel Facts in the Methodology of Scientific Research Programs.Wenceslao J. Gonzalez - 2015 - In Philosophico-Methodological Analysis of Prediction and its Role in Economics. Cham: Imprint: Springer. pp. 103-124.
    In the methodology of scientific research programs (MSRP) there are important features on the problem of prediction, especially regarding novel facts. In his approach, Imre Lakatos proposed three different levels on prediction: aim, process, and assessment. Chapter 5 pays attention to the characterization of prediction in the methodology of research programs. Thus, it takes into account several features: (1) its pragmatic characterization, (2) the logical perspective as a proposition, (3) the epistemological component, (4) its role in the appraisal of research (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  40. Ethics and epistemology of accurate prediction in clinical research.Spencer Phillips Hey - 2015 - Journal of Medical Ethics 41 (7):559-562.
    All major research ethics policies assert that the ethical review of clinical trial protocols should include a systematic assessment of risks and benefits. But despite this policy, protocols do not typically contain explicit probability statements about the likely risks or benefits involved in the proposed research. In this essay, I articulate a range of ethical and epistemic advantages that explicit forecasting would offer to the health research enterprise. I then consider how some particular confidence levels may come into conflict with (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  41. On embodiment in predictions. A book review. [REVIEW]Przemysław Nowakowski - 2015 - Avant: Trends in Interdisciplinary Studies (3):155-159.
  42. Lesser degrees of explanation: further implications of F. A. Hayek's methodology of sciences of complex phenomena.Scott Scheall - 2015 - Erasmus Journal for Philosophy and Economics 8 (1):42.
    F.A. Hayek argued that the sciences of complex phenomena, including (perhaps especially) economics, are limited to incomplete “explanations of the principle” and “pattern predictions.” According to Hayek, these disciplines suffer from (what I call) a data problem, i.e., the hopelessness of populating theoretical models with data adequate to full explanations and precise predictions. In Hayek’s terms, explanations in these fields are always a matter of “degree.” However, Hayek’s methodology implies a distinct theory problem: theoretical models of complex phenomena may be (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  43. (1 other version) Reflections on predictive processing and the mind. An Interview.Jakob Hohwy - 2014 - Avant: Trends in Interdisciplinary Studies (3):145-152.
  44. Introducing Knowledge-based Medicine - Conference Presentation - Medicine is not science: Guessing the future, predicting the past.Clifford Miller - 2014 - Conference Presentation Universidad Franscisco de Vitoria Person Centered Medicine July 2014; 07/2014.
    There is a middle ground of imperfect knowledge in fields like medicine and the social sciences. It stands between our day-to-day relatively certain knowledge obtained from ordinary basic observation of regularities in our world and our knowledge from well-validated theories in the physical sciences. -/- The latter enable reliable prediction a great deal of the time of the happening of events never before experienced. The former enable prediction only of what has happened before and beyond that of educated guesses which (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  45. Prediction and accommodation revisited.John Worrall - 2014 - Studies in History and Philosophy of Science Part A 45 (1):54-61.
    The paper presents a further articulation and defence of the view on prediction and accommodation that I have proposed earlier. It operates by analysing two accounts of the issue-by Patrick Maher and by Marc Lange-that, at least at first sight, appear to be rivals to my own. Maher claims that the time-order of theory and evidence may be important in terms of degree of confirmation, while that claim is explicitly denied in my account. I argue, however, that when his account (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark   19 citations  
  46. State of the Field: Why novel prediction matters.Heather Douglas & P. D. Magnus - 2013 - Studies in History and Philosophy of Science Part A 44 (4):580-589.
    There is considerable disagreement about the epistemic value of novel predictive success, i.e. when a scientist predicts an unexpected phenomenon, experiments are conducted, and the prediction proves to be accurate. We survey the field on this question, noting both fully articulated views such as weak and strong predictivism, and more nascent views, such as pluralist reasons for the instrumental value of prediction. By examining the various reasons offered for the value of prediction across a range of inferential contexts , we (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark   24 citations  
  47. Review: Cornelis Menke: Zum methodologischen Wert von Vorhersagen . Paderborn: Mentis, 2009, 188 pages. [REVIEW]Christian J. Feldbacher - 2013 - Kriterion - Journal of Philosophy 27 (1):53-64.
  48. Space-Time Dimension Problem as a Stumbling Block of Inflationary Cosmology.Rinat M. Nugayev - 2013 - In Vadim V. Kazutinsky, Elena A. Mamchur, Alexandre D. Panov & V. D. Erekaev (eds.), Metauniverse,Space,Time. Institute of Philosophy of RAS. pp. 52-73.
    It is taken for granted that the explanation of the Universe’s space-time dimension belongs to the host of the arguments that exhibit the superiority of modern (inflationary) cosmology over the standard model. In the present paper some doubts are expressed . They are based upon the fact superstring theory is too formal to represent genuine unification of general relativity and quantum field theory. Neveretheless, the fact cannot exclude the opportunity that in future the superstring theory can become more physical. Hence (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  49. Theory-laden experimentation.Samuel Schindler - 2013 - Studies in History and Philosophy of Science Part A 44 (1):89-101.
    The thesis of theory-ladenness of observations, in its various guises, is widely considered as either ill-conceived or harmless to the rationality of science. The latter view rests partly on the work of the proponents of New Experimentalism who have argued, among other things, that experimental practices are efficient in guarding against any epistemological threat posed by theory-ladenness. In this paper I show that one can generate a thesis of theory-ladenness for experimental practices from an influential New Experimentalist account. The notion (...)
    Remove from this list   Direct download (8 more)  
     
    Export citation  
     
    Bookmark   12 citations  
  50. Scientific Uncertainty: A User's Guide.Seamus Bradley - 2012 - Grantham Institute on Climate Change Discussion Paper.
    There are different kinds of uncertainty. I outline some of the various ways that uncertainty enters science, focusing on uncertainty in climate science and weather prediction. I then show how we cope with some of these sources of error through sophisticated modelling techniques. I show how we maintain confidence in the face of error.
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
1 — 50 / 142