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  1. Degree of Explanation.Robert Northcott - 2012 - Synthese 190 (15):3087-3105.
    Partial explanations are everywhere. That is, explanations citing causes that explain some but not all of an effect are ubiquitous across science, and these in turn rely on the notion of degree of explanation. I argue that current accounts are seriously deficient. In particular, they do not incorporate adequately the way in which a cause’s explanatory importance varies with choice of explanandum. Using influential recent contrastive theories, I develop quantitative definitions that remedy this lacuna, and relate it to existing measures (...)
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  • Conceived This Way: Innateness Defended.Northcott Robert - forthcoming - Philosophers Imprint.
    We propose a novel account of the distinction between innate and acquired biological traits: biological traits are innate to the degree that they are caused by factors intrinsic to the organism at the time of its origin; they are acquired to the degree that they are caused by factors extrinsic to the organism. This account borrows from recent work on causation in order to make rigorous the notion of quantitative contributions to traits by different factors in development. We avoid the (...)
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  • Genetic Traits and Causal Explanation.Robert Northcott - 2012 - In Kathryn Plaisance & Thomas Reydon (eds.), Philosophy of Behavioral Biology. Springer. pp. 65-82.
    I use a contrastive theory of causal explanation to analyze the notion of a genetic trait. The resulting definition is relational, an implication of which is that no trait is genetic always and everywhere. Rather, every trait may be either genetic or non-genetic, depending on explanatory context. I also outline some other advantages of connecting the debate to the wider causation literature, including how that yields us an account of the distinction between genetic traits and genetic dispositions.
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  • Can ANOVA Measure Causal Strength?Robert Northcott - 2008 - Quarterly Review of Biology 83 (1):47-55.
    The statistical technique of analysis of variance is often used by biologists as a measure of causal factors’ relative strength or importance. I argue that it is a tool ill suited to this purpose, on several grounds. I suggest a superior alternative, and outline some implications. I finish with a diagnosis of the source of error – an unwitting inheritance of bad philosophy that now requires the remedy of better philosophy.
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  • Causation and Contrast Classes.Robert Northcott - 2008 - Philosophical Studies 139 (1):111 - 123.
    I argue that causation is a contrastive relation: c-rather-than-C* causes e-rather-than-E*, where C* and E* are contrast classes associated respectively with actual events c and e. I explain why this is an improvement on the traditional binary view, and develop a detailed definition. It turns out that causation is only well defined in ‘uniform’ cases, where either all or none of the members of C* are related appropriately to members of E*.
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  • Walsh on Causes and Evolution.Robert Northcott - 2010 - Philosophy of Science 77 (3):457-467.
    Denis Walsh has written a striking new defense in this journal of the statisticalist (i.e., noncausalist) position regarding the forces of evolution. I defend the causalist view against his new objections. I argue that the heart of the issue lies in the nature of nonadditive causation. Detailed consideration of that turns out to defuse Walsh’s ‘description‐dependence’ critique of causalism. Nevertheless, the critique does suggest a basis for reconciliation between the two competing views. *Received December 2009; revised December 2009. †To contact (...)
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  • Partial Explanations in Social Science’.Robert Northcott - 2012 - In Harold Kincaid (ed.), The Oxford Handbook of Philosophy of Social Science. Oxford University Press. pp. 130-153.
    Comparing different causes’ importance, and apportioning responsibility between them, requires making good sense of the notion of partial explanation, that is, of degree of explanation. How much is this subjective, how much objective? If the causes in question are probabilistic, how much is the outcome due to them and how much to simple chance? I formulate the notion of degree of causation, or effect size, relating it to influential recent work in the literature on causation. I examine to what extent (...)
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  • Genetic Representation Explains the Cluster of Innateness‐Related Properties.Nicholas Shea - 2012 - Mind and Language 27 (4):466-493.
    The concept of innateness is used to make inferences between various better-understood properties, like developmental canalization, evolutionary adaptation, heritability, species-typicality, and so on (‘innateness-related properties’). This article uses a recently-developed account of the representational content carried by inheritance systems like the genome to explain why innateness-related properties cluster together, especially in non-human organisms. Although inferences between innateness-related properties are deductively invalid, and lead to false conclusions in many actual cases, where some aspect of a phenotypic trait develops in reliance on (...)
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  • Weighted Explanations in History.Robert Northcott - 2008 - Philosophy of the Social Sciences 38 (1):76-96.
    , whereby some causes are deemed more important than others, are ubiquitous in historical studies. Drawing from influential recent work on causation, I develop a definition of causal-explanatory strength. This makes clear exactly which aspects of explanatory weighting are subjective and which objective. It also sheds new light on several traditional issues, showing for instance that: underlying causes need not be more important than proximate ones; several different causes can each be responsible for most of an effect; small causes need (...)
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  • ‘More of a Cause’: Recent Work on Degrees of Causation and Responsibility.Alex Kaiserman - 2018 - Philosophy Compass 13 (7):e12498.
    It is often natural to compare two events by describing one as ‘more of a cause’ of some effect than the other. But what do such comparisons amount to, exactly? This paper aims to provide a guided tour of the recent literature on ‘degrees of causation’. Section 2 looks at what I call ‘dependence measures’, which arise from thinking of causes as difference-makers. Section 3 looks at what I call ‘production measures’, which arise from thinking of causes as jointly sufficient (...)
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