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  1. added 2019-01-09
    Probabilistic Causation and the Explanatory Role of Natural Selection.Pablo Razeto-Barry & Ramiro Frick - 2011 - Studies in History and Philosophy of Science Part C 42 (3):344-355.
    The explanatory role of natural selection is one of the long-term debates in evolutionary biology. Nevertheless, the consensus has been slippery because conceptual confusions and the absence of a unified, formal causal model that integrates different explanatory scopes of natural selection. In this study we attempt to examine two questions: (i) What can the theory of natural selection explain? and (ii) Is there a causal or explanatory model that integrates all natural selection explananda? For the first question, we argue that (...)
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  2. added 2018-10-24
    Reducing the Dauer Larva: Molecular Models of Biological Phenomena in Caenorhabditis Elegans Research.Arciszewski Michal - manuscript
    One important aspect of biological explanation is detailed causal modeling of particular phenomena in limited experimental background conditions. Recognising this allows a new avenue for intertheoretic reduction to be seen. Reductions in biology are possible, when one fully recognises that a sufficient condition for a reduction in biology is a molecular model of 1) only the demonstrated causal parameters of a biological model and 2) only within a replicable experimental background. These intertheoretic identifications –which are ubiquitous in biology and form (...)
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  3. added 2018-10-24
    Spoils to the Vector - How to Model Causes If You Are a Realist About Powers.Stephen Mumford & Rani Lill Anjum - 2011 - The Monist 94 (1):54-80.
    A standard way of representing causation is with neuron diagrams. This has become popular since the influential work of David Lewis. But it should not be assumed that such representations are metaphysically neutral and amenable to any theory of causation. On the contrary, this way of representing causation already makes several Humean assumptions about what causation is, and which suit Lewis’s programme of Humean Supervenience. An alternative of a vector diagram is better suited for a powers ontology. Causation should be (...)
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  4. added 2018-10-24
    Children with Reading Disability Show Brain Differences in Effective Connectivity for Visual, but Not Auditory Word Comprehension.Li Liu, Vira Amit, Emma Friedman & James Booth - 2010 - PLoS ONE 10.
    Background -/- Previous literature suggests that those with reading disability (RD) have more pronounced deficits during semantic processing in reading as compared to listening comprehension. This discrepancy has been supported by recent neuroimaging studies showing abnormal activity in RD during semantic processing in the visual but not in the auditory modality. Whether effective connectivity between brain regions in RD could also show this pattern of discrepancy has not been investigated. Methodology/Principal Findings -/- Children (8- to 14-year-olds) were given a semantic (...)
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  5. added 2018-10-24
    Drivers of Organizational Creativity.Mats Sundgren, Elof Dimenäs, Jan-Eric Gustafsson & Marcus Selart - 2005 - RandD Management 35:359-374.
    A path model of organizational creativity was presented; it conceptualized the influences of information sharing, learning culture, motivation, and networking on creative climate. A structural equation model was fitted to data from the pharmaceutical industry to test the proposed model. The model accounted for 86% of the variance in the creative climate dependent variable. Information sharing had a positive effect on learning culture, which in turn had a positive effect on creative climate, while there were negative direct effects of information (...)
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  6. added 2018-08-30
    Horizontal Surgicality and Mechanistic Constitution.Michael Baumgartner, Lorenzo Casini & Beate Krickel - 2018 - Erkenntnis:1-14.
    While ideal interventions are acknowledged by many as valuable tools for the analysis of causation, recent discussions have shown that, since there are no ideal interventions on upper-level phenomena that non-reductively supervene on their underlying mechanisms, interventions cannot—contrary to a popular opinion—ground an informative analysis of constitution. This has led some to abandon the project of analyzing constitution in interventionist terms. By contrast, this paper defines the notion of a horizontally surgical intervention, and argues that, when combined with some innocuous (...)
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  7. added 2018-08-30
    Philosophy of Social Science: A Contemporary Introduction.Mark Risjord - 2014 - Routledge.
    The Philosophy of Social Science: A Contemporary Introduction examines the perennial questions of philosophy by engaging with the empirical study of society. The book offers a comprehensive overview of debates in the field, with special attention to questions arising from new research programs in the social sciences. The text uses detailed examples of social scientific research to motivate and illustrate the philosophical discussion. Topics include the relationship of social policy to social science, interpretive research, action explanation, game theory, social scientific (...)
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  8. added 2018-07-19
    A Unified Account of General Learning Mechanisms and Theory‐of‐Mind Development.Theodore Bach - 2014 - Mind and Language 29 (3):351-381.
    Modularity theorists have challenged that there are, or could be, general learning mechanisms that explain theory-of-mind development. In response, supporters of the ‘scientific theory-theory’ account of theory-of-mind development have appealed to children's use of auxiliary hypotheses and probabilistic causal modeling. This article argues that these general learning mechanisms are not sufficient to meet the modularist's challenge. The article then explores an alternative domain-general learning mechanism by proposing that children grasp the concept belief through the progressive alignment of relational structure that (...)
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  9. added 2018-06-18
    Causation, Production, and Dependence, or A Model-Invariant Theory of Causation.J. Dmitri Gallow - manuscript
    I provide a theory of causation formulated within the causal modeling framework. This theory is model-invariant in the following sense: if the theory says that C caused (didn't cause) E in a causal model, M, then it will continue to say that C caused (didn't cause) E once we've removed an inessential variable from M. On this theory, we can understand causation as a model-invariant generalization of a relation of causal production. Begin by saying that C produces E iff they (...)
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  10. added 2018-06-10
    A Field Guide to Mechanisms: Part II.Holly Andersen - 2014 - Philosophy Compass 9 (4):284-293.
    In this field guide, I distinguish five separate senses with which the term ‘mechanism’ is used in contemporary philosophy of science. Many of these senses have overlapping areas of application but involve distinct philosophical claims and characterize the target mechanisms in relevantly different ways. This field guide will clarify the key features of each sense and introduce some main debates, distinguishing those that transpire within a given sense from those that are best understood as concerning two distinct senses. The ‘new (...)
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  11. added 2018-06-10
    Of Miracles and Interventions.Luke Glynn - 2013 - Erkenntnis 78 (1):43-64.
    In Making Things Happen, James Woodward influentially combines a causal modeling analysis of actual causation with an interventionist semantics for the counterfactuals encoded in causal models. This leads to circularities, since interventions are defined in terms of both actual causation and interventionist counterfactuals. Circularity can be avoided by instead combining a causal modeling analysis with a semantics along the lines of that given by David Lewis, on which counterfactuals are to be evaluated with respect to worlds in which their antecedents (...)
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  12. added 2018-06-07
    Addendum to "A Formal Framework for Representing Mechanisms?".Alexander Gebharter - manuscript
    In (Gebharter 2014) I suggested a framework for modeling the hierarchical organization of mechanisms. In this short addendum I want to highlight some connections of my approach to the statistics and machine learning literature and some of its limitations not mentioned in the paper.
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  13. added 2018-06-07
    Faithfulness, Coordination and Causal Coincidences.Naftali Weinberger - 2018 - Erkenntnis 83 (2):113-133.
    Within the causal modeling literature, debates about the Causal Faithfulness Condition have concerned whether it is probable that the parameters in causal models will have values such that distinct causal paths will cancel. As the parameters in a model are fixed by the probability distribution over its variables, it is initially puzzling what it means to assign probabilities to these parameters. I propose that to assign a probability to a parameter in a model is to treat that parameter as a (...)
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  14. added 2018-06-07
    Patterns, Information, and Causation.Holly Andersen - 2017 - Journal of Philosophy 114 (11):592-622.
    This paper articulates an account of causation as a collection of information-theoretic relationships between patterns instantiated in the causal nexus. I draw on Dennett’s account of real patterns to characterize potential causal relata as patterns with specific identification criteria and noise tolerance levels, and actual causal relata as those patterns instantiated at some spatiotemporal location in the rich causal nexus as originally developed by Salmon. I develop a representation framework using phase space to precisely characterize causal relata, including their degree (...)
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  15. added 2018-06-07
    A Proposed Probabilistic Extension of the Halpern and Pearl Definition of ‘Actual Cause’.Luke Fenton-Glynn - unknown
    In their article 'Causes and Explanations: A Structural-Model Approach. Part I: Causes', Joseph Halpern and Judea Pearl draw upon structural equation models to develop an attractive analysis of 'actual cause'. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation.
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  16. added 2018-05-29
    On the Limits of Causal Modeling: Spatially-Structurally Complex Biological Phenomena.Marie I. Kaiser - 2016 - Philosophy of Science 83 (5):921-933.
    This paper examines the adequacy of causal graph theory as a tool for modeling biological phenomena and formalizing biological explanations. I point out that the causal graph approach reaches it limits when it comes to modeling biological phenomena that involve complex spatial and structural relations. Using a case study from molecular biology, DNA-binding and -recognition of proteins, I argue that causal graph models fail to adequately represent and explain causal phenomena in this field. The inadequacy of these models is due (...)
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  17. added 2018-05-29
    Where Grounding and Causation Part Ways: Comments on Schaffer.Kathrin Koslicki - 2016 - Philosophical Studies 173 (1):101-112.
    Does the notion of ground, as it has recently been employed by metaphysicians, point to a single unified phenomenon? Jonathan Schaffer holds that the phenomenon of grounding exhibits the unity characteristic of a single genus. In defense of this hypothesis, Schaffer proposes to take seriously the analogy between causation and grounding. More specifically, Schaffer argues that both grounding and causation are best approached through a single formalism, viz., that utilized by structural equation models of causation. In this paper, I present (...)
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  18. added 2018-02-12
    Causal Graphs and Biological Mechanisms.Alexander Gebharter & Marie I. Kaiser - 2014 - In Marie I. Kaiser, Oliver Scholz, Daniel Plenge & Andreas Hüttemann (eds.), Explanation in the special sciences: The case of biology and history. Dordrecht: Springer. pp. 55-86.
    Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological research practice (...)
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  19. added 2017-09-06
    Path-Specific Effects.Naftali Weinberger - forthcoming - British Journal for the Philosophy of Science.
    A cause may influence its effect via multiple paths. Paradigmatically (Hesslow [1974]), taking birth control pills both decreases one’s risk of thrombosis by preventing pregnancy and increases it by producing a blood chemical. Building on Pearl ([2001]), I explicate the notion of a path-specific effect. Roughly, a path-specific effect of C on E via path P is the degree to which a change in C would change E were they to be transmitted only via P. Facts about such effects may (...)
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  20. added 2017-07-26
    Explanation, Confirmation, and Hempel's Paradox.William Roche - 2017 - In Kevin McCain & Ted Poston (eds.), Best explanations: New essays on inference to the best explanation. Oxford: Oxford University Press. pp. 219-241.
    Hempel’s Converse Consequence Condition (CCC), Entailment Condition (EC), and Special Consequence Condition (SCC) have some prima facie plausibility when taken individually. Hempel, though, shows that they have no plausibility when taken together, for together they entail that E confirms H for any propositions E and H. This is “Hempel’s paradox”. It turns out that Hempel’s argument would fail if one or more of CCC, EC, and SCC were modified in terms of explanation. This opens up the possibility that Hempel’s paradox (...)
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  21. added 2017-01-25
    Normality and Actual Causal Strength.Thomas F. Icard, Jonathan F. Kominsky & Joshua Knobe - 2017 - Cognition 161:80-93.
    Existing research suggests that people's judgments of actual causation can be influenced by the degree to which they regard certain events as normal. We develop an explanation for this phenomenon that draws on standard tools from the literature on graphical causal models and, in particular, on the idea of probabilistic sampling. Using these tools, we propose a new measure of actual causal strength. This measure accurately captures three effects of normality on causal judgment that have been observed in existing studies. (...)
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  22. added 2016-12-08
    Coherence and Confirmation Through Causation.Gregory Wheeler & Richard Scheines - 2013 - Mind 122 (485):135-170.
    Coherentism maintains that coherent beliefs are more likely to be true than incoherent beliefs, and that coherent evidence provides more confirmation of a hypothesis when the evidence is made coherent by the explanation provided by that hypothesis. Although probabilistic models of credence ought to be well-suited to justifying such claims, negative results from Bayesian epistemology have suggested otherwise. In this essay we argue that the connection between coherence and confirmation should be understood as a relation mediated by the causal relationships (...)
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  23. added 2016-08-20
    Aggregating Causal Judgments.Richard Bradley, Franz Dietrich & Christian List - 2014 - Philosophy of Science 81 (4):491-515.
    Decision-making typically requires judgments about causal relations: we need to know the causal effects of our actions and the causal relevance of various environmental factors. We investigate how several individuals' causal judgments can be aggregated into collective causal judgments. First, we consider the aggregation of causal judgments via the aggregation of probabilistic judgments, and identify the limitations of this approach. We then explore the possibility of aggregating causal judgments independently of probabilistic ones. Formally, we introduce the problem of causal-network aggregation. (...)
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  24. added 2016-08-17
    Folk Intuitions of Actual Causation: A Two-Pronged Debunking Explanation.David Rose - 2017 - Philosophical Studies 174 (5):1323-1361.
    How do we determine whether some candidate causal factor is an actual cause of some particular outcome? Many philosophers have wanted a view of actual causation which fits with folk intuitions of actual causation and those who wish to depart from folk intuitions of actual causation are often charged with the task of providing a plausible account of just how and where the folk have gone wrong. In this paper, I provide a range of empirical evidence aimed at showing just (...)
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  25. added 2016-04-01
    Structural Equations and Beyond.Franz Huber - 2013 - Review of Symbolic Logic 6 (4):709-732.
    Recent accounts of actual causation are stated in terms of extended causal models. These extended causal models contain two elements representing two seemingly distinct modalities. The first element are structural equations which represent the or mechanisms of the model, just as ordinary causal models do. The second element are ranking functions which represent normality or typicality. The aim of this paper is to show that these two modalities can be unified. I do so by formulating two constraints under which extended (...)
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  26. added 2016-02-29
    Systems Without a Graphical Causal Representation.Daniel M. Hausman, Reuben Stern & Naftali Weinberger - 2014 - Synthese 191 (8):1925-1930.
    There are simple mechanical systems that elude causal representation. We describe one that cannot be represented in a single directed acyclic graph. Our case suggests limitations on the use of causal graphs for causal inference and makes salient the point that causal relations among variables depend upon details of causal setups, including values of variables.
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  27. added 2015-09-11
    Philosophical Controversies in the Evaluation of Medical Treatments : With a Focus on the Evidential Roles of Randomization and Mechanisms in Evidence-Based Medicine.Alexander Mebius - 2015 - Dissertation, KTH Royal Institute of Technology
    This thesis examines philosophical controversies surrounding the evaluation of medical treatments, with a focus on the evidential roles of randomised trials and mechanisms in Evidence-Based Medicine. Current 'best practice' usually involves excluding non-randomised trial evidence from systematic reviews in cases where randomised trials are available for inclusion in the reviews. The first paper challenges this practice and evaluates whether adding of evidence from non-randomised trials might improve the quality and precision of some systematic reviews. The second paper compares the alleged (...)
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  28. added 2015-01-08
    Experimental Philosophy and Causal Attribution.Jonathan Livengood & David Rose - 2016 - In Justin Sytsma & Wesley Buckwalter (eds.), A Companion to Experimental Philosophy. Blackwell.
    Humans often attribute the things that happen to one or another actual cause. In this chapter, we survey some recent philosophical and psychological research on causal attribution. We pay special attention to the relation between graphical causal modeling and theories of causal attribution. We think that the study of causal attribution is one place where formal and experimental techniques nicely complement one another.
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  29. added 2014-09-07
    How to Analyse Retrodictive Probabilities in Inference to the Best Explanation.Andrew Holster - manuscript
    IBE ('Inference to the best explanation' or abduction) is a popular and highly plausible theory of how we should judge the evidence for claims of past events based on present evidence. It has been notably developed and supported recently by Meyer following Lipton. I believe this theory is essentially correct. This paper supports IBE from a probability perspective, and argues that the retrodictive probabilities involved in such inferences should be analysed in terms of predictive probabilities and a priori probability ratios (...)
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  30. added 2014-04-10
    Evidence-Based Policy: A Practical Guide to Doing It Better, Nancy Cartwright and Jeremy Hardie. Oxford University Press, 2013, Ix + 196 Pages. [REVIEW]Naftali Weinberger - 2014 - Economics and Philosophy 30 (1):113-120.
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  31. added 2014-04-02
    Should Causal Models Always Be Markovian? The Case of Multi-Causal Forks in Medicine.Donald Gillies & Aidan Sudbury - 2013 - European Journal for Philosophy of Science 3 (3):275-308.
    The development of causal modelling since the 1950s has been accompanied by a number of controversies, the most striking of which concerns the Markov condition. Reichenbach's conjunctive forks did satisfy the Markov condition, while Salmon's interactive forks did not. Subsequently some experts in the field have argued that adequate causal models should always satisfy the Markov condition, while others have claimed that non-Markovian causal models are needed in some cases. This paper argues for the second position by considering the multi-causal (...)
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  32. added 2014-03-06
    The Metaphysics of Causal Models: Where's the Biff?Toby Handfield, Charles R. Twardy, Kevin B. Korb & Graham Oppy - 2008 - Erkenntnis 68 (2):149-68.
    This paper presents an attempt to integrate theories of causal processes—of the kind developed by Wesley Salmon and Phil Dowe—into a theory of causal models using Bayesian networks. We suggest that arcs in causal models must correspond to possible causal processes. Moreover, we suggest that when processes are rendered physically impossible by what occurs on distinct paths, the original model must be restricted by removing the relevant arc. These two techniques suffice to explain cases of late preëmption and other cases (...)
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  33. added 2014-03-04
    The Problem of Piecemeal Induction.Conor Mayo-Wilson - 2011 - Philosophy of Science 78 (5):864-874.
    It is common to assume that the problem of induction arises only because of small sample sizes or unreliable data. In this paper, I argue that the piecemeal collection of data can also lead to underdetermination of theories by evidence, even if arbitrarily large amounts of completely reliable experimental and observational data are collected. Specifically, I focus on the construction of causal theories from the results of many studies (perhaps hundreds), including randomized controlled trials and observational studies, where the studies (...)
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  34. added 2013-05-10
    Introduction to Special Issue on 'Actual Causation'.Michael Baumgartner & Luke Glynn - 2013 - Erkenntnis 78 (1):1-8.
    An actual cause of some token effect is itself a token event that helped to bring about that effect. The notion of an actual cause is different from that of a potential cause – for example a pre-empted backup – which had the capacity to bring about the effect, but which wasn't in fact operative on the occasion in question. Sometimes actual causes are also distinguished from mere background conditions: as when we judge that the struck match was a cause (...)
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  35. added 2013-05-10
    A Probabilistic Analysis of Causation.Luke Glynn - 2011 - British Journal for the Philosophy of Science 62 (2):343-392.
    The starting point in the development of probabilistic analyses of token causation has usually been the naïve intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that (...)
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  36. added 2012-08-15
    A Reply to Rose, Livengood, Sytsma, and Machery.Chandra Sripada, Richard Gonzalez, Daniel Kessler, Eric Laber, Sara Konrath & Vijay Nair - manuscript
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  37. added 2012-04-06
    Can External Claims of Randomised Evaluations Used in Developmental Economics Be Considered Knowledge, in Light of the Problem of Induction?Palaniyapan Muthhukumar - manuscript
    The usage of Randomised Evaluations(REs) in social inquiry has been recent and responses to them have been wide ranging.RE seek to make predictions on the impact of an intervention, when it is attempted in a new situation. REs work by first determining the impact of the intervention. Subsequently, for the new situation it is expected that the impact would be similar. -/- The problem of induction poses one of the most serious challenges to the epistemological status of RE claims as (...)
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