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Profile: Jon Williamson (University of Kent at Canterbury)
  1.  5
    Jon Williamson (2010). In Defence of Objective Bayesianism. OUP Oxford.
    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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  2.  37
    Federica Russo & Jon Williamson (2007). Interpreting Causality in the Health Sciences. 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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  3.  40
    Jon Williamson (2004). Bayesian Nets and Causality: Philosophical and Computational Foundations. OUP Oxford.
    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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  4.  33
    Federica Russo & Jon Williamson (2011). Generic Versus Single-Case Causality: The Case of Autopsy. [REVIEW] 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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  5.  74
    Phyllis Illari & Jon Williamson (2012). What is a Mechanism? Thinking About Mechanisms Across the Sciences. 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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  6.  32
    Rolf Haenni, Jan-Willem Romeijn, Gregory Wheeler & Jon Williamson (2011). Probabilistic Logics and Probabilistic Networks. Synthese Library.
    Additionally, the text shows how to develop computationally feasible methods to mesh with this framework.
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  7.  14
    Brendan Clarke, Donald Gillies, Phyllis Illari, Frederica Russo & Jon Williamson (2013). The Evidence That Evidence-Based Medicine Omits. 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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  8. Jon Williamson, Maximising Entropy Efficiently.
    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="http://philpapers.org/go.pl?id=WILMEE&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2002%2Fmaxenteffic.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILMEE'>3 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="Save in your personal bibliography" class="ll" onclick="showLists('WILMEE','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILMEE"></span></div></div></li> <li id='eHAWTPP-3' onclick="ee('click','HAWTPP-3')" onmouseover="ee('over','HAWTPP-3')" onmouseout="ee('out','HAWTPP-3')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/HAWTPP-3#analytics'><span style='color:#10A010'>12 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/HAWTPP-3"><span class='name'>James Hawthorne</span>, <span class='name'>Jürgen Landes</span>, <span class='name'>Christian Wallmann</span> & <span class='name'>Jon Williamson</span> (forthcoming). <span class='articleTitle recTitle'>The Principal Principle Implies the Principle of Indifference.</span></a><span class='pubInfo'> <em class='pubName'>British Journal for the Philosophy of Science</em>:axv030.</span></span><div class="extras"><div class="abstract">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. </div><div class="catsCon" id="ecats-con-HAWTPP-3"><div><a class='catName' href='/browse/chance-credence-principles' rel='section'>Chance-Credence Principles</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a><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 class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=HAWTPP-3&proxyId=&u=http%3A%2F%2Fbjps.oxfordjournals.org%2Fcgi%2Fcontent%2Fshort%2Faxv030v1%3Frss%3D1" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/HAWTPP-3'>6 more</a>)   <div id="la-HAWTPP-3" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('HAWTPP-3')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-HAWTPP-3" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('HAWTPP-3','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-HAWTPP-3"></span></div></div></li> <li id='eCLAMAT-3' onclick="ee('click','CLAMAT-3')" onmouseover="ee('over','CLAMAT-3')" onmouseout="ee('out','CLAMAT-3')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/CLAMAT-3#analytics'><span style='color:#10A010'>31 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/CLAMAT-3"><span class='name'>Brendan Clarke</span>, <span class='name'>Donald Gillies</span>, <span class='name'>Phyllis Illari</span>, <span class='name'>Federica Russo</span> & <span class='name'>Jon Williamson</span> (2014). <span class='articleTitle recTitle'>Mechanisms and the Evidence Hierarchy.</span></a><span class='pubInfo'> <em class='pubName'>Topoi</em> 33 (2):339-360.</span></span><div class="extras"><div class="abstract">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<span id="CLAMAT-3-absexp"> (<span class="ll" onclick='$("CLAMAT-3-abstract2").show();$("CLAMAT-3-absexp").hide()'>...</span>)</span><span id="CLAMAT-3-abstract2" style="display:none"> explicit protocols for evaluating evidence. Next we provide case studies which exemplify the ways in which evidence of mechanisms complements evidence of correlation in practice. Finally, we put forward some general considerations as to how the two sorts of evidence can be more closely integrated by EBM. (<span class="ll" onclick='$("CLAMAT-3-abstract2").hide();$("CLAMAT-3-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-CLAMAT-3"><div><a class='catName' href='/browse/value-theory' rel='section'>Value Theory</a></div> </div><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=CLAMAT-3&proxyId=&u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11245-013-9220-9" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/CLAMAT-3'>6 more</a>)   <div id="la-CLAMAT-3" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('CLAMAT-3')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-CLAMAT-3" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('CLAMAT-3','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/CLAMAT-3"><i class="fa fa-share-alt"></i> 2 citations</a>   <span class="eMsg" id="msg-CLAMAT-3"></span></div></div></li> <li id='eRUSECA-3' onclick="ee('click','RUSECA-3')" onmouseover="ee('over','RUSECA-3')" onmouseout="ee('out','RUSECA-3')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/RUSECA-3#analytics'><span style='color:#10A010'>9 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/RUSECA-3"><span class='name'>Federica Russo</span> & <span class='name'>Jon Williamson</span> (2011). <span class='articleTitle recTitle'>Epistemic Causality and Evidence-Based Medicine.</span></a><span class='pubInfo'> <em class='pubName'>History and Philosophy of the Life Sciences</em> 33 (4).</span></span><div class="extras"><div class="abstract">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<span id="RUSECA-3-absexp"> (<span class="ll" onclick='$("RUSECA-3-abstract2").show();$("RUSECA-3-absexp").hide()'>...</span>)</span><span id="RUSECA-3-abstract2" style="display:none"> inferences (e.g., diagnoses and prognoses) are appropriate, rather than about the presence of some physical causal relation analogous to distance or gravitational attraction. It is shown that the epistemic theory has important consequences for medical practice, in particular with regard to evidence-based causal assessment. (<span class="ll" onclick='$("RUSECA-3-abstract2").hide();$("RUSECA-3-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-RUSECA-3"><div><a class='catName' href='/browse/philosophy-of-medicine' rel='section'>Philosophy of Medicine</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-science-misc' rel='section'>Philosophy of Science, Misc</a></div> </div><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=RUSECA-3&proxyId=&u=http%3A%2F%2Fphilsci-archive.pitt.edu%2F8351%2F1%2Fepcause-medicine.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/RUSECA-3'>4 more</a>)   <div id="la-RUSECA-3" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('RUSECA-3')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-RUSECA-3" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('RUSECA-3','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/RUSECA-3"><i class="fa fa-share-alt"></i> 5 citations</a>   <span class="eMsg" id="msg-RUSECA-3"></span></div></div></li> <li id='eILLFAO' onclick="ee('click','ILLFAO')" onmouseover="ee('over','ILLFAO')" onmouseout="ee('out','ILLFAO')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/ILLFAO#analytics'><span style='color:#10A010'>21 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/ILLFAO"><span class='name'>Phyllis McKay Illari</span> & <span class='name'>Jon Williamson</span> (2010). <span class='articleTitle recTitle'>Function and Organization: Comparing the Mechanisms of Protein Synthesis and Natural Selection.</span></a><span class='pubInfo'> <em class='pubName'>Studies in History and Philosophy of Science Part C</em> 41 (3):279-291.</span></span><div class="extras"><div class="abstract">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<span id="ILLFAO-absexp"> (<span class="ll" onclick='$("ILLFAO-abstract2").show();$("ILLFAO-absexp").hide()'>...</span>)</span><span id="ILLFAO-abstract2" style="display:none"> of natural selection.We take each element of mechanistic explanation in turn. Having appreciated the importance of functional individuation, we show how decomposition and organization should be better understood in these terms. We thereby show that mechanistic explanation by protein synthesis and natural selection are more closely analogous than they appear—both possess all three of these core elements of a mechanism widely recognized in the mechanisms literature. (<span class="ll" onclick='$("ILLFAO-abstract2").hide();$("ILLFAO-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-ILLFAO"><div><a class='catName' href='/browse/evolutionary-biology' rel='section'>Evolutionary Biology</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-biology' rel='section'>Philosophy of Biology</a></div> </div><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=ILLFAO&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2010%2FFunctionOrganisation.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/ILLFAO'>4 more</a>)   <div id="la-ILLFAO" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('ILLFAO')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-ILLFAO" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('ILLFAO','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/ILLFAO"><i class="fa fa-share-alt"></i> 6 citations</a>   <span class="eMsg" id="msg-ILLFAO"></span></div></div></li> <li id='eWILMAR-2' onclick="ee('click','WILMAR-2')" onmouseover="ee('over','WILMAR-2')" onmouseout="ee('out','WILMAR-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILMAR-2#analytics'><span style='color:#10A010'>77 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILMAR-2"><span class='name'>Phyllis McKay Illari</span> & <span class='name'>Jon Williamson</span> (2011). <span class='articleTitle recTitle'>Mechanisms Are Real and Local.</span></a><span class='pubInfo'> In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), <em><a href="http://philpapers.org/rec/MCKCIT">Causality in the Sciences</a></em>. OUP Oxford</span></span><div class="extras"><div class="abstract">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’<span id="WILMAR-2-absexp"> (<span class="ll" onclick='$("WILMAR-2-abstract2").show();$("WILMAR-2-absexp").hide()'>...</span>)</span><span id="WILMAR-2-abstract2" style="display:none"> and ‘physical explanation’. We argue that mechanistic explanation requires that mechanisms are both real and local. We then go on to argue that real, local mechanisms require a broadly active metaphysics for mechanisms, such as a capacities metaphysics. (<span class="ll" onclick='$("WILMAR-2-abstract2").hide();$("WILMAR-2-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILMAR-2"><div><a class='catName' href='/browse/varieties-of-explanation' rel='section'>Varieties of 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="http://philpapers.org/go.pl?id=WILMAR-2&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2009%2Freal-local.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILMAR-2'>2 more</a>)   <div id="la-WILMAR-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILMAR-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILMAR-2" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILMAR-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILMAR-2"><i class="fa fa-share-alt"></i> 4 citations</a>   <span class="eMsg" id="msg-WILMAR-2"></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:#10A010'>79 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILPTO-3"><span class='name'>Jon Williamson</span> (2009). <span class='articleTitle recTitle'>Probabilistic Theories of Causality.</span></a><span class='pubInfo'> In Helen Beebee, Peter Menzies & Christopher Hitchcock (eds.), <em><a href="http://philpapers.org/rec/BEETOH">The Oxford Handbook of Causation</a></em>. Oxford University Press 185--212.</span></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/causation-laws-etc' rel='section'>Causation, Laws, etc</a><span class='catIn'> in </span><a class='catArea' href='/browse/metaphysics' rel='section'>Metaphysics</a></div> </div><div class="options"><div class='affiliateLinks'><span class='price_used bargain'><a class='price_used bargain' target="_blank" rel="nofollow" href="http://www.amazon.com/gp/offer-listing/019927973X?SubscriptionId=AKIAI4HPG2KEPF5SCBQA&tag=philp-20&linkCode=xm2&camp=2025&creative=386001&creativeASIN=019927973X&condition=used">$75.31 used</a></span>   <span class='price_new'><a class='price_new' target="_blank" rel="nofollow" href="http://www.amazon.com/gp/offer-listing/019927973X?SubscriptionId=AKIAI4HPG2KEPF5SCBQA&tag=philp-20&linkCode=xm2&camp=2025&creative=386001&creativeASIN=019927973X&condition=new">$147.62 new</a></span>   <span class='price_amazon'><a class='price_amazon' target="_blank" rel="nofollow" href="http://www.amazon.com/The-Oxford-Handbook-Causation-Handbooks/dp/019927973X?SubscriptionId=AKIAI4HPG2KEPF5SCBQA&tag=philp-20&linkCode=xm2&camp=2025&creative=165953&creativeASIN=019927973X">$180.00 direct from Amazon</a></span>   (collection)   <a href="http://www.amazon.com/The-Oxford-Handbook-Causation-Handbooks/dp/019927973X%3FSubscriptionId%3DAKIAI4HPG2KEPF5SCBQA%26tag%3Dphilp-20%26linkCode%3Dxm2%26camp%3D2025%26creative%3D165953%26creativeASIN%3D019927973X">Amazon page</a></div><a rel="nofollow" href="http://philpapers.org/go.pl?id=WILPTO-3&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2007%2FProbabilisticCausality.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILPTO-3'>3 more</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="Save in your personal bibliography" class="ll" onclick="showLists('WILPTO-3','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILPTO-3"><i class="fa fa-share-alt"></i> 6 citations</a>   <span class="eMsg" id="msg-WILPTO-3"></span></div></div></li> <li id='eWILOBB' onclick="ee('click','WILOBB')" onmouseover="ee('over','WILOBB')" onmouseout="ee('out','WILOBB')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILOBB#analytics'><span style='color:#10A010'>66 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILOBB"><span class='name'>Jon Williamson</span> (2011). <span class='articleTitle recTitle'>Objective Bayesianism, Bayesian Conditionalisation and Voluntarism.</span></a><span class='pubInfo'> <em class='pubName'>Synthese</em> 178 (1):67-85.</span></span><div class="extras"><div class="abstract">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<span id="WILOBB-absexp"> (<span class="ll" onclick='$("WILOBB-abstract2").show();$("WILOBB-absexp").hide()'>...</span>)</span><span id="WILOBB-abstract2" style="display:none"> because diachronic Dutch book arguments are subject to a reductio: in certain circumstances one can Dutch book an agent however she changes her degrees of belief . One may also criticise objective Bayesianism on the grounds that its norms are not compulsory but voluntary, the result of a stance. It is argued that this second objection also misses the mark, since objective Bayesian norms are tied up in the very notion of degrees of belief. (<span class="ll" onclick='$("WILOBB-abstract2").hide();$("WILOBB-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILOBB"><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/doxastic-voluntarism' rel='section'>Doxastic Voluntarism</a><span class='catIn'> in </span><a class='catArea' href='/browse/epistemology' rel='section'>Epistemology</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/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="http://philpapers.org/go.pl?id=WILOBB&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2007%2FOBBCstances.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILOBB'>8 more</a>)   <div id="la-WILOBB" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILOBB')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILOBB" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILOBB','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILOBB"><i class="fa fa-share-alt"></i> 4 citations</a>   <span class="eMsg" id="msg-WILOBB"></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:#10A010'>21 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/RUSETI"><span class='name'>Federica Russo</span> & <span class='name'>Jon Williamson</span> (2012). <span class='articleTitle recTitle'>EnviroGenomarkers: The Interplay Between Mechanisms and Difference Making in Establishing Causal Claims.</span></a><span class='pubInfo'> <em class='pubName'>Medicine Studies</em> 3 (4):249-262.</span></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/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="http://philpapers.org/go.pl?id=RUSETI&proxyId=&u=http%3A%2F%2Flink.springer.com%2Fcontent%2Fpdf%2F10.1007%252Fs12376-012-0079-7" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/RUSETI'>7 more</a>)   <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="Save in your personal bibliography" class="ll" onclick="showLists('RUSETI','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/RUSETI"><i class="fa fa-share-alt"></i> 3 citations</a>   <span class="eMsg" id="msg-RUSETI"></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:#10A010'>40 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILDVE"><span class='name'>Jon Williamson</span> (2006). <span class='articleTitle recTitle'>Dispositional Versus Epistemic Causality.</span></a><span class='pubInfo'> <em class='pubName'>Minds and Machines</em> 16 (3):259-276.</span></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/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="http://philpapers.org/go.pl?id=WILDVE&proxyId=&u=http%3A%2F%2Fwww.lightforcenetwork.com%2Fsites%2Fdefault%2Ffiles%2FJon%2520Williamson%2520-%2520Dispositional%2520vs%2520Epistemic%2520Causes.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILDVE'>7 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="Save in your personal bibliography" class="ll" onclick="showLists('WILDVE','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILDVE"><i class="fa fa-share-alt"></i> 8 citations</a>   <span class="eMsg" id="msg-WILDVE"></span></div></div></li> <li id='eWILCPV' onclick="ee('click','WILCPV')" onmouseover="ee('over','WILCPV')" onmouseout="ee('out','WILCPV')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILCPV#analytics'><span style='color:#10A010'>28 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILCPV"><span class='name'>Jon Williamson</span> (2006). <span class='articleTitle recTitle'>Causal Pluralism Versus Epistemic Causality.</span></a><span class='pubInfo'> <em class='pubName'>Philosophica</em> 77 (1):69-96.</span></span><div class="extras"><div class="abstract">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<span id="WILCPV-absexp"> (<span class="ll" onclick='$("WILCPV-abstract2").show();$("WILCPV-absexp").hide()'>...</span>)</span><span id="WILCPV-abstract2" style="display:none"> – just one eclectic notion. The resolution of this conundrum, I think, requires us to accept that our causal beliefs are generated by a wide variety of indicators, but to deny that this variety of indicators yields a variety of concepts of cause. This focus on the relation between evidence and causal beliefs leads to what I call epistemic causality. Under this view, certain causal beliefs are appropriate or rational on the basis of observed evidence; our notion of cause can be understood purely in terms of these rational beliefs. Causality, then, is a feature of our epistemic representation of the world, rather than of the world itself. This yields one, multifaceted notion of cause. (<span class="ll" onclick='$("WILCPV-abstract2").hide();$("WILCPV-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILCPV"><div><a class='catName' href='/browse/causation-laws-etc' rel='section'>Causation, Laws, etc</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="http://philpapers.org/go.pl?id=WILCPV&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2006%2Fplurality.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILCPV'>4 more</a>)   <div id="la-WILCPV" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILCPV')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILCPV" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILCPV','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILCPV"><i class="fa fa-share-alt"></i> 7 citations</a>   <span class="eMsg" id="msg-WILCPV"></span></div></div></li> <li id='eWILFBT-4' onclick="ee('click','WILFBT-4')" onmouseover="ee('over','WILFBT-4')" onmouseout="ee('out','WILFBT-4')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILFBT-4#analytics'><span style='color:#10A010'>78 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILFBT-4"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>From Bayesianism to the Epistemic View of Mathematics: Remarks Motivated by Richard Jeffrey’s ‘Subjective Probability: The Real Thing.</span></a><span class='pubInfo'></span></span><div class="extras"><div class="catsCon" id="ecats-con-WILFBT-4"><div><a class='catName' href='/browse/probabilistic-frameworks' rel='section'>Probabilistic Frameworks</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="http://philpapers.org/go.pl?id=WILFBT-4&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F7450%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILFBT-4'>2 more</a>)   <div id="la-WILFBT-4" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILFBT-4')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILFBT-4" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILFBT-4','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILFBT-4"></span></div></div></li> <li id='eWILICI-2' onclick="ee('click','WILICI-2')" onmouseover="ee('over','WILICI-2')" onmouseout="ee('out','WILICI-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILICI-2#analytics'><span style='color:#10A010'>99 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILICI-2"><span class='name'>Jon Williamson</span> (2007). <span class='articleTitle recTitle'>Interpreting Causality in the Health Sciences.</span></a><span class='pubInfo'> <em class='pubName'>International Studies in the Philosophy of Science</em> 21 (2):157-170.</span></span><div class="extras"><div class="abstract">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 of causality<span id="WILICI-2-absexp"> (<span class="ll" onclick='$("WILICI-2-abstract2").show();$("WILICI-2-absexp").hide()'>...</span>)</span><span id="WILICI-2-abstract2" style="display:none"> that unifies its mechanistic and probabilistic aspects. We argue that the epistemic theory of causality provides the required unification. (<span class="ll" onclick='$("WILICI-2-abstract2").hide();$("WILICI-2-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILICI-2">No categories</div><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=WILICI-2&proxyId=&u=http%3A%2F%2Fwww.tandfonline.com%2Fdoi%2Fabs%2F10.1080%2F02698590701498084" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILICI-2'>8 more</a>)   <div id="la-WILICI-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILICI-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILICI-2" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILICI-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILICI-2"><i class="fa fa-share-alt"></i> 4 citations</a>   <span class="eMsg" id="msg-WILICI-2"></span></div></div></li> <li id='eLANJOB' onclick="ee('click','LANJOB')" onmouseover="ee('over','LANJOB')" onmouseout="ee('out','LANJOB')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/LANJOB#analytics'><span style='color:#10A010'>11 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/LANJOB"><span class='name'>Jürgen Landes</span> & <span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Justifying Objective Bayesianism on Predicate Languages.</span></a><span class='pubInfo'></span></span><div class="extras"><div class="abstract">Objective Bayesianism says that the strengths of one’s beliefs ought to be probabilities, calibrated to physical probabilities insofar as one has evidence of them, and otherwise sufficiently equivocal. These norms of belief are often explicated using the maximum entropy principle. In this paper we investigate the extent to which one can provide a unified justification of the objective Bayesian norms in the case in which the background language is a first-order predicate language, with a view to applying the resulting formalism<span id="LANJOB-absexp"> (<span class="ll" onclick='$("LANJOB-abstract2").show();$("LANJOB-absexp").hide()'>...</span>)</span><span id="LANJOB-abstract2" style="display:none"> to inductive logic. We show that the maximum entropy principle can be motivated largely in terms of minimising worst-case expected loss. (<span class="ll" onclick='$("LANJOB-abstract2").hide();$("LANJOB-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-LANJOB"><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><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=LANJOB&proxyId=&u=http%3A%2F%2Fdoi.org%2F10.3390%2Fe17042459%20" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/LANJOB'>3 more</a>)   <div id="la-LANJOB" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('LANJOB')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-LANJOB" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('LANJOB','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-LANJOB"></span></div></div></li> <li id='eCLAMMW' onclick="ee('click','CLAMMW')" onmouseover="ee('over','CLAMMW')" onmouseout="ee('out','CLAMMW')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/CLAMMW#analytics'><span style='color:#10A010'>21 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/CLAMMW"><span class='name'>Brendan Clarke</span>, <span class='name'>Bert Leuridan</span> & <span class='name'>Jon Williamson</span> (2013). <span class='articleTitle recTitle'>Modelling Mechanisms with Causal Cycles.</span></a><span class='pubInfo'> <em class='pubName'>Synthese</em> 191 (8):1-31.</span></span><div class="extras"><div class="abstract">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<span id="CLAMMW-absexp"> (<span class="ll" onclick='$("CLAMMW-abstract2").show();$("CLAMMW-absexp").hide()'>...</span>)</span><span id="CLAMMW-abstract2" style="display:none"> nature of mechanisms. Like the standard Bayesian net formalism, it models causal relationships using directed acyclic graphs. Given this appeal to acyclicity, causal cycles pose a prima facie problem for the RBN approach. This paper argues that the problem is a significant one given the ubiquity of causal cycles in mechanisms, but that the problem can be solved by combining two sorts of solution strategy in a judicious way. (<span class="ll" onclick='$("CLAMMW-abstract2").hide();$("CLAMMW-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-CLAMMW"><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 class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=CLAMMW&proxyId=&u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11229-013-0360-7" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/CLAMMW'>6 more</a>)   <div id="la-CLAMMW" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('CLAMMW')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-CLAMMW" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('CLAMMW','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/CLAMMW"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-CLAMMW"></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:#10A010'>43 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILMTO-2"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Mechanistic Theories of Causality.</span></a><span class='pubInfo'></span></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-laws-etc' rel='section'>Causation, Laws, etc</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="http://philpapers.org/go.pl?id=WILMTO-2&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2010%2FMechanisticCausality.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILMTO-2'>3 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="Save in your personal bibliography" class="ll" onclick="showLists('WILMTO-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILMTO-2"><i class="fa fa-share-alt"></i> 3 citations</a>   <span class="eMsg" id="msg-WILMTO-2"></span></div></div></li> <li id='eWILHUD' onclick="ee('click','WILHUD')" onmouseover="ee('over','WILHUD')" onmouseout="ee('out','WILHUD')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILHUD#analytics'><span style='color:#10A010'>23 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILHUD"><span class='name'>Jon Williamson</span> (2014). <span class='articleTitle recTitle'>How Uncertain Do We Need to Be?</span></a><span class='pubInfo'> <em class='pubName'>Erkenntnis</em> 79 (6):1249-1271.</span></span><div class="extras"><div class="abstract">Expert probability forecasts can be useful for decision making . But levels of uncertainty escalate: however the forecaster expresses the uncertainty that attaches to a forecast, there are good reasons for her to express a further level of uncertainty, in the shape of either imprecision or higher order uncertainty . Bayesian epistemology provides the means to halt this escalator, by tying expressions of uncertainty to the propositions expressible in an agent’s language . But Bayesian epistemology comes in three main varieties.<span id="WILHUD-absexp"> (<span class="ll" onclick='$("WILHUD-abstract2").show();$("WILHUD-absexp").hide()'>...</span>)</span><span id="WILHUD-abstract2" style="display:none"> Strictly subjective Bayesianism and empirically-based subjective Bayesianism have difficulty in justifying the use of a forecaster’s probabilities for decision making . On the other hand, objective Bayesianism can justify the use of these probabilities, at least when the probabilities are consistent with the agent’s evidence . Hence objective Bayesianism offers the most promise overall for explaining how testimony of uncertainty can be useful for decision making. Interestingly, the objective Bayesian analysis provided in Sect. 5 can also be used to justify a version of the Principle of Reflection. (<span class="ll" onclick='$("WILHUD-abstract2").hide();$("WILHUD-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILHUD"><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><a class='catName' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=WILHUD&proxyId=&u=http%3A%2F%2Flink.springer.com%2Fcontent%2Fpdf%2F10.1007%252Fs10670-013-9516-6.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILHUD'>7 more</a>)   <div id="la-WILHUD" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILHUD')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILHUD" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILHUD','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILHUD"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILHUD"></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:#10A010'>28 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILHCC-3"><span class='name'>Jon Williamson</span> (2013). <span class='articleTitle recTitle'>How Can Causal Explanations Explain?</span></a><span class='pubInfo'> <em class='pubName'>Erkenntnis</em> 78 (2):257-275.</span></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="http://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="Save in your personal bibliography" class="ll" onclick="showLists('WILHCC-3','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILHCC-3"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILHCC-3"></span></div></div></li> <li id='eCASMFP' onclick="ee('click','CASMFP')" onmouseover="ee('over','CASMFP')" onmouseout="ee('out','CASMFP')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/CASMFP#analytics'><span style='color:#10A010'>27 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/CASMFP"><span class='name'>Lorenzo Casini</span>, <span class='name'>Phyllis Mckay Illari</span>, <span class='name'>Federica Russo</span> & <span class='name'>Jon Williamson</span> (2011). <span class='articleTitle recTitle'>Models for Prediction, Explanation and Control.</span></a><span class='pubInfo'> <em class='pubName'>Theoria</em> 26 (1):5-33.</span></span><div class="extras"><div class="abstract">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<span id="CASMFP-absexp"> (<span class="ll" onclick='$("CASMFP-abstract2").show();$("CASMFP-absexp").hide()'>...</span>)</span><span id="CASMFP-abstract2" style="display:none"> how a simple two-level RBN can be used tomodel a mechanism in cancer science. The higher level of our model contains variables at the clinical level, while the lower level maps the structure of the cell’s mechanism for apoptosis. (<span class="ll" onclick='$("CASMFP-abstract2").hide();$("CASMFP-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-CASMFP"><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="http://philpapers.org/go.pl?id=CASMFP&proxyId=&u=http%3A%2F%2Fwww.pdcnet.org%2Fcollection%2Fshow%3Fid%3Dtheoria_2011_0026_0001_0005_0033%26file_type%3Dpdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/CASMFP'>6 more</a>)   <div id="la-CASMFP" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('CASMFP')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-CASMFP" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('CASMFP','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/CASMFP"><i class="fa fa-share-alt"></i> 2 citations</a>   <span class="eMsg" id="msg-CASMFP"></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:#10A010'>42 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILC-2"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Causality.</span></a><span class='pubInfo'></span></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">No categories</div><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=WILC-2&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2004%2Fcausality.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILC-2'>3 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="Save in your personal bibliography" class="ll" onclick="showLists('WILC-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILC-2"><i class="fa fa-share-alt"></i> 3 citations</a>   <span class="eMsg" id="msg-WILC-2"></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'><div style='float:right' class='subtle'> <a href='/rec/WILPOP-3#analytics'><span style='color:#10A010'>35 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILPOP-3"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Philosophies of Probability: Objective Bayesianism and its Challenges.</span></a><span class='pubInfo'></span></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"><a rel="nofollow" href="http://philpapers.org/go.pl?id=WILPOP-3&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2004%2Fphilprob.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a>   <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="Save in your personal bibliography" class="ll" onclick="showLists('WILPOP-3','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILPOP-3"><i class="fa fa-share-alt"></i> 3 citations</a>   <span class="eMsg" id="msg-WILPOP-3"></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:#10A010'>100 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILWFA"><span class='name'>Jon Williamson</span> (2013). <span class='articleTitle recTitle'>Why Frequentists and Bayesians Need Each Other.</span></a><span class='pubInfo'> <em class='pubName'>Erkenntnis</em> 78 (2):293-318.</span></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="http://philpapers.org/go.pl?id=WILWFA&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2011%2Fbridges.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILWFA'>8 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="Save in your personal bibliography" class="ll" onclick="showLists('WILWFA','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILWFA"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILWFA"></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:#10A010'>35 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILII"><span class='name'>Jon Williamson</span> (2007). <span class='articleTitle recTitle'>Inductive Influence.</span></a><span class='pubInfo'> <em class='pubName'>British Journal for the Philosophy of Science</em> 58 (4):689 - 708.</span></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();$("WILII-absexp").hide()'>...</span>)</span><span id="WILII-abstract2" style="display:none"> to capture the Johnson-Carnap continuum of inductive methods, as well as the Nix-Paris continuum, and show how inductive influence can be measured. (<span class="ll" onclick='$("WILII-abstract2").hide();$("WILII-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILII"><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/prior-probabilities' rel='section'>Prior Probabilities</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="http://philpapers.org/go.pl?id=WILII&proxyId=&u=http%3A%2F%2Fbjps.oxfordjournals.org%2Fcgi%2Fdoi%2F10.1093%2Fbjps%2Faxm032" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILII'>9 more</a>)   <div id="la-WILII" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILII')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILII" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILII','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILII"><i class="fa fa-share-alt"></i> 3 citations</a>   <span class="eMsg" id="msg-WILII"></span></div></div></li> <li id='eDARITA' onclick="ee('click','DARITA')" onmouseover="ee('over','DARITA')" onmouseout="ee('out','DARITA')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/DARITA#analytics'><span style='color:#10A010'>50 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/DARITA"><span class='name'>George Darby</span> & <span class='name'>Jon Williamson</span> (2011). <span class='articleTitle recTitle'>Imaging Technology and the Philosophy of Causality.</span></a><span class='pubInfo'> <em class='pubName'>Philosophy and Technology</em> 24 (2):115-136.</span></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="DARITA-absexp"> (<span class="ll" onclick='$("DARITA-abstract2").show();$("DARITA-absexp").hide()'>...</span>)</span><span id="DARITA-abstract2" style="display:none"> making, cannot account for the need for the other kind of evidence. Weber (Int Stud Philos Sci 23(2):277–295, 2009) has suggested to the contrary that Giere’s probabilistic analysis of causality survives this criticism. In this paper, we look in detail at the case of medical imaging technology, which, we argue, supports the thesis of Russo and Williamson, and we respond to Weber’s suggestion, arguing that Giere’s account does not survive the criticism. (<span class="ll" onclick='$("DARITA-abstract2").hide();$("DARITA-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-DARITA"><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="http://philpapers.org/go.pl?id=DARITA&proxyId=&u=http%3A%2F%2Fwww.springerlink.com%2Fcontent%2F376j74k283161p4r%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/DARITA'>5 more</a>)   <div id="la-DARITA" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('DARITA')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-DARITA" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('DARITA','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/DARITA"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-DARITA"></span></div></div></li> <li id='eWILBNA-2' onclick="ee('click','WILBNA-2')" onmouseover="ee('over','WILBNA-2')" onmouseout="ee('out','WILBNA-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILBNA-2#analytics'><span style='color:#10A010'>32 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILBNA-2"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Bayesian Nets and Causality.</span></a><span class='pubInfo'></span></span><div class="extras"><div class="abstract">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.. </div><div class="catsCon" id="ecats-con-WILBNA-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="http://philpapers.org/go.pl?id=WILBNA-2&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2005%2FBNAC.htm" target='_blank' ><i class="fa fa-download"></i> Direct download</a>   <div id="la-WILBNA-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILBNA-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILBNA-2" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILBNA-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILBNA-2"><i class="fa fa-share-alt"></i> 2 citations</a>   <span class="eMsg" id="msg-WILBNA-2"></span></div></div></li> <li id='eWILDJA-2' onclick="ee('click','WILDJA-2')" onmouseover="ee('over','WILDJA-2')" onmouseout="ee('out','WILDJA-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILDJA-2#analytics'><span style='color:#10A010'>10 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILDJA-2"><span class='name'>Jon Williamson</span> (2015). <span class='articleTitle recTitle'>Deliberation, Judgement and the Nature of Evidence.</span></a><span class='pubInfo'> <em class='pubName'>Economics and Philosophy</em> 31 (1):27-65.</span></span><div class="extras"><div class="abstract">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<span id="WILDJA-2-absexp"> (<span class="ll" onclick='$("WILDJA-2-abstract2").show();$("WILDJA-2-absexp").hide()'>...</span>)</span><span id="WILDJA-2-abstract2" style="display:none"> standard axioms for merging need to be altered somewhat. (<span class="ll" onclick='$("WILDJA-2-abstract2").hide();$("WILDJA-2-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILDJA-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="http://philpapers.org/go.pl?id=WILDJA-2&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F47312%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILDJA-2'>4 more</a>)   <div id="la-WILDJA-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILDJA-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILDJA-2" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILDJA-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILDJA-2"></span></div></div></li> <li id='eWILPL' onclick="ee('click','WILPL')" onmouseover="ee('over','WILPL')" onmouseout="ee('out','WILPL')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILPL#analytics'><span style='color:#10A010'>16 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILPL"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Probability Logic.</span></a><span class='pubInfo'></span></span><div class="extras"><div class="abstract">Practical reasoning requires decision—making in the face of uncertainty. Xenelda has just left to go to work when she hears a burglar alarm. She doesn’t know whether it is hers but remembers that she left a window slightly open. Should she be worried? Her house may not be being burgled, since the wind or a power cut may have set the burglar alarm off, and even if it isn’t her alarm sounding she might conceivably be being burgled. Thus Xenelda can<span id="WILPL-absexp"> (<span class="ll" onclick='$("WILPL-abstract2").show();$("WILPL-absexp").hide()'>...</span>)</span><span id="WILPL-abstract2" style="display:none"> not be certain that her house is being burgled, and the decision that she takes must be based on her degree of certainty, together with the possible outcomes of that decision. (<span class="ll" onclick='$("WILPL-abstract2").hide();$("WILPL-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILPL"><div><a class='catName' href='/browse/applications-of-probability' rel='section'>Applications of 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="http://philpapers.org/go.pl?id=WILPL&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2000%2Fprobability_logic.ps" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILPL'>2 more</a>)   <div id="la-WILPL" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILPL')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILPL" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILPL','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILPL"><i class="fa fa-share-alt"></i> 2 citations</a>   <span class="eMsg" id="msg-WILPL"></span></div></div></li> <li id='eWILOBW' onclick="ee('click','WILOBW')" onmouseover="ee('over','WILOBW')" onmouseout="ee('out','WILOBW')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILOBW#analytics'><span style='color:#10A010'>20 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILOBW"><span class='name'>Jon Williamson</span> (2008). <span class='articleTitle recTitle'>Objective Bayesianism with Predicate Languages.</span></a><span class='pubInfo'> <em class='pubName'>Synthese</em> 163 (3):341 - 356.</span></span><div class="extras"><div class="abstract">Objective Bayesian probability is often defined over rather simple domains, e.g., finite event spaces or propositional languages. This paper investigates the extension of objective Bayesianism to first-order logical languages. It is argued that the objective Bayesian should choose a probability function, from all those that satisfy constraints imposed by background knowledge, that is closest to a particular frequency-induced probability function which generalises the λ = 0 function of Carnap’s continuum of inductive methods. </div><div class="catsCon" id="ecats-con-WILOBW"><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="http://philpapers.org/go.pl?id=WILOBW&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2007%2Fobpl.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILOBW'>8 more</a>)   <div id="la-WILOBW" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILOBW')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILOBW" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILOBW','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILOBW"><i class="fa fa-share-alt"></i> 2 citations</a>   <span class="eMsg" id="msg-WILOBW"></span></div></div></li> <li id='eWILBRD' onclick="ee('click','WILBRD')" onmouseover="ee('over','WILBRD')" onmouseout="ee('out','WILBRD')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILBRD#analytics'><span style='color:#10A010'>12 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILBRD"><span class='name'>Jon Williamson</span> (2010). <span class='articleTitle recTitle'>B. De Finetti, <Em>Philosophical Lectures on Probability</Em>.</span> <span class='hint'>[REVIEW]</span></a><span class='pubInfo'> <em class='pubName'>Philosophia Mathematica</em> 18 (1):130-135.</span></span><div class="extras"><div class="abstract">(No abstract is available for this citation). </div><div class="catsCon" id="ecats-con-WILBRD"><div><a class='catName' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=WILBRD&proxyId=&u=http%3A%2F%2Fphilmat.oxfordjournals.org%2Fcontent%2Fearly%2F2009%2F11%2F05%2Fphilmat.nkp019%3Frelated-urls%3Dyes%26legid%3Dphilmat%3Bnkp019v1%26cited-by%3Dyes%26legid%3Dphilmat%3Bnkp019v1" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILBRD'>6 more</a>)   <div id="la-WILBRD" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILBRD')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILBRD" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILBRD','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILBRD"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILBRD"></span></div></div></li> <li id='eRUSCAP-2' onclick="ee('click','RUSCAP-2')" onmouseover="ee('over','RUSCAP-2')" onmouseout="ee('out','RUSCAP-2')" class='entry'><span class="citation"><a href="http://philpapers.org/rec/RUSCAP-2"><span class='name'>Federica Russo</span> & <span class='name'>Jon Williamson</span> (eds.) (2007). <span class='pub_name recTitle'><span class='articleTitle recTitle'>Causality and Probability in the Sciences.</span></span></a><span class='pubInfo'></span></span><div class="extras"><div class="catsCon" id="ecats-con-RUSCAP-2"><div><a class='catName' href='/browse/causation-laws-etc-miscellaneous' rel='section'>Causation, Laws, Etc, Miscellaneous</a><span class='catIn'> in </span><a class='catArea' href='/browse/metaphysics' rel='section'>Metaphysics</a></div> </div><div class="options"><div id="tr-RUSCAP-2" title="Translate" class="yui-skin-sam ldiv" style="cursor:pointer" onclick="translateEntry('RUSCAP-2')"><i class="fa fa-language"></i> Translate</div>   <div id="la-RUSCAP-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('RUSCAP-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-RUSCAP-2" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('RUSCAP-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/RUSCAP-2"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-RUSCAP-2"></span></div></div></li> <li id='eWILOBP' onclick="ee('click','WILOBP')" onmouseover="ee('over','WILOBP')" onmouseout="ee('out','WILOBP')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILOBP#analytics'><span style='color:#10A010'>31 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILOBP"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Objective Bayesian Probabilistic Logic.</span></a><span class='pubInfo'></span></span><div class="extras"><div class="abstract">This paper develops connections between objective Bayesian epistemology—which holds that the strengths of an agent’s beliefs should be representable by probabilities, should be calibrated with evidence of empirical probability, and should otherwise be equivocal—and probabilistic logic. After introducing objective Bayesian epistemology over propositional languages, the formalism is extended to handle predicate languages. A rather general probabilistic logic is formulated and then given a natural semantics in terms of objective Bayesian epistemology. The machinery of objective Bayesian nets and objective credal nets<span id="WILOBP-absexp"> (<span class="ll" onclick='$("WILOBP-abstract2").show();$("WILOBP-absexp").hide()'>...</span>)</span><span id="WILOBP-abstract2" style="display:none"> is introduced and this machinery is applied to provide a calculus for probabilistic logic that meshes with the objective Bayesian semantics. (<span class="ll" onclick='$("WILOBP-abstract2").hide();$("WILOBP-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILOBP"><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="http://philpapers.org/go.pl?id=WILOBP&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F20878%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILOBP'>3 more</a>)   <div id="la-WILOBP" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILOBP')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILOBP" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILOBP','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILOBP"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILOBP"></span></div></div></li> <li id='eWILIPI' onclick="ee('click','WILIPI')" onmouseover="ee('over','WILIPI')" onmouseout="ee('out','WILIPI')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILIPI#analytics'><span style='color:#10A010'>105 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILIPI"><span class='name'>Federica Russo</span> & <span class='name'>Jon Williamson</span> (2007). <span class='articleTitle recTitle'>Interpreting Probability in Causal Models for Cancer.</span></a><span class='pubInfo'> In Federica Russo & Jon Williamson (eds.), <em><a href="http://philpapers.org/rec/RUSCAP-2">Causality and Probability in the Sciences</a></em>. 217--242.</span></span><div class="extras"><div class="abstract">How should probabilities be interpreted in causal models in the social and health sciences? In this paper we take a step towards answering this question by investigating the case of cancer in epidemiology and arguing that the objective Bayesian interpretation is most appropriate in this domain. </div><div class="catsCon" id="ecats-con-WILIPI"><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="http://philpapers.org/go.pl?id=WILIPI&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2006%2Finterpreting.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILIPI'>4 more</a>)   <div id="la-WILIPI" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILIPI')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILIPI" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILIPI','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILIPI"></span></div></div></li> <li id='eWILFBE' onclick="ee('click','WILFBE')" onmouseover="ee('over','WILFBE')" onmouseout="ee('out','WILFBE')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILFBE#analytics'><span style='color:#10A010'>62 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILFBE"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>From Bayesian Epistemology to Inductive Logic.</span></a><span class='pubInfo'></span></span><div class="extras"><div class="abstract">Inductive logic admits a variety of semantics (Haenni et al., 2011, Part 1). This paper develops semantics based on the norms of Bayesian epistemology (Williamson, 2010, Chapter 7). §1 introduces the semantics and then, in §2, the paper explores methods for drawing inferences in the resulting logic and compares the methods of this paper with the methods of Barnett and Paris (2008). §3 then evaluates this Bayesian inductive logic in the light of four traditional critiques of inductive logic, arguing (i)<span id="WILFBE-absexp"> (<span class="ll" onclick='$("WILFBE-abstract2").show();$("WILFBE-absexp").hide()'>...</span>)</span><span id="WILFBE-abstract2" style="display:none"> that it is language independent in a key sense, (ii) that it admits connections with the Principle of Indifference but these connections do not lead to paradox, (iii) that it can capture the phenomenon of learning from experience, and (iv) that while the logic advocates scepticism with regard to some universal hypotheses, such scepticism is not problematic from the point of view of scientific theorising. (<span class="ll" onclick='$("WILFBE-abstract2").hide();$("WILFBE-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILFBE"><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/inductive-logic' rel='section'>Inductive Logic</a><span class='catIn'> in </span><a class='catArea' href='/browse/logic-and-philosophy-of-logic' rel='section'>Logic and Philosophy of Logic</a></div> <div><a class='catName' href='/browse/inductive-skepticism' rel='section'>Inductive Skepticism</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="http://philpapers.org/go.pl?id=WILFBE&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2011%2FBEIL.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILFBE'>3 more</a>)   <div id="la-WILFBE" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILFBE')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILFBE" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILFBE','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILFBE"></span></div></div></li> <li id='eWILCAA-3' onclick="ee('click','WILCAA-3')" onmouseover="ee('over','WILCAA-3')" onmouseout="ee('out','WILCAA-3')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILCAA-3#analytics'><span style='color:#10A010'>16 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILCAA-3"><span class='name'>Jon Williamson</span> (2006). <span class='articleTitle recTitle'>Combining Argumentation and Bayesian Nets for Breast Cancer Prognosis.</span></a><span class='pubInfo'> <em class='pubName'>Journal of Logic, Language and Information</em> 15 (1-2):155-178.</span></span><div class="extras"><div class="abstract">We present a new framework for combining logic with probability, and demonstrate the application of this framework to breast cancer prognosis. Background knowledge concerning breast cancer prognosis is represented using logical arguments. This background knowledge and a database are used to build a Bayesian net that captures the probabilistic relationships amongst the variables. Causal hypotheses gleaned from the Bayesian net in turn generate new arguments. The Bayesian net can be queried to help decide when one argument attacks another. The Bayesian<span id="WILCAA-3-absexp"> (<span class="ll" onclick='$("WILCAA-3-abstract2").show();$("WILCAA-3-absexp").hide()'>...</span>)</span><span id="WILCAA-3-abstract2" style="display:none"> net is used to perform the prognosis, while the argumentation framework is used to provide a qualitative explanation of the prognosis. (<span class="ll" onclick='$("WILCAA-3-abstract2").hide();$("WILCAA-3-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILCAA-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><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=WILCAA-3&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2005%2FPrognosis.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILCAA-3'>6 more</a>)   <div id="la-WILCAA-3" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILCAA-3')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILCAA-3" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILCAA-3','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILCAA-3"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILCAA-3"></span></div></div></li> <li id='eWILCAA' onclick="ee('click','WILCAA')" onmouseover="ee('over','WILCAA')" onmouseout="ee('out','WILCAA')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILCAA#analytics'><span style='color:#10A010'>8 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILCAA"><span class='name'>Matt Williams</span> & <span class='name'>Jon Williamson</span> (2006). <span class='articleTitle recTitle'>Combining Argumentation and Bayesian Nets for Breast Cancer Prognosis.</span></a><span class='pubInfo'> <em class='pubName'>Journal of Logic, Language and Information</em> 15 (1-2):155-178.</span></span><div class="extras"><div class="abstract">We present a new framework for combining logic with probability, and demonstrate the application of this framework to breast cancer prognosis. Background knowledge concerning breast cancer prognosis is represented using logical arguments. This background knowledge and a database are used to build a Bayesian net that captures the probabilistic relationships amongst the variables. Causal hypotheses gleaned from the Bayesian net in turn generate new arguments. The Bayesian net can be queried to help decide when one argument attacks another. The Bayesian<span id="WILCAA-absexp"> (<span class="ll" onclick='$("WILCAA-abstract2").show();$("WILCAA-absexp").hide()'>...</span>)</span><span id="WILCAA-abstract2" style="display:none"> net is used to perform the prognosis, while the argumentation framework is used to provide a qualitative explanation of the prognosis. (<span class="ll" onclick='$("WILCAA-abstract2").hide();$("WILCAA-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILCAA"><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="http://philpapers.org/go.pl?id=WILCAA&proxyId=&u=http%3A%2F%2Fwww.springerlink.com%2Fcontent%2Fw082614002715016%2Ffulltext.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILCAA'>4 more</a>)   <div id="la-WILCAA" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILCAA')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILCAA" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILCAA','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <a href="/citations/WILCAA"><i class="fa fa-share-alt"></i> 1 citation</a>   <span class="eMsg" id="msg-WILCAA"></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:#10A010'>24 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/LANOBA"><span class='name'>Jürgen Landes</span> & <span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Objective Bayesianism and the Maximum Entropy Principle.</span></a><span class='pubInfo'></span></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/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="http://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'>4 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="Save in your personal bibliography" class="ll" onclick="showLists('LANOBA','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-LANOBA"></span></div></div></li> <li id='eCORFOB' onclick="ee('click','CORFOB')" onmouseover="ee('over','CORFOB')" onmouseout="ee('out','CORFOB')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/CORFOB#analytics'><span style='color:#10A010'>21 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/CORFOB"><span class='name'>David Corfield</span> & <span class='name'>Jon Williamson</span> (eds.) (2001). <span class='pub_name recTitle'><span class='articleTitle recTitle'>Foundations of Bayesianism.</span></span></a><span class='pubInfo'> Kluwer Academic Publishers.</span></span><div class="extras"><div class="abstract">The volume includes important criticisms of Bayesian reasoning and also gives an insight into some of the points of disagreement amongst advocates of the ... </div><div class="catsCon" id="ecats-con-CORFOB"><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><div class="options"><div class='affiliateLinks'><span class='price_used 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href='/browse/scientific-discovery' rel='section'>Scientific Discovery</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="http://philpapers.org/go.pl?id=WILARA-2&proxyId=&u=http%3A%2F%2Fbjps.oxfordjournals.org%2Fcgi%2Freprint%2F54%2F2%2F353" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILARA-2'>5 more</a>)   <div id="la-WILARA-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILARA-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILARA-2" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILARA-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILARA-2"></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:#10A010'>67 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WHEEPA"><span class='name'>Gregory Wheeler</span> & <span class='name'>Jon Williamson</span> (2011). <span class='articleTitle recTitle'>Evidential Probability and Objective Bayesian Epistemology.</span></a><span class='pubInfo'> In Prasanta S. Bandyopadhyay & Malcolm Forster (eds.), <em><a href="http://philpapers.org/rec/BANHOT">Handbook of the Philosophy of Statistics</a></em>. Elsevier</span></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="http://philpapers.org/go.pl?id=WHEEPA&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2008%2FEP-OBE.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WHEEPA'>3 more</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="Save in your personal bibliography" class="ll" onclick="showLists('WHEEPA','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WHEEPA"></span></div></div></li> <li id='eWILWLA-2' onclick="ee('click','WILWLA-2')" onmouseover="ee('over','WILWLA-2')" onmouseout="ee('out','WILWLA-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILWLA-2#analytics'><span style='color:#10A010'>45 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILWLA-2"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Why Look at Causality in the Sciences? A Manifesto.</span></a><span class='pubInfo'></span></span><div class="extras"><div class="abstract">This introduction to the volume begins with a manifesto that puts forward two theses: first, that the sciences are the best place to turn in order to understand causality; second, that scientifically-informed philosophical investigation can bring something to the sciences too. Next, the chapter goes through the various parts of the volume, drawing out relevant background and themes of the chapters in those parts. Finally, the chapter discusses the progeny of the papers and identifies some next steps for research into<span id="WILWLA-2-absexp"> (<span class="ll" onclick='$("WILWLA-2-abstract2").show();$("WILWLA-2-absexp").hide()'>...</span>)</span><span id="WILWLA-2-abstract2" style="display:none"> causality in the sciences. (<span class="ll" onclick='$("WILWLA-2-abstract2").hide();$("WILWLA-2-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILWLA-2">No categories</div><div class="options"><div id="tr-WILWLA-2" title="Translate" class="yui-skin-sam ldiv" style="cursor:pointer" onclick="translateEntry('WILWLA-2')"><i class="fa fa-language"></i> Translate</div>   <a rel="nofollow" href="http://philpapers.org/go.pl?id=WILWLA-2&proxyId=&u=http%3A%2F%2Ffds.oup.com%2Fwww.oup.com%2Fpdf%2F13%2F9780199574131_chapter1.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a>   <div id="la-WILWLA-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILWLA-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILWLA-2" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILWLA-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILWLA-2"></span></div></div></li> <li id='eWILIUA' onclick="ee('click','WILIUA')" onmouseover="ee('over','WILIUA')" onmouseout="ee('out','WILIUA')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILIUA#analytics'><span style='color:#10A010'>59 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILIUA"><span class='name'>Jon Williamson</span>, <span class='articleTitle recTitle'>Intervention, Underdetermination, and Theory Generation.</span></a><span class='pubInfo'></span></span><div class="extras"><div class="abstract">We consider the use of intervention data for eliminating the underdetermination in statistical modelling, and for guiding extensions of the statistical models. The leading example is factor analysis, a major statistical tool in the social sciences. We first relate indeterminacy in factor analysis to the problem of underdetermination. Then we draw a parallel between factor analysis models and Bayesian networks with hidden nodes, which allows us to clarify the use of intervention data for dealing with indeterminacy. It will be shown<span id="WILIUA-absexp"> (<span class="ll" onclick='$("WILIUA-abstract2").show();$("WILIUA-absexp").hide()'>...</span>)</span><span id="WILIUA-abstract2" style="display:none"> that in some cases, the indeterminacy can be resolved by an intervention. In the other cases, the intervention data suggest specific extensions of the model. The upshot is that intervention data can replace theoretical criteria that are typically employed in resolving underdetermination and theory change. (<span class="ll" onclick='$("WILIUA-abstract2").hide();$("WILIUA-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILIUA"><div><a class='catName' href='/browse/underdetermination-of-theory-by-data' rel='section'>Underdetermination of Theory by Data</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="http://philpapers.org/go.pl?id=WILIUA&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2008%2Ffaraday.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a>   <div id="la-WILIUA" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILIUA')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILIUA" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILIUA','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILIUA"></span></div></div></li> <li id='eWILRCI-2' onclick="ee('click','WILRCI-2')" onmouseover="ee('over','WILRCI-2')" onmouseout="ee('out','WILRCI-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILRCI-2#analytics'><span style='color:#10A010'>11 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILRCI-2"><span class='name'>Jon Williamson</span> & <span class='name'>D. M. Gabbay</span>, <span class='articleTitle recTitle'>Recursive Causality in Bayesian Networks and Self-Fibring Networks.</span></a><span class='pubInfo'></span></span><div class="extras"><div class="catsCon" id="ecats-con-WILRCI-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="http://philpapers.org/go.pl?id=WILRCI-2&proxyId=&u=http%3A%2F%2Fkar.kent.ac.uk%2F7362%2F" target='_blank' ><i class="fa fa-download"></i> Direct download</a>   <div id="la-WILRCI-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILRCI-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILRCI-2" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILRCI-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILRCI-2"></span></div></div></li> <li id='eWILMFP-2' onclick="ee('click','WILMFP-2')" onmouseover="ee('over','WILMFP-2')" onmouseout="ee('out','WILMFP-2')" class='entry'><div style='float:right' class='subtle'> <a href='/rec/WILMFP-2#analytics'><span style='color:#10A010'>40 <i class="fa fa-download"></i></span></a></div><span class="citation"><a href="http://philpapers.org/rec/WILMFP-2"><span class='name'>Jon Williamson</span> (2011). <span class='articleTitle recTitle'>Models for Prediction, Explanation and Control: Recursive Bayesian Networks.</span></a><span class='pubInfo'> <em class='pubName'>Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia</em> 26 (70):5-33.</span></span><div class="extras"><div class="abstract">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<span id="WILMFP-2-absexp"> (<span class="ll" onclick='$("WILMFP-2-abstract2").show();$("WILMFP-2-absexp").hide()'>...</span>)</span><span id="WILMFP-2-abstract2" style="display:none"> how a simple two-level RBN can be used to model a mechanism in cancer science. The higher level of our model contains variables at the clinical level, while the lower level maps the structure of the cell's mechanism for apoptosis. (<span class="ll" onclick='$("WILMFP-2-abstract2").hide();$("WILMFP-2-absexp").show();'>shrink</span>)</span></div><div class="catsCon" id="ecats-con-WILMFP-2"><div><a class='catName' href='/browse/bayesian-reasoning-misc' rel='section'>Bayesian Reasoning, Misc</a><span class='catIn'> in </span><a class='catArea' href='/browse/philosophy-of-probability' rel='section'>Philosophy of Probability</a></div> </div><div class="options"><a rel="nofollow" href="http://philpapers.org/go.pl?id=WILMFP-2&proxyId=&u=http%3A%2F%2Fwww.kent.ac.uk%2Fsecl%2Fphilosophy%2Fjw%2F2010%2Frbns.pdf" target='_blank' ><i class="fa fa-download"></i> Direct download</a> (<a href='/rec/WILMFP-2'>8 more</a>)   <div id="la-WILMFP-2" title="Export to another format" class="yui-skin-sam ldiv"> </div><span class="ll" onclick="showExports('WILMFP-2')"><i class="fa fa-external-link"></i> Export citation<img src="/philpapers/raw/subind.gif"></span>   <div id="ml-WILMFP-2" class="yui-skin-sam ldiv"> </div><span title="Save in your personal bibliography" class="ll" onclick="showLists('WILMFP-2','')"><i class="fa fa-floppy-o"></i> My bibliography<img src="/philpapers/raw/subind.gif"></span>  <span class="eMsg" id="msg-WILMFP-2"></span></div></div></li> </ol> </div> <div id='prevNextHtml' class='centered'><center><table><td><span class='prevNext'><img border='0' src='/philpapers/raw/icons/back-g.png'></td><td>1 — 50 / 101</td><td><span class='prevNext'><span title='Next page' class='clickable' onclick='goToNextPage()'><img border='0' src='/philpapers/raw/icons/forward.png'></span></span></td></table></center></div> </td> <td class="side_td"> <form name="expform"> <div class="sideBox"> <div class="sideBoxH">BibTeX / EndNote / RIS / etc</div> <div class="sideBoxC"> Export this page: <div style='margin-top:5px'> <select name="expf" id="expf" onChange="$('expLimit').show()"> <option value=''>Choose a format..</option> <option value='htm'>Formatted text</option><option value='txt'>Plain text</option><option value='bib'>BibTeX</option><option value='zot'>Zotero</option><option value='enw'>EndNote</option><option value='ris'>Reference Manager</option></select> <div id='expLimit' style="display:none"> Limit to <input type="text" id="expLimitI" size="3" value="500"> items. <input type="button" value="Export" onclick=" if ($F('expf')) { $('ap-format').value=$F('expf'); $('ap-limit').value=$F('expLimitI'); refreshWith($('allparams')); } else { alert('You must first choose a format.') } "> </div> </div> </div> </div> </form> <form id="moreOptions" name="more"> <div class="sideBox"> <div class="sideBoxH">Restrictions</div> <div class="sideBoxC"> <input class='checkbox' type='checkbox' name='proOnly' id='proOnly' onClick="createCookie('proOnly',this.checked ? 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