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Jon Williamson
University of Kent
  1. What is a Mechanism? Thinking About Mechanisms Across the Sciences.Phyllis Illari & Jon Williamson - 2012 - European Journal for Philosophy of Science 2 (1):119-135.
    After a decade of intense debate about mechanisms, there is still no consensus characterization. In this paper we argue for a characterization that applies widely to mechanisms across the sciences. We examine and defend our disagreements with the major current contenders for characterizations of mechanisms. Ultimately, we indicate that the major contenders can all sign up to our characterization.
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  2.  54
    In Defence of Objective Bayesianism.Jon Williamson - 2010 - Oxford University Press.
    Objective Bayesianism is a methodological theory that is currently applied in statistics, philosophy, artificial intelligence, physics and other sciences. This book develops the formal and philosophical foundations of the theory, at a level accessible to a graduate student with some familiarity with mathematical notation.
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  3. Mechanisms and the Evidence Hierarchy.Brendan Clarke, Donald Gillies, Phyllis Illari, Federica Russo & Jon Williamson - 2014 - Topoi 33 (2):339-360.
    Evidence-based medicine (EBM) makes use of explicit procedures for grading evidence for causal claims. Normally, these procedures categorise evidence of correlation produced by statistical trials as better evidence for a causal claim than evidence of mechanisms produced by other methods. We argue, in contrast, that evidence of mechanisms needs to be viewed as complementary to, rather than inferior to, evidence of correlation. In this paper we first set out the case for treating evidence of mechanisms alongside evidence of correlation in (...)
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  4. Interpreting Causality in the Health Sciences.Federica Russo & Jon Williamson - 2007 - International Studies in the Philosophy of Science 21 (2):157 – 170.
    We argue that the health sciences make causal claims on the basis of evidence both of physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of causality solely in terms of physical mechanisms or solely in terms of probabilistic relationships, does not do justice to the causal claims of these sciences. Yet there seems to be a single relation of cause in these sciences - pluralism about causality will not do either. Instead, we maintain, the health sciences require a theory (...)
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  5. Bayesian Nets and Causality: Philosophical and Computational Foundations.Jon Williamson - 2004 - Oxford University Press.
    Bayesian nets are widely used in artificial intelligence as a calculus for causal reasoning, enabling machines to make predictions, perform diagnoses, take decisions and even to discover causal relationships. This book, aimed at researchers and graduate students in computer science, mathematics and philosophy, brings together two important research topics: how to automate reasoning in artificial intelligence, and the nature of causality and probability in philosophy.
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  6.  23
    Evaluating Evidence of Mechanisms in Medicine.Veli-Pekka Parkkinen, Christian Wallmann, Michael Wilde, Brendan Clarke, Phyllis Illari, Michael P. Kelly, Charles Norell, Federica Russo, Beth Shaw & Jon Williamson - 2018 - Dordrecht, Netherlands: Springer.
    The use of evidence in medicine is something we should continuously seek to improve. This book seeks to develop our understanding of evidence of mechanism in evaluating evidence in medicine, public health, and social care; and also offers tools to help implement improved assessment of evidence of mechanism in practice. In this way, the book offers a bridge between more theoretical and conceptual insights and worries about evidence of mechanism and practical means to fit the results into evidence assessment procedures.
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  7. The Principal Principle Implies the Principle of Indifference.James Hawthorne, Jürgen Landes, Christian Wallmann & Jon Williamson - 2017 - British Journal for the Philosophy of Science 68 (1):axv030.
    We argue that David Lewis’s principal principle implies a version of the principle of indifference. The same is true for similar principles that need to appeal to the concept of admissibility. Such principles are thus in accord with objective Bayesianism, but in tension with subjective Bayesianism. 1 The Argument2 Some Objections Met.
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  8. Modelling Mechanisms with Causal Cycles.Brendan Clarke, Bert Leuridan & Jon Williamson - 2014 - Synthese 191 (8):1-31.
    Mechanistic philosophy of science views a large part of scientific activity as engaged in modelling mechanisms. While science textbooks tend to offer qualitative models of mechanisms, there is increasing demand for models from which one can draw quantitative predictions and explanations. Casini et al. (Theoria 26(1):5–33, 2011) put forward the Recursive Bayesian Networks (RBN) formalism as well suited to this end. The RBN formalism is an extension of the standard Bayesian net formalism, an extension that allows for modelling the hierarchical (...)
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  9. Function and Organization: Comparing the Mechanisms of Protein Synthesis and Natural Selection.Phyllis McKay Illari & Jon Williamson - 2010 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 41 (3):279-291.
    In this paper, we compare the mechanisms of protein synthesis and natural selection. We identify three core elements of mechanistic explanation: functional individuation, hierarchical nestedness or decomposition, and organization. These are now well understood elements of mechanistic explanation in fields such as protein synthesis, and widely accepted in the mechanisms literature. But Skipper and Millstein have argued that natural selection is neither decomposable nor organized. This would mean that much of the current mechanisms literature does not apply to the mechanism (...)
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  10.  72
    Probabilistic Logics and Probabilistic Networks.Rolf Haenni, Jan-Willem Romeijn, Gregory Wheeler & Jon Williamson - 2011 - Synthese Library.
    Additionally, the text shows how to develop computationally feasible methods to mesh with this framework.
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  11.  44
    The Evidence That Evidence-Based Medicine Omits.Brendan Clarke, Donald Gillies, Phyllis Illari, Federica Russo & Jon Williamson - 2013 - Preventive Medicine 57:745-747.
    According to current hierarchies of evidence for EBM, evidence of correlation is always more important than evidence of mechanisms when evaluating and establishing causal claims. We argue that evidence of mechanisms needs to be treated alongside evidence of correlation. This is for three reasons. First, correlation is always a fallible indicator of causation, subject in particular to the problem of confounding; evidence of mechanisms can in some cases be more important than evidence of correlation when assessing a causal claim. Second, (...)
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  12.  58
    Deliberation, Judgement and the Nature of Evidence.Jon Williamson - unknown
    A normative Bayesian theory of deliberation and judgement requires a procedure for merging the evidence of a collection of agents. In order to provide such a procedure, one needs to ask what the evidence is that grounds Bayesian probabilities. After finding fault with several views on the nature of evidence, it is argued that evidence is whatever is rationally taken for granted. This view is shown to have consequences for an account of merging evidence, and it is argued that standard (...)
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  13. Generic Versus Single-Case Causality: The Case of Autopsy. [REVIEW]Jon Williamson - 2011 - European Journal for Philosophy of Science 1 (1):47-69.
    This paper addresses questions about how the levels of causality (generic and single-case causality) are related. One question is epistemological: can relationships at one level be evidence for relationships at the other level? We present three kinds of answer to this question, categorised according to whether inference is top-down, bottom-up, or the levels are independent. A second question is metaphysical: can relationships at one level be reduced to relationships at the other level? We present three kinds of answer to this (...)
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  14. Probabilistic Theories.Jon Williamson - 2009 - In Helen Beebee, Christopher Hitchcock & Peter Menzies (eds.), The Oxford Handbook of Causation. Oxford University Press.
     
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  15. Bayesian Nets and Causality.Jon Williamson - manuscript
    How should we reason with causal relationships? Much recent work on this question has been devoted to the theses (i) that Bayesian nets provide a calculus for causal reasoning and (ii) that we can learn causal relationships by the automated learning of Bayesian nets from observational data. The aim of this book is to..
     
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  16.  75
    Epistemic Causality and Evidence-Based Medicine.Federica Russo & Jon Williamson - 2011 - History and Philosophy of the Life Sciences 33 (4).
    Causal claims in biomedical contexts are ubiquitous albeit they are not always made explicit. This paper addresses the question of what causal claims mean in the context of disease. It is argued that in medical contexts causality ought to be interpreted according to the epistemic theory. The epistemic theory offers an alternative to traditional accounts that cash out causation either in terms of “difference-making” relations or in terms of mechanisms. According to the epistemic approach, causal claims tell us about which (...)
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  17.  43
    Establishing Causal Claims in Medicine.Jon Williamson - 2019 - International Studies in the Philosophy of Science 32 (1):33-61.
    ABSTRACTRusso and Williamson [2007. “Interpreting Causality in the Health Sciences.” International Studies in the Philosophy of Science 21: 157–170] put forward the following thesis: in order to establish a causal claim in medicine, one normally needs to establish both that the putative cause and putative effect are appropriately correlated and that there is some underlying mechanism that can account for this correlation. I argue that, although the Russo–Williamson thesis conflicts with the tenets of present-day evidence-based medicine, it offers a better (...)
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  18. Objective Bayesianism, Bayesian Conditionalisation and Voluntarism.Jon Williamson - 2011 - Synthese 178 (1):67-85.
    Objective Bayesianism has been criticised on the grounds that objective Bayesian updating, which on a finite outcome space appeals to the maximum entropy principle, differs from Bayesian conditionalisation. The main task of this paper is to show that this objection backfires: the difference between the two forms of updating reflects negatively on Bayesian conditionalisation rather than on objective Bayesian updating. The paper also reviews some existing criticisms and justifications of conditionalisation, arguing in particular that the diachronic Dutch book justification fails (...)
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  19. Models for Prediction, Explanation and Control: Recursive Bayesian Networks.Jon Williamson - 2011 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 26 (1):5-33.
    The Recursive Bayesian Net (RBN) formalism was originally developed for modelling nested causal relationships. In this paper we argue that the formalism can also be applied to modelling the hierarchical structure of mechanisms. The resulting network contains quantitative information about probabilities, as well as qualitative information about mechanistic structure and causal relations. Since information about probabilities, mechanisms and causal relations is vital for prediction, explanation and control respectively, an RBN can be applied to all these tasks. We show in particular (...)
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  20. Lectures on Inductive Logic.Jon Williamson - 2017 - Oxford University Press.
    Inductive logic is a theory of how one should reason in the face of uncertainty. It has applications to decision making and artificial intelligence, as well as to scientific problems.
     
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  21. Causal Pluralism Versus Epistemic Causality.Jon Williamson - 2006 - Philosophica 77 (1):69-96.
    It is tempting to analyse causality in terms of just one of the indicators of causal relationships, e.g., mechanisms, probabilistic dependencies or independencies, counterfactual conditionals or agency considerations. While such an analysis will surely shed light on some aspect of our concept of cause, it will fail to capture the whole, rather multifarious, notion. So one might instead plump for pluralism: a different analysis for a different occasion. But we do not seem to have lots of different concepts of cause (...)
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  22. Mechanisms Are Real and Local.Phyllis McKay Illari & Jon Williamson - 2011 - In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), Causality in the Sciences. Oxford University Press.
    Mechanisms have become much-discussed, yet there is still no consensus on how to characterise them. In this paper, we start with something everyone is agreed on – that mechanisms explain – and investigate what constraints this imposes on our metaphysics of mechanisms. We examine two widely shared premises about how to understand mechanistic explanation: (1) that mechanistic explanation offers a welcome alternative to traditional laws-based explanation and (2) that there are two senses of mechanistic explanation that we call ‘epistemic explanation’ (...)
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  23. Maximising Entropy Efficiently.Jon Williamson - manuscript
    Recommended citation: . . Link¨ oping Electronic Articles in Computer and Information Science, Vol. 7(2002): nr 0. http://www.ep.liu.se/ea/cis/2002/00/. September 18, 2002. </div><div class="catsCon" id="ecats-con-WILMEE"><div><a class='catName' href='/browse/thermodynamics-and-statistical-mechanics' rel='section'>Thermodynamics and Statistical Mechanics</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-physical-science' rel='section'>Philosophy of Physical Science</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILMEE&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F7376%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILMEE'>(2 more)</a>   <div id="la-WILMEE" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILMEE')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILMEE" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILMEE','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILMEE"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILMEE"></span></div></div></li> <li id='eWALTPP-13' onclick="ee('click','WALTPP-13')" onmouseover="ee('over','WALTPP-13')" onmouseout="ee('out','WALTPP-13')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WALTPP-13#analytics'><span style='color:#109D49'>8 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WALTPP-13"><span class='articleTitle recTitle'>The Principal Principle and subjective Bayesianism.</span></a><a class='discreet' title="View other works by Christian Wallmann" href="/s/Christian%20Wallmann"><span class='name'>Christian Wallmann</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2020</span> - <span class='pubInfo'> <em class='pubName'>European Journal for Philosophy of Science</em> 10 (1):1-14.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">This paper poses a problem for Lewis’ Principal Principle in a subjective Bayesian framework: we show that, where chances inform degrees of belief, subjective Bayesianism fails to validate normal informal standards of what is reasonable. This problem points to a tension between the Principal Principle and the claim that conditional degrees of belief are conditional probabilities. However, one version of objective Bayesianism has a straightforward resolution to this problem, because it avoids this latter claim. The problem, then, offers some support<span id="WALTPP-13-absexp"> (<span class="ll" onclick='$("WALTPP-13-abstract2").show();$("WALTPP-13-absexp").hide()'>...</span>)</span><span id="WALTPP-13-abstract2" style="display:none"> to this version of objective Bayesianism. (<span class="ll" onclick='$("WALTPP-13-abstract2").hide();$("WALTPP-13-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WALTPP-13"><div><a class='catName' href='/browse/science-logic-and-mathematics' rel='section'>Science, Logic, and Mathematics</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WALTPP-13&proxyId=&u=http%3A%2F%2Fdx.doi.org%2F10.1007%2Fs13194-019-0266-4" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WALTPP-13'>(2 more)</a>   <div id="tr-WALTPP-13" title="Translate" class="yui-skin-sam ldiv" style="cursor:pointer" onclick="translateEntry('WALTPP-13')"><i class="fa fa-language"></i> Translate</div>   <div id="la-WALTPP-13" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WALTPP-13')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WALTPP-13" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WALTPP-13','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WALTPP-13"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WALTPP-13"></span></div></div></li> <li id='eILLIDO' onclick="ee('click','ILLIDO')" onmouseover="ee('over','ILLIDO')" onmouseout="ee('out','ILLIDO')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/ILLIDO#analytics'><span style='color:#109D49'>63 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/ILLIDO"><span class='articleTitle recTitle'>In Defence of Activities.</span></a><a class='discreet' title="View other works by Phyllis Illari" href="/s/Phyllis%20Illari"><span class='name'>Phyllis Illari</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2013</span> - <span class='pubInfo'> <em class='pubName'>Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie</em> 44 (1):69-83.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">In this paper, we examine what is to be said in defence of Machamer, Darden and Craver’s (MDC) controversial dualism about activities and entities (Machamer, Darden and Craver’s in Philos Sci 67:1–25, 2000). We explain why we believe the notion of an activity to be a novel, valuable one, and set about clearing away some initial objections that can lead to its being brushed aside unexamined. We argue that substantive debate about ontology can only be effective when desiderata for an<span id="ILLIDO-absexp"> (<span class="ll" onclick='$("ILLIDO-abstract2").show();$("ILLIDO-absexp").hide()'>...</span>)</span><span id="ILLIDO-abstract2" style="display:none"> ontology are explicitly articulated. We distinguish three such desiderata. The first is a more permissive descriptive ontology of science, the second a more reductive ontology prioritising understanding, and the third a more reductive ontology prioritising minimalism. We compare MDC’s entities-activities ontology to its closest rival, the entities-capacities ontology, and argue that the entities-activities ontology does better on all three desiderata. (<span class="ll" onclick='$("ILLIDO-abstract2").hide();$("ILLIDO-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-ILLIDO"><div><a class='catName' href='/browse/mechanistic-explanation' rel='section'>Mechanistic Explanation</a><span class='catIn'> in </span><a class='catArea' href='/browse/general-philosophy-of-science' rel='section'>General Philosophy of Science</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=ILLIDO&proxyId=&u=http%3A%2F%2Flink.springer.com%2Fcontent%2Fpdf%2F10.1007%252Fs10838-013-9217-5.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/ILLIDO'>(6 more)</a>   <div id="la-ILLIDO" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('ILLIDO')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-ILLIDO" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('ILLIDO','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/ILLIDO"><i class="fa fa-share-alt"></i> 9 citations</a>   <span class="eMsg" id="msg-ILLIDO"></span></div></div></li> <li id='eWILHCC-3' onclick="ee('click','WILHCC-3')" onmouseover="ee('over','WILHCC-3')" onmouseout="ee('out','WILHCC-3')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILHCC-3#analytics'><span style='color:#109D49'>69 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILHCC-3"><span class='articleTitle recTitle'>How Can Causal Explanations Explain?</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2013</span> - <span class='pubInfo'> <em class='pubName'>Erkenntnis</em> 78 (2):257-275.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">The mechanistic and causal accounts of explanation are often conflated to yield a ‘causal-mechanical’ account. This paper prizes them apart and asks: if the mechanistic account is correct, how can causal explanations be explanatory? The answer to this question varies according to how causality itself is understood. It is argued that difference-making, mechanistic, dualist and inferentialist accounts of causality all struggle to yield explanatory causal explanations, but that an epistemic account of causality is more promising in this regard. </div><div class="catsCon" id="ecats-con-WILHCC-3"><div><a class='catName' href='/browse/explanation' rel='section'>Explanation</a><span class='catIn'> in </span><a class='catArea' href='/browse/general-philosophy-of-science' rel='section'>General Philosophy of Science</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILHCC-3&proxyId=&u=http%3A%2F%2Flink.springer.com%2Fcontent%2Fpdf%2F10.1007%252Fs10670-013-9512-x.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILHCC-3'>(7 more)</a>   <div id="la-WILHCC-3" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILHCC-3')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILHCC-3" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILHCC-3','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILHCC-3"><i class="fa fa-share-alt"></i> 8 citations</a>   <span class="eMsg" id="msg-WILHCC-3"></span></div></div></li> <li id='eWILCFE-2' onclick="ee('click','WILCFE-2')" onmouseover="ee('over','WILCFE-2')" onmouseout="ee('out','WILCFE-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILCFE-2#analytics'><span style='color:#109D49'>25 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILCFE-2"><span class='articleTitle recTitle'>Calibration for Epistemic Causality.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">forthcoming</span> - <span class='pubInfo'> <em class='pubName'>Erkenntnis</em>:1-20.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">The epistemic theory of causality is analogous to epistemic theories of probability. Most proponents of epistemic probability would argue that one's degrees of belief should be calibrated to chances, insofar as one has evidence of chances. The question arises as to whether causal beliefs should satisfy an analogous calibration norm. In this paper, I formulate a particular version of a norm requiring calibration to chances and argue that this norm is the most fundamental evidential norm for epistemic probability. I then<span id="WILCFE-2-absexp"> (<span class="ll" onclick='$("WILCFE-2-abstract2").show();$("WILCFE-2-absexp").hide()'>...</span>)</span><span id="WILCFE-2-abstract2" style="display:none"> develop an analogous calibration norm for epistemic causality, argue that it is the *only* evidential norm required for epistemic causality, and show how an epistemic account of causality that incorporates this norm can be used to analyse objective causal relationships. (<span class="ll" onclick='$("WILCFE-2-abstract2").hide();$("WILCFE-2-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILCFE-2">No categories</div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILCFE-2&proxyId=&u=https%3A%2F%2Fkar.kent.ac.uk%2F74176%2F1%2FCalibrationEC.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILCFE-2'>(4 more)</a>   <div id="la-WILCFE-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILCFE-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILCFE-2" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILCFE-2','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILCFE-2"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILCFE-2"></span></div></div></li> <li id='eWILWFA' onclick="ee('click','WILWFA')" onmouseover="ee('over','WILWFA')" onmouseout="ee('out','WILWFA')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILWFA#analytics'><span style='color:#109D49'>148 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILWFA"><span class='articleTitle recTitle'>Why Frequentists and Bayesians Need Each Other.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2013</span> - <span class='pubInfo'> <em class='pubName'>Erkenntnis</em> 78 (2):293-318.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">The orthodox view in statistics has it that frequentism and Bayesianism are diametrically opposed—two totally incompatible takes on the problem of statistical inference. This paper argues to the contrary that the two approaches are complementary and need to mesh if probabilistic reasoning is to be carried out correctly. </div><div class="catsCon" id="ecats-con-WILWFA"><div><a class='catName' href='/browse/philosophy-of-statistics' rel='section'>Philosophy of Statistics</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILWFA&proxyId=&u=http%3A%2F%2Flink.springer.com%2Fcontent%2Fpdf%2F10.1007%252Fs10670-011-9317-8.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILWFA'>(6 more)</a>   <div id="la-WILWFA" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILWFA')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILWFA" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILWFA','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILWFA"><i class="fa fa-share-alt"></i> 7 citations</a>   <span class="eMsg" id="msg-WILWFA"></span></div></div></li> <li id='eAROTUO-2' onclick="ee('click','AROTUO-2')" onmouseover="ee('over','AROTUO-2')" onmouseout="ee('out','AROTUO-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/AROTUO-2#analytics'><span style='color:#109D49'>21 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/AROTUO-2"><span class='articleTitle recTitle'>The Use of Mechanistic Evidence in Drug Approval.</span></a><a class='discreet' title="View other works by Jeffrey K. Aronson" href="/s/Jeffrey K.%20Aronson"><span class='name'>Jeffrey K. Aronson</span></a>, <a class='discreet' title="View other works by Adam La Caze" href="/s/Adam%20La Caze"><span class='name'>Adam La Caze</span></a>, <a class='discreet' title="View other works by Michael P. Kelly" href="/s/Michael P.%20Kelly"><span class='name'>Michael P. Kelly</span></a>, <a class='discreet' title="View other works by Veli-Pekka Parkkinen" href="/s/Veli-Pekka%20Parkkinen"><span class='name'>Veli-Pekka Parkkinen</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2018</span> - <span class='pubInfo'> <em class='pubName'>Journal of Evaluation in Clinical Practice</em> 24 (5):1166-1176.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">The role of mechanistic evidence tends to be under‐appreciated in current evidence‐based medicine, which focusses on clinical studies, tending to restrict attention to randomized controlled studies when they are available. The EBM+ programme seeks to redress this imbalance, by suggesting methods for evaluating mechanistic studies alongside clinical studies. Drug approval is a problematic case for the view that mechanistic evidence should be taken into account, because RCTs are almost always available. Nevertheless, we argue that mechanistic evidence is central to all<span id="AROTUO-2-absexp"> (<span class="ll" onclick='$("AROTUO-2-abstract2").show();$("AROTUO-2-absexp").hide()'>...</span>)</span><span id="AROTUO-2-abstract2" style="display:none"> the key tasks in the drug approval process: in drug discovery and development; assessing pharmaceutical quality; devising dosage regimens; assessing efficacy, harms, external validity, and cost‐effectiveness; evaluating adherence; and extending product licences. We recommend that, when preparing for meetings in which any aspect of drug approval is to be discussed, mechanistic evidence should be systematically analysed and presented to the committee members alongside analyses of clinical studies. (<span class="ll" onclick='$("AROTUO-2-abstract2").hide();$("AROTUO-2-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-AROTUO-2">No categories</div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=AROTUO-2&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F66978%2F11%2FAronson_et_al-2018-Journal_of_Evaluation_in_Clinical_Practice.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/AROTUO-2'>(6 more)</a>   <div id="la-AROTUO-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('AROTUO-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-AROTUO-2" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('AROTUO-2','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/AROTUO-2"><i class="fa fa-share-alt"></i> 2 citations</a>   <span class="eMsg" id="msg-AROTUO-2"></span></div></div></li> <li id='eWILMOB-2' onclick="ee('click','WILMOB-2')" onmouseover="ee('over','WILMOB-2')" onmouseout="ee('out','WILMOB-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILMOB-2#analytics'><span style='color:#109D49'>71 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILMOB-2"><span class='articleTitle recTitle'>Motivating Objective Bayesianism: From Empirical Constraints to Objective Probabilities.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">manuscript</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">Kyburg goes half-way towards objective Bayesianism. He accepts that frequencies constrain rational belief to an interval but stops short of isolating an optimal degree of belief within this interval. I examine the case for going the whole hog. </div><div class="catsCon" id="ecats-con-WILMOB-2"><div><a class='catName' href='/browse/bayesian-reasoning-misc' rel='section'>Bayesian Reasoning, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILMOB-2&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F1291%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a>   <div id="la-WILMOB-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILMOB-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILMOB-2" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILMOB-2','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILMOB-2"><i class="fa fa-share-alt"></i> 12 citations</a>   <span class="eMsg" id="msg-WILMOB-2"></span></div></div></li> <li id='eLANOBA' onclick="ee('click','LANOBA')" onmouseover="ee('over','LANOBA')" onmouseout="ee('out','LANOBA')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/LANOBA#analytics'><span style='color:#109D49'>71 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/LANOBA"><span class='articleTitle recTitle'>Objective Bayesianism and the Maximum Entropy Principle.</span></a><a class='discreet' title="View other works by Jürgen Landes" href="/s/Jürgen%20Landes"><span class='name'>Jürgen Landes</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">unknown</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">Objective Bayesian epistemology invokes three norms: the strengths of our beliefs should be probabilities, they should be calibrated to our evidence of physical probabilities, and they should otherwise equivocate sufficiently between the basic propositions that we can express. The three norms are sometimes explicated by appealing to the maximum entropy principle, which says that a belief function should be a probability function, from all those that are calibrated to evidence, that has maximum entropy. However, the three norms of objective Bayesianism<span id="LANOBA-absexp"> (<span class="ll" onclick='$("LANOBA-abstract2").show();$("LANOBA-absexp").hide()'>...</span>)</span><span id="LANOBA-abstract2" style="display:none"> are usually justified in different ways. In this paper we show that the three norms can all be subsumed under a single justification in terms of minimising worst-case expected loss. This, in turn, is equivalent to maximising a generalised notion of entropy. We suggest that requiring language invariance, in addition to minimising worst-case expected loss, motivates maximisation of standard entropy as opposed to maximisation of other instances of generalised entropy. Our argument also provides a qualified justification for updating degrees of belief by Bayesian conditionalisation. However, conditional probabilities play a less central part in the objective Bayesian account than they do under the subjective view of Bayesianism, leading to a reduced role for Bayes’ Theorem. (<span class="ll" onclick='$("LANOBA-abstract2").hide();$("LANOBA-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-LANOBA"><div><a class='catName' href='/browse/conditionalization' rel='section'>Conditionalization</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> <div><a class='catName' href='/browse/indifference-principles' rel='section'>Indifference Principles</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> <div><a class='catName' href='/browse/maximum-entropy-principles' rel='section'>Maximum Entropy Principles</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> <div><a class='catName' href='/browse/updating-principles' rel='section'>Updating Principles</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=LANOBA&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F35197%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/LANOBA'>(3 more)</a>   <div id="la-LANOBA" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('LANOBA')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-LANOBA" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('LANOBA','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/LANOBA"><i class="fa fa-share-alt"></i> 7 citations</a>   <span class="eMsg" id="msg-LANOBA"></span></div></div></li> <li id='eWILMTO-2' onclick="ee('click','WILMTO-2')" onmouseover="ee('over','WILMTO-2')" onmouseout="ee('out','WILMTO-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILMTO-2#analytics'><span style='color:#109D49'>91 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILMTO-2"><span class='articleTitle recTitle'>Mechanistic Theories of Causality.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">unknown</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">After introducing a range of mechanistic theories of causality and some of the problems they face, I argue that while there is a decisive case against a purely mechanistic analysis, a viable theory of causality must incorporate mechanisms as an ingredient. I describe one way of providing an analysis of causality which reaps the rewards of the mechanistic approach without succumbing to its pitfalls. </div><div class="catsCon" id="ecats-con-WILMTO-2"><div><a class='catName' href='/browse/causation-miscellaneous' rel='section'>Causation, Miscellaneous</a><span class='catIn'> in </span><a class='catArea' href='/browse/metaphysics' rel='section'>Metaphysics</a></div> <div><a class='catName' href='/browse/process-theories-of-causation' rel='section'>Process Theories of Causation</a><span class='catIn'> in </span><a class='catArea' href='/browse/metaphysics' rel='section'>Metaphysics</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILMTO-2&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F27845%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILMTO-2'>(2 more)</a>   <div id="la-WILMTO-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILMTO-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILMTO-2" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILMTO-2','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILMTO-2"><i class="fa fa-share-alt"></i> 9 citations</a>   <span class="eMsg" id="msg-WILMTO-2"></span></div></div></li> <li id='eILLCIT-2' onclick="ee('click','ILLCIT-2')" onmouseover="ee('over','ILLCIT-2')" onmouseout="ee('out','ILLCIT-2')" class='entry'><span class="citation"><a target='_blank' href="https://philpapers.org/rec/ILLCIT-2"><span class='pub_name recTitle'><span class='articleTitle recTitle'>Causality in the Sciences.</span></span></a><a class='discreet' title="View other works by Phyllis Illari" href="/s/Phyllis%20Illari"><span class='name'>Phyllis Illari</span></a>, <a class='discreet' title="View other works by Federica Russo" href="/s/Federica%20Russo"><span class='name'>Federica Russo</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> (eds.) - <span class="pubYear">2011</span> - <span class='pubInfo'> Oxford University Press.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">Why do ideas of how mechanisms relate to causality and probability differ so much across the sciences? Can progress in understanding the tools of causal inference in some sciences lead to progress in others? This book tackles these questions and others concerning the use of causality in the sciences. </div><div class="catsCon" id="ecats-con-ILLCIT-2"><div><a class='catName' href='/browse/causal-reasoning-misc' rel='section'>Causal Reasoning, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/epistemology' rel='section'>Epistemology</a></div> </div><div class="options"><div id="la-ILLCIT-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('ILLCIT-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-ILLCIT-2" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('ILLCIT-2','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/ILLCIT-2"><i class="fa fa-share-alt"></i> 6 citations</a>   <span class="eMsg" id="msg-ILLCIT-2"></span></div></div></li> <li id='eWILMTO-6' onclick="ee('click','WILMTO-6')" onmouseover="ee('over','WILMTO-6')" onmouseout="ee('out','WILMTO-6')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILMTO-6#analytics'><span style='color:#109D49'>48 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILMTO-6"><span class='articleTitle recTitle'>Mechanistic Theories of Causality Part I.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2011</span> - <span class='pubInfo'> <em class='pubName'>Philosophy Compass</em> 6 (6):421-432.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">Part I of this paper introduces a range of mechanistic theories of causality, including process theories and the complex-systems theories, and some of the problems they face. Part II argues that while there is a decisive case against a purely mechanistic analysis, a viable theory of causality must incorporate mechanisms as an ingredient, and describes one way of providing an analysis of causality which reaps the rewards of the mechanistic approach without succumbing to its pitfalls. </div><div class="catsCon" id="ecats-con-WILMTO-6"><div><a class='catName' href='/browse/causation-miscellaneous' rel='section'>Causation, Miscellaneous</a><span class='catIn'> in </span><a class='catArea' href='/browse/metaphysics' rel='section'>Metaphysics</a></div> <div><a class='catName' href='/browse/process-theories-of-causation' rel='section'>Process Theories of Causation</a><span class='catIn'> in </span><a class='catArea' href='/browse/metaphysics' rel='section'>Metaphysics</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILMTO-6&proxyId=&u=http%3A%2F%2Fdx.doi.org%2F10.1111%2Fj.1747-9991.2011.00400.x" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILMTO-6'>(5 more)</a>   <div id="la-WILMTO-6" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILMTO-6')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILMTO-6" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILMTO-6','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILMTO-6"><i class="fa fa-share-alt"></i> 9 citations</a>   <span class="eMsg" id="msg-WILMTO-6"></span></div></div></li> <li id='eWILDVE' onclick="ee('click','WILDVE')" onmouseover="ee('over','WILDVE')" onmouseout="ee('out','WILDVE')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILDVE#analytics'><span style='color:#109D49'>114 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILDVE"><span class='articleTitle recTitle'>Dispositional Versus Epistemic Causality.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2006</span> - <span class='pubInfo'> <em class='pubName'>Minds and Machines</em> 16 (3):259-276.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">I put forward several desiderata that a philosophical theory of causality should satisfy: it should account for the objectivity of causality, it should underpin formalisms for causal reasoning, it should admit a viable epistemology, it should be able to cope with the great variety of causal claims that are made, and it should be ontologically parsimonious. I argue that Nancy Cartwright’s dispositional account of causality goes part way towards meeting these criteria but is lacking in important respects. I go on<span id="WILDVE-absexp"> (<span class="ll" onclick='$("WILDVE-abstract2").show();$("WILDVE-absexp").hide()'>...</span>)</span><span id="WILDVE-abstract2" style="display:none"> to argue that my epistemic account, which ties causal relationships to an agent’s knowledge and ignorance, performs well in the light of the desiderata. Such an account, I claim, is all we require from a theory of causality. (<span class="ll" onclick='$("WILDVE-abstract2").hide();$("WILDVE-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILDVE"><div><a class='catName' href='/browse/causal-reasoning-misc' rel='section'>Causal Reasoning, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/epistemology' rel='section'>Epistemology</a></div> <div><a class='catName' href='/browse/philosophy-of-artificial-intelligence' rel='section'>Philosophy of Artificial Intelligence</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-cognitive-science' rel='section'>Philosophy of Cognitive Science</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILDVE&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2006%2Fdispositions.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILDVE'>(6 more)</a>   <div id="la-WILDVE" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILDVE')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILDVE" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILDVE','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILDVE"><i class="fa fa-share-alt"></i> 13 citations</a>   <span class="eMsg" id="msg-WILDVE"></span></div></div></li> <li id='eWILFBT-8' onclick="ee('click','WILFBT-8')" onmouseover="ee('over','WILFBT-8')" onmouseout="ee('out','WILFBT-8')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILFBT-8#analytics'><span style='color:#109D49'>267 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILFBT-8"><span class='articleTitle recTitle'>From Bayesianism to the Epistemic View of Mathematics: Review of R. Jeffrey, <Em>Subjective Probability: The Real Thing</Em>. <span class='hint'>[REVIEW]</span></span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2006</span> - <span class='pubInfo'> <em class='pubName'>Philosophia Mathematica</em> 14 (3):365-369.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">Subjective Probability: The Real Thing is the last book written by the late Richard Jeffrey, a key proponent of the Bayesian interpretation of probability.Bayesians hold that probability is a mental notion: saying that the probability of rain is 0.7 is just saying that you believe it will rain to degree 0.7. Degrees of belief are themselves cashed out in terms of bets—in this case you consider 7:3 to be fair odds for a bet on rain. There are two extreme Bayesian<span id="WILFBT-8-absexp"> (<span class="ll" onclick='$("WILFBT-8-abstract2").show();$("WILFBT-8-absexp").hide()'>...</span>)</span><span id="WILFBT-8-abstract2" style="display:none"> positions. Strict subjectivists think that an agent can adopt whatever degrees of belief she likes, as long as they satisfy the axioms of probability. Thus your degree of belief in rain and degree of belief in no rain must sum to one but are otherwise unconstrained. At the other extreme, objectivists claim that an agent's background knowledge considerably narrows down the choice of appropriate degrees of belief. In particular, if you know only that the frequency of rain is 0.7 then you should believe it will rain to degree 0.7; if you know absolutely nothing about the weather then you should set your degree of belief in rain to be 0.5; in neither of these cases is there room for subjective choice of degree of belief. In this book, Jeffrey advocates what is sometimes called empirically-based subjectivism, a position that lies between the two extremes of strict subjectivism and objectivism. According to this position, knowledge of frequencies constrains degree of belief, but lack of knowledge does not impose any constraints, so that if you know nothing about the weather you may adopt any degree of belief in rain you like.1The aim of the book is not so much to justify this point of view as to provide a comprehensive exposition of probability theory from the …. (<span class="ll" onclick='$("WILFBT-8-abstract2").hide();$("WILFBT-8-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILFBT-8"><div><a class='catName' href='/browse/bayesian-reasoning-misc' rel='section'>Bayesian Reasoning, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> <div><a class='catName' href='/browse/degrees-of-belief' rel='section'>Degrees of Belief</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> <div><a class='catName' href='/browse/epistemology-of-mathematics-misc' rel='section'>Epistemology of Mathematics, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-mathematics' rel='section'>Philosophy of Mathematics</a></div> <div><a class='catName' href='/browse/philosophy-of-mathematics' rel='section'>Philosophy of Mathematics</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILFBT-8&proxyId=&u=http%3A%2F%2Fdx.doi.org%2F10.1093%2Fphilmat%2Fnkj018" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILFBT-8'>(8 more)</a>   <div id="la-WILFBT-8" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILFBT-8')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILFBT-8" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILFBT-8','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILFBT-8"></span></div></div></li> <li id='eRUSETI' onclick="ee('click','RUSETI')" onmouseover="ee('over','RUSETI')" onmouseout="ee('out','RUSETI')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/RUSETI#analytics'><span style='color:#109D49'>66 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/RUSETI"><span class='articleTitle recTitle'>EnviroGenomarkers: The Interplay Between Mechanisms and Difference Making in Establishing Causal Claims.</span></a><a class='discreet' title="View other works by Federica Russo" href="/s/Federica%20Russo"><span class='name'>Federica Russo</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2012</span> - <span class='pubInfo'> <em class='pubName'>Medicine Studies</em> 3 (4):249-262.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">According to Russo and Williamson :157–170, 2007, Hist Philos Life Sci 33:389–396, 2011a, Philos Sci 1:47–69, 2011b), in order to establish a causal claim of the form, ‘C is a cause of E’, one typically needs evidence that there is an underlying mechanism between C and E as well as evidence that C makes a difference to E. This thesis has been used to argue that hierarchies of evidence, as championed by evidence-based movements, tend to give primacy to evidence of<span id="RUSETI-absexp"> (<span class="ll" onclick='$("RUSETI-abstract2").show();$("RUSETI-absexp").hide()'>...</span>)</span><span id="RUSETI-abstract2" style="display:none"> difference making over evidence of mechanisms and are flawed because the two sorts of evidence are required and they should be treated on a par. An alternative approach gives primacy to evidence of mechanism over evidence of difference making. In this paper, we argue that this alternative approach is equally flawed, again because both sorts of evidence need to be treated on a par. As an illustration of this parity, we explain how scientists working in the ‘EnviroGenomarkers’ project constantly make use of the two evidential components in a dynamic and intertwined way. We argue that such an interplay is needed not only for causal assessment but also for policy purposes. (<span class="ll" onclick='$("RUSETI-abstract2").hide();$("RUSETI-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-RUSETI"><div><a class='catName' href='/browse/evidence-and-knowledge' rel='section'>Evidence and Knowledge</a><span class='catIn'> in </span><a class='catArea' href='/browse/epistemology' rel='section'>Epistemology</a></div> <div><a class='catName' href='/browse/medical-ethics' rel='section'>Medical Ethics</a><span class='catIn'> in </span><a class='catArea' href='/browse/applied-ethics' rel='section'>Applied Ethics</a></div> <div><a class='catName' href='/browse/scientific-method' rel='section'>Scientific Method</a><span class='catIn'> in </span><a class='catArea' href='/browse/general-philosophy-of-science' rel='section'>General Philosophy of Science</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=RUSETI&proxyId=&u=http%3A%2F%2Flink.springer.com%2Fcontent%2Fpdf%2F10.1007%252Fs12376-012-0079-7.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/RUSETI'>(5 more)</a>   <div id="tr-RUSETI" title="Translate" class="yui-skin-sam ldiv" style="cursor:pointer" onclick="translateEntry('RUSETI')"><i class="fa fa-language"></i> Translate</div>   <div id="la-RUSETI" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('RUSETI')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-RUSETI" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('RUSETI','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/RUSETI"><i class="fa fa-share-alt"></i> 7 citations</a>   <span class="eMsg" id="msg-RUSETI"></span></div></div></li> <li id='eWILJTP-4' onclick="ee('click','WILJTP-4')" onmouseover="ee('over','WILJTP-4')" onmouseout="ee('out','WILJTP-4')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILJTP-4#analytics'><span style='color:#109D49'>14 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILJTP-4"><span class='articleTitle recTitle'>Justifying the Principle of Indifference.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2018</span> - <span class='pubInfo'> <em class='pubName'>European Journal for Philosophy of Science</em> 8 (3):559-586.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">This paper presents a new argument for the Principle of Indifference. This argument can be thought of in two ways: as a pragmatic argument, justifying the principle as needing to hold if one is to minimise worst-case expected loss, or as an epistemic argument, justifying the principle as needing to hold in order to minimise worst-case expected inaccuracy. The question arises as to which interpretation is preferable. I show that the epistemic argument contradicts Evidentialism and suggest that the relative plausibility<span id="WILJTP-4-absexp"> (<span class="ll" onclick='$("WILJTP-4-abstract2").show();$("WILJTP-4-absexp").hide()'>...</span>)</span><span id="WILJTP-4-abstract2" style="display:none"> of Evidentialism provides grounds to prefer the pragmatic interpretation. If this is right, it extends to a general preference for pragmatic arguments for the Principle of Indifference, and also to a general preference for pragmatic arguments for other norms of Bayesian epistemology. (<span class="ll" onclick='$("WILJTP-4-abstract2").hide();$("WILJTP-4-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILJTP-4"><div><a class='catName' href='/browse/science-logic-and-mathematics' rel='section'>Science, Logic, and Mathematics</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILJTP-4&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F66127%2F1%2FECPI.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILJTP-4'>(7 more)</a>   <div id="la-WILJTP-4" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILJTP-4')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILJTP-4" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILJTP-4','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILJTP-4"><i class="fa fa-share-alt"></i> 2 citations</a>   <span class="eMsg" id="msg-WILJTP-4"></span></div></div></li> <li id='eWILPTO-3' onclick="ee('click','WILPTO-3')" onmouseover="ee('over','WILPTO-3')" onmouseout="ee('out','WILPTO-3')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILPTO-3#analytics'><span style='color:#109D49'>146 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILPTO-3"><span class='articleTitle recTitle'>Probabilistic Theories of Causality.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2009</span> - <span class='pubInfo'> In Helen Beebee, Peter Menzies & Christopher Hitchcock (eds.), <em><a href="https://philpapers.org/rec/BEETOH">The Oxford Handbook of Causation</a></em>. Oxford University Press. pp. 185--212.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">This chapter provides an overview of a range of probabilistic theories of causality, including those of Reichenbach, Good and Suppes, and the contemporary causal net approach. It discusses two key problems for probabilistic accounts: counterexamples to these theories and their failure to account for the relationship between causality and mechanisms. It is argued that to overcome the problems, an epistemic theory of causality is required. </div><div class="catsCon" id="ecats-con-WILPTO-3"><div><a class='catName' href='/browse/statistical-theories-of-causation' rel='section'>Statistical Theories of Causation</a><span class='catIn'> in </span><a class='catArea' href='/browse/metaphysics' rel='section'>Metaphysics</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILPTO-3&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F23596%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a>   <div id="la-WILPTO-3" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILPTO-3')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILPTO-3" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILPTO-3','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILPTO-3"><i class="fa fa-share-alt"></i> 9 citations</a>   <span class="eMsg" id="msg-WILPTO-3"></span></div></div></li> <li id='eILLWLA' onclick="ee('click','ILLWLA')" onmouseover="ee('over','ILLWLA')" onmouseout="ee('out','ILLWLA')" class='entry'><span class="citation"><a target='_blank' href="https://philpapers.org/rec/ILLWLA"><span class='articleTitle recTitle'>Why Look at Causality in the Sciences?</span></a><a class='discreet' title="View other works by Phyllis McKay Illari" href="/s/Phyllis McKay%20Illari"><span class='name'>Phyllis McKay Illari</span></a>, <a class='discreet' title="View other works by Federica Russo" href="/s/Federica%20Russo"><span class='name'>Federica Russo</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2011</span> - <span class='pubInfo'> In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), <em><a href="https://philpapers.org/rec/MCKCIT">Causality in the Sciences</a></em>. Oxford University Press.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="catsCon" id="ecats-con-ILLWLA">No categories</div><div class="options"><div id="la-ILLWLA" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('ILLWLA')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-ILLWLA" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('ILLWLA','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/ILLWLA"><i class="fa fa-share-alt"></i> 8 citations</a>   <span class="eMsg" id="msg-ILLWLA"></span></div></div></li> <li id='eCASMFP-4' onclick="ee('click','CASMFP-4')" onmouseover="ee('over','CASMFP-4')" onmouseout="ee('out','CASMFP-4')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/CASMFP-4#analytics'><span style='color:#109D49'>19 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/CASMFP-4"><span class='articleTitle recTitle'>Models for Prediction, Explanation and Control: Recursive Bayesian Networks.</span></a><a class='discreet' title="View other works by Lorenzo Casini" href="/s/Lorenzo%20Casini"><span class='name'>Lorenzo Casini</span></a>, <a class='discreet' title="View other works by Phyllis McKay Illari" href="/s/Phyllis McKay%20Illari"><span class='name'>Phyllis McKay Illari</span></a>, <a class='discreet' title="View other works by Federica Russo" href="/s/Federica%20Russo"><span class='name'>Federica Russo</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2011</span> - <span class='pubInfo'> <em class='pubName'>Theoria : An International Journal for Theory, History and Fundations of Science</em> 26 (1):5-33.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">The Recursive Bayesian Net formalism was originally developed for modelling nested causal relationships. In this paper we argue that the formalism can also be applied to modelling the hierarchical structure of mechanisms. The resulting network contains quantitative information about probabilities, as well as qualitative information about mechanistic structure and causal relations. Since information about probabilities, mechanisms and causal relations is vital for prediction, explanation and control respectively, an RBN can be applied to all these tasks. We show in particular how<span id="CASMFP-4-absexp"> (<span class="ll" onclick='$("CASMFP-4-abstract2").show();$("CASMFP-4-absexp").hide()'>...</span>)</span><span id="CASMFP-4-abstract2" style="display:none"> a simple two-level RBN can be used to model a mechanism in cancer science. The higher level of our model contains variables at the clinical level, while the lower level maps the structure of the cell's mechanism for apoptosis. (<span class="ll" onclick='$("CASMFP-4-abstract2").hide();$("CASMFP-4-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-CASMFP-4">No categories</div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=CASMFP-4&proxyId=&u=http%3A%2F%2Fphilsci-archive.pitt.edu%2F10288%2F1%2F784-3409-1-PB.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/CASMFP-4'>(6 more)</a>   <div id="la-CASMFP-4" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('CASMFP-4')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-CASMFP-4" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('CASMFP-4','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/CASMFP-4"><i class="fa fa-share-alt"></i> 7 citations</a>   <span class="eMsg" id="msg-CASMFP-4"></span></div></div></li> <li id='eWILPOP-3' onclick="ee('click','WILPOP-3')" onmouseover="ee('over','WILPOP-3')" onmouseout="ee('out','WILPOP-3')" class='entry'><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILPOP-3"><span class='articleTitle recTitle'>Philosophies of Probability: Objective Bayesianism and its Challenges.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">manuscript</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">This chapter presents an overview of the major interpretations of probability followed by an outline of the objective Bayesian interpretation and a discussion of the key challenges it faces. I discuss the ramifications of interpretations of probability and objective Bayesianism for the philosophy of mathematics in general. </div><div class="catsCon" id="ecats-con-WILPOP-3"><div><a class='catName' href='/browse/bayesian-reasoning-misc' rel='section'>Bayesian Reasoning, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> <div><a class='catName' href='/browse/logical-probability' rel='section'>Logical Probability</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><div id="la-WILPOP-3" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILPOP-3')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILPOP-3" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILPOP-3','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILPOP-3"><i class="fa fa-share-alt"></i> 9 citations</a>   <span class="eMsg" id="msg-WILPOP-3"></span></div></div></li> <li id='eWILEPI-4' onclick="ee('click','WILEPI-4')" onmouseover="ee('over','WILEPI-4')" onmouseout="ee('out','WILEPI-4')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILEPI-4#analytics'><span style='color:#109D49'>6 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILEPI-4"><span class='articleTitle recTitle'>Evidential Proximity, Independence, and the Evaluation of Carcinogenicity.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2019</span> - <span class='pubInfo'> <em class='pubName'>Journal of Evaluation in Clinical Practice</em> 25 (6):955-961.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">This paper analyses the methods of the International Agency for Research on Cancer for evaluating the carcinogenicity of various agents. I identify two fundamental evidential principles that underpin these methods, which I call Evidential Proximity and Independence. I then show, by considering the 2018 evaluation of the carcinogenicity of styrene and styrene‐7,8‐oxide, that these principles have been implemented in a way that can lead to inconsistency. I suggest a way to resolve this problem: admit a general exception to Independence and<span id="WILEPI-4-absexp"> (<span class="ll" onclick='$("WILEPI-4-abstract2").show();$("WILEPI-4-absexp").hide()'>...</span>)</span><span id="WILEPI-4-abstract2" style="display:none"> treat the implementation of Evidential Proximity more flexibly where this exception applies. I show that this suggestion is compatible with the general principles laid down in the 2019 version of IARC's methods guide, its Preamble to the Monographs. (<span class="ll" onclick='$("WILEPI-4-abstract2").hide();$("WILEPI-4-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILEPI-4">No categories</div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILEPI-4&proxyId=&u=https%3A%2F%2Fkar.kent.ac.uk%2F75285%2F1%2FEPEC.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILEPI-4'>(4 more)</a>   <div id="la-WILEPI-4" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILEPI-4')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILEPI-4" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILEPI-4','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILEPI-4"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILEPI-4"></span></div></div></li> <li id='eWILITA-3' onclick="ee('click','WILITA-3')" onmouseover="ee('over','WILITA-3')" onmouseout="ee('out','WILITA-3')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILITA-3#analytics'><span style='color:#109D49'>125 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILITA-3"><span class='articleTitle recTitle'>Imaging Technology and the Philosophy of Causality.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2011</span> - <span class='pubInfo'> <em class='pubName'>Philosophy and Technology</em> 24 (2):115-136.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">Russo and Williamson (Int Stud Philos Sci 21(2):157–170, 2007) put forward the thesis that, at least in the health sciences, to establish the claim that C is a cause of E, one normally needs evidence of an underlying mechanism linking C and E as well as evidence that C makes a difference to E. This epistemological thesis poses a problem for most current analyses of causality which, in virtue of analysing causality in terms of just one of mechanisms or difference<span id="WILITA-3-absexp"> (<span class="ll" onclick='$("WILITA-3-abstract2").show();$("WILITA-3-absexp").hide()'>...</span>)</span><span id="WILITA-3-abstract2" style="display:none"> making, cannot account for the need for the other kind of evidence. Weber (Int Stud Philos Sci 23(2):277–295, 2009) has suggested to the contrary that Giere’s probabilistic analysis of causality survives this criticism. In this paper, we look in detail at the case of medical imaging technology, which, we argue, supports the thesis of Russo and Williamson, and we respond to Weber’s suggestion, arguing that Giere’s account does not survive the criticism. (<span class="ll" onclick='$("WILITA-3-abstract2").hide();$("WILITA-3-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILITA-3"><div><a class='catName' href='/browse/formal-epistemology' rel='section'>Formal Epistemology</a><span class='catIn'> in </span><a class='catArea' href='/browse/epistemology' rel='section'>Epistemology</a></div> <div><a class='catName' href='/browse/observation-misc' rel='section'>Observation, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/general-philosophy-of-science' rel='section'>General Philosophy of Science</a></div> <div><a class='catName' href='/browse/theories-of-causation-misc' rel='section'>Theories of Causation, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/metaphysics' rel='section'>Metaphysics</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILITA-3&proxyId=&u=http%3A%2F%2Fdx.doi.org%2F10.1007%2Fs13347-010-0010-7" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILITA-3'>(3 more)</a>   <div id="la-WILITA-3" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILITA-3')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILITA-3" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILITA-3','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILITA-3"><i class="fa fa-share-alt"></i> 6 citations</a>   <span class="eMsg" id="msg-WILITA-3"></span></div></div></li> <li id='eWILC-2' onclick="ee('click','WILC-2')" onmouseover="ee('over','WILC-2')" onmouseout="ee('out','WILC-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILC-2#analytics'><span style='color:#109D49'>82 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILC-2"><span class='articleTitle recTitle'>Causality.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">manuscript</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">This chapter addresses two questions: what are causal relationships? how can one discover causal relationships? I provide a survey of the principal answers given to these questions, followed by an introduction to my own view, epistemic causality, and then a comparison of epistemic causality with accounts provided by Judea Pearl and Huw Price. </div><div class="catsCon" id="ecats-con-WILC-2"><div><a class='catName' href='/browse/bayesian-reasoning' rel='section'>Bayesian Reasoning</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILC-2&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F2509%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILC-2'>(2 more)</a>   <div id="la-WILC-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILC-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILC-2" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILC-2','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILC-2"><i class="fa fa-share-alt"></i> 9 citations</a>   <span class="eMsg" id="msg-WILC-2"></span></div></div></li> <li id='eWILPOP-7' onclick="ee('click','WILPOP-7')" onmouseover="ee('over','WILPOP-7')" onmouseout="ee('out','WILPOP-7')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILPOP-7#analytics'><span style='color:#109D49'>23 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILPOP-7"><span class='articleTitle recTitle'>Philosophies of Probability.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">unknown</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">This chapter presents an overview of the major interpretations of probability followed by an outline of the objective Bayesian interpretation and a discussion of the key challenges it faces. I discuss the ramifications of interpretations of probability and objective Bayesianism for the philosophy of mathematics in general. </div><div class="catsCon" id="ecats-con-WILPOP-7"><div><a class='catName' href='/browse/bayesian-reasoning-misc' rel='section'>Bayesian Reasoning, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILPOP-7&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F20892%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a>   <div id="la-WILPOP-7" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILPOP-7')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILPOP-7" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILPOP-7','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILPOP-7"><i class="fa fa-share-alt"></i> 8 citations</a>   <span class="eMsg" id="msg-WILPOP-7"></span></div></div></li> <li id='eWHEEPA' onclick="ee('click','WHEEPA')" onmouseover="ee('over','WHEEPA')" onmouseout="ee('out','WHEEPA')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WHEEPA#analytics'><span style='color:#109D49'>146 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WHEEPA"><span class='articleTitle recTitle'>Evidential Probability and Objective Bayesian Epistemology.</span></a><a class='discreet' title="View other works by Gregory Wheeler" href="/s/Gregory%20Wheeler"><span class='name'>Gregory Wheeler</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2011</span> - <span class='pubInfo'> In Prasanta S. Bandyopadhyay & Malcolm Forster (eds.), <em><a href="https://philpapers.org/rec/BANHOT-2">Handbook of the Philosophy of Science, Vol. 7: Philosophy of Statistics</a></em>. Elsevier.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">In this chapter we draw connections between two seemingly opposing approaches to probability and statistics: evidential probability on the one hand and objective Bayesian epistemology on the other. </div><div class="catsCon" id="ecats-con-WHEEPA"><div><a class='catName' href='/browse/bayesian-reasoning-misc' rel='section'>Bayesian Reasoning, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> <div><a class='catName' href='/browse/formal-epistemology-misc' rel='section'>Formal Epistemology, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/epistemology' rel='section'>Epistemology</a></div> <div><a class='catName' href='/browse/logical-probability' rel='section'>Logical Probability</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WHEEPA&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F27949%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a>   <div id="la-WHEEPA" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WHEEPA')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WHEEPA" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WHEEPA','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WHEEPA"><i class="fa fa-share-alt"></i> 5 citations</a>   <span class="eMsg" id="msg-WHEEPA"></span></div></div></li> <li id='eWALFAT-8' onclick="ee('click','WALFAT-8')" onmouseover="ee('over','WALFAT-8')" onmouseout="ee('out','WALFAT-8')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WALFAT-8#analytics'><span style='color:#109D49'>5 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WALFAT-8"><span class='articleTitle recTitle'>Four Approaches to the Reference Class Problem.</span></a><a class='discreet' title="View other works by Christian Wallmann" href="/s/Christian%20Wallmann"><span class='name'>Christian Wallmann</span></a> & <a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">unknown</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="catsCon" id="ecats-con-WALFAT-8">No categories</div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WALFAT-8&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F61556%2F1%2FRCP.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WALFAT-8'>(4 more)</a>   <div id="la-WALFAT-8" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WALFAT-8')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WALFAT-8" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WALFAT-8','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WALFAT-8"><i class="fa fa-share-alt"></i> 2 citations</a>   <span class="eMsg" id="msg-WALFAT-8"></span></div></div></li> <li id='eWILETT-3' onclick="ee('click','WILETT-3')" onmouseover="ee('over','WILETT-3')" onmouseout="ee('out','WILETT-3')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILETT-3#analytics'><span style='color:#109D49'>22 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILETT-3"><span class='articleTitle recTitle'>Establishing the Teratogenicity of Zika and Evaluating Causal Criteria.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">forthcoming</span> - <span class='pubInfo'> <em class='pubName'>Synthese</em>:1-14.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">The teratogenicity of the Zika virus was considered established in 2016, and is an interesting case because three different sets of causal criteria were used to assess teratogenicity. This paper appeals to the thesis of Russo and Williamson to devise an epistemological framework that can be used to compare and evaluate sets of causal criteria. The framework can also be used to decide when enough criteria are satisfied to establish causality. Arguably, the three sets of causal criteria considered here offer<span id="WILETT-3-absexp"> (<span class="ll" onclick='$("WILETT-3-abstract2").show();$("WILETT-3-absexp").hide()'>...</span>)</span><span id="WILETT-3-abstract2" style="display:none"> only a rudimentary assessment of mechanistic studies, and some suggestions are made as to alternative ways to establish causality. (<span class="ll" onclick='$("WILETT-3-abstract2").hide();$("WILETT-3-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILETT-3">No categories</div><div class="options"><a rel="nofollow" href="https://philpapers.org/go.pl?id=WILETT-3&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F67423%2F1%2Fzika.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> <a href='/rec/WILETT-3'>(8 more)</a>   <div id="la-WILETT-3" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILETT-3')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILETT-3" class="yui-skin-sam ldiv"> </div><span title="Bookmark this publication" class="ll" onclick="showLists('WILETT-3','')"><i class="fa fa-bookmark"></i> Bookmark<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILETT-3"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILETT-3"></span></div></div></li> <li id='eWILII' onclick="ee('click','WILII')" onmouseover="ee('over','WILII')" onmouseout="ee('out','WILII')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILII#analytics'><span style='color:#109D49'>99 <i class="fa fa-download"></i></span></a></div><span class="citation"><a target='_blank' href="https://philpapers.org/rec/WILII"><span class='articleTitle recTitle'>Inductive Influence.</span></a><a class='discreet' title="View other works by Jon Williamson" href="/s/Jon%20Williamson"><span class='name'>Jon Williamson</span></a> - <span class="pubYear">2007</span> - <span class='pubInfo'> <em class='pubName'>British Journal for the Philosophy of Science</em> 58 (4):689 - 708.</span></span><span class='toggle' style='display:none' data-target='extras'>details</span><div class="extras"><div class="abstract">Objective Bayesianism has been criticised for not allowing learning from experience: it is claimed that an agent must give degree of belief ½ to the next raven being black, however many other black ravens have been observed. I argue that this objection can be overcome by appealing to objective Bayesian nets, a formalism for representing objective Bayesian degrees of belief. Under this account, previous observations exert an inductive influence on the next observation. I show how this approach can be used<span id="WILII-absexp"> (<span class="ll" onclick='$("WILII-abstract2").show();$("WILII-absexp").hide()'>...</span>)</span><span id="WILII-abstract2" style="display:none"> to capture the Johnson-Carnap continuum of inductive methods, as well as the Nix-Paris continuum, and show how inductive influence can be measured. 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