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Robert Northcott
Birkbeck College
Robert Northcott
Birkbeck College, London
  1. Prisoner's Dilemma Doesn't Explain Much.Robert Northcott & Anna Alexandrova - 2015 - In Martin Peterson (ed.), The Prisoner’s Dilemma. Classic philosophical arguments. Cambridge: Cambridge University Press. pp. 64-84.
    We make the case that the Prisoner’s Dilemma, notwithstanding its fame and the quantity of intellectual resources devoted to it, has largely failed to explain any phenomena of social scientific or biological interest. In the heart of the paper we examine in detail a famous purported example of Prisoner’s Dilemma empirical success, namely Axelrod’s analysis of WWI trench warfare, and argue that this success is greatly overstated. Further, we explain why this negative verdict is likely true generally and not just (...)
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  2. 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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  3. 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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  4. Verisimilitude: A Causal Approach.Robert Northcott - 2013 - Synthese 190 (9):1471-1488.
    I present a new definition of verisimilitude, framed in terms of causes. Roughly speaking, according to it a scientific model is approximately true if it captures accurately the strengths of the causes present in any given situation. Against much of the literature, I argue that any satisfactory account of verisimilitude must inevitably restrict its judgments to context-specific models rather than general theories. We may still endorse—and only need—a relativized notion of scientific progress, understood now not as global advance but rather (...)
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  5. How Necessary Are Randomized Controlled Trials?Robert Northcott - 2012 - In Ronald Munson (ed.), Intervention and Reflection: Basic Issues in Medical Ethics. Thomson Wadsworth. pp. 187-191.
    This short review piece is from a textbook on Medical Ethics.
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  6. Progress in Economics: Lessons From the Spectrum Auctions.Anna Alexandrova & Robert Northcott - 2009 - In Harold Kincaid & Don Ross (eds.), The Oxford Handbook of Philosophy of Economics. Oxford University Press. pp. 306--337.
    The 1994 US spectrum auction is now a paradigmatic case of the successful use of microeconomic theory for policy-making. We use a detailed analysis of it to review standard accounts in philosophy of science of how idealized models are connected to messy reality. We show that in order to understand what made the design of the spectrum auction successful, a new such account is required, and we present it here. Of especial interest is the light this sheds on the issue (...)
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  7. It's Just a Feeling: Why Economic Models Do Not Explain.Anna Alexandrova & Robert Northcott - 2013 - Journal of Economic Methodology 20 (3):262 - 267.
    Julian Reiss correctly identified a trilemma about economic models: we cannot maintain that they are false, but nevertheless explain and that only true accounts explain. In this reply we give reasons to reject the second premise ? that economic models explain. Intuitions to the contrary should be distrusted.
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  8. Comparing Apples with Oranges.Robert Northcott - 2005 - Analysis 65 (1):12-18.
    Comparisons of causal efficacy are ubiquitous in the practice of science and indeed everyday life. I focus on just one aspect of this task – one to my knowledge nowhere yet addressed satisfactorily – namely, comparing the efficacies of two causes that work in apparently incommensurable ways. Contrary to common opinion I argue that, to be comparable, it is neither necessary nor sufficient that two causes also be commensurable.
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  9. Natural-Born Determinists: A New Defense of Causation as Probability-Raising.Robert Northcott - 2010 - Philosophical Studies 150 (1):1-20.
    A definition of causation as probability-raising is threatened by two kinds of counterexample: first, when a cause lowers the probability of its effect; and second, when the probability of an effect is raised by a non-cause. In this paper, I present an account that deals successfully with problem cases of both these kinds. In doing so, I also explore some novel implications of incorporating into the metaphysical investigation considerations of causal psychology.
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  10. 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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  11.  94
    Free Will is Not a Testable Hypothesis.Robert Northcott - 2019 - Erkenntnis 84 (3):617-631.
    Much recent work in neuroscience aims to shed light on whether we have free will. Can it? Can any science? To answer, we need to disentangle different notions of free will, and clarify what we mean by ‘empirical’ and ‘testable’. That done, my main conclusion is, duly interpreted: that free will is not a testable hypothesis. In particular, it is neither verifiable nor falsifiable by empirical evidence. The arguments for this are not a priori but rather are based on a (...)
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  12.  9
    Big Data and Prediction: Four Case Studies.Robert Northcott - forthcoming - Studies in History and Philosophy of Science Part A.
    Has the rise of data-intensive science, or ‘big data’, revolutionized our ability to predict? Does it imply a new priority for prediction over causal understanding, and a diminished role for theory and human experts? I examine four important cases where prediction is desirable: political elections, the weather, GDP, and the results of interventions suggested by economic experiments. These cases suggest caution. Although big data methods are indeed very useful sometimes, in this paper’s cases they improve predictions either limitedly or not (...)
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  13.  21
    When Are Purely Predictive Models Best?Robert Northcott - unknown
    Can purely predictive models be useful in investigating causal systems? I argue ‘yes’. Moreover, in many cases not only are they useful, they are essential. The alternative is to stick to models or mechanisms drawn from well-understood theory. But a necessary condition for explanation is empirical success, and in many cases in social and field sciences such success can only be achieved by purely predictive models, not by ones drawn from theory. Alas, the attempt to use theory to achieve explanation (...)
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  14. 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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  15.  30
    Conceived This Way: Innateness Defended.Robert Northcott & Gualtiero Piccinini - 2017 - Philosophers' Imprint 18.
    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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  16. Causal Efficacy and the Analysis of Variance.Robert Northcott - 2006 - Biology and Philosophy 21 (2):253-276.
    The causal impacts of genes and environment on any one biological trait are inextricably entangled, and consequently it is widely accepted that it makes no sense in singleton cases to privilege either factor for particular credit. On the other hand, at a population level it may well be the case that one of the factors is responsible for more variation than the other. Standard methodological practice in biology uses the statistical technique of analysis of variance to measure this latter kind (...)
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  17. Is Actual Difference Making Actually Different?Robert Northcott - 2009 - Journal of Philosophy 106 (11):629-633.
    This paper responds to Kenneth Waters’s account of actual difference making. Among other things, I argue that although Waters is right that researchers may sometimes be justified in focusing on genes rather than other causes of phenotypic traits, he is wrong that the apparatus of actual difference makers overcomes the traditional causal parity thesis.
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  18.  40
    Prediction Versus Accommodation in Economics.Robert Northcott - unknown
    Should we insist on prediction, i.e. on correctly forecasting the future? Or can we rest content with accommodation, i.e. empirical success only with respect to the past? I apply general considerations about this issue to the case of economics. In particular, I examine various ways in which mere accommodation can be sufficient, in order to see whether those ways apply to economics. Two conclusions result. First, an entanglement thesis: the need for prediction is entangled with the methodological role of orthodox (...)
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  19. 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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  20. 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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  21.  41
    Pre-Emption Cases May Support, Not Undermine, the Counterfactual Theory of Causation.Robert Northcott - forthcoming - Synthese:1-19.
    Pre-emption cases have been taken by almost everyone to imply the unviability of the simple counterfactual theory of causation. Yet there is ample motivation from scientific practice to endorse a simple version of the theory if we can. There is a way in which a simple counterfactual theory, at least if understood contrastively, can be supported even while acknowledging that intuition goes firmly against it in pre-emption cases – or rather, only in some of those cases. For I present several (...)
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  22. Harm and Causation.Robert Northcott - 2015 - Utilitas 27 (2):147-164.
    I propose an analysis of harm in terms of causation: harm is when a subject is caused to be worse off. The pay-off from this lies in the details. In particular, importing influential recent work from the causation literature yields a contrastive-counterfactual account. This enables us to incorporate harm's multiple senses into a unified scheme, and to provide that scheme with theoretical ballast. It also enables us to respond effectively to previous criticisms of counterfactual accounts, as well as to sharpen (...)
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  23. 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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  24. Opinion Polling and Election Predictions.Robert Northcott - 2014 - Philosophy of Science 82 (5):1260-1271.
    Election prediction by means of opinion polling is a rare empirical success story for social science. I examine the details of a prominent case, drawing two lessons of more general interest: Methodology over metaphysics. Traditional metaphysical criteria were not a useful guide to whether successful prediction would be possible; instead, the crucial thing was selecting an effective methodology. Which methodology? Success required sophisticated use of case-specific evidence from opinion polling. The pursuit of explanations via general theory or causal mechanisms, by (...)
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  25. A Dilemma for the Doomsday Argument.Robert Northcott - 2016 - Ratio 29 (3):268-282.
    I present a new case in which the Doomsday Argument runs afoul of epistemic intuition much more strongly than before. This leads to a dilemma: in the new case either DA is committed to unacceptable counterintuitiveness and belief in miracles, or else it is irrelevant. I then explore under what conditions DA can escape this dilemma. The discussion turns on several issues that have not been much emphasised in previous work on DA: a concern that I label trumping; the degree (...)
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  26.  86
    Pearson’s Wrong Turning: Against Statistical Measures of Causal Efficacy.Robert Northcott - 2004 - Philosophy of Science 72 (5):900-912.
    Standard statistical measures of strength of association, although pioneered by Pearson deliberately to be acausal, nowadays are routinely used to measure causal efficacy. But their acausal origins have left them ill suited to this latter purpose. I distinguish between two different conceptions of causal efficacy, and argue that: 1) Both conceptions can be useful 2) The statistical measures only attempt to capture the first of them 3) They are not fully successful even at this 4) An alternative definition more squarely (...)
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  27. The Irrational Game: Why There’s No Perfect System.Robert Northcott - 2006 - In Eric Bronson (ed.), Poker and Philosophy. Open Court. pp. 105-115.
    This is a chapter written for a popular audience, in which I use poker as a convenient illustration of probability, determinism and counterfactuals. More originally, I also discuss the roles of rationality versus psychological hunches, and explain why even in principle game theory cannot provide us the panacea of a perfect winning srategy. (N.B. The document I have uploaded here is slightly longer than the abbreviated version that appears in the book, and also differs in a few other minor details.) (...)
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  28. On Lewis, Schaffer and the Non-Reductive Evaluation of Counterfactuals.Robert Northcott - 2009 - Theoria 75 (4):336-343.
    Jonathan Schaffer (2004 ) proposes an ingenious amendment to David Lewis's semantics for counterfactuals. This amendment explicitly invokes the notion of causal independence, thus giving up Lewis's ambitions for a reductive counterfactual account of causation. But in return, it rescues Lewis's semantics from extant counterexamples. I present a new counterexample that defeats even Schaffer's amendment. Further, I argue that a better approach would be to follow the causal modelling literature and evaluate counterfactuals via an explicit postulated causal structure. This alternative (...)
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  29.  60
    Bad Luck or the Ref's Fault?Robert Northcott - 2010 - In Ted Richards (ed.), Soccer and Philosophy. Open Court. pp. 319-326.
    In this book chapter written for a popular audience, I discuss classic issues surrounding luck, determinism and probability in the context of the penalty shoot-outs used in football’s World Cup. Can it ever make objective sense to blame an outcome on bad luck? I go on to discuss whether we can legitimately pin the blame on any one factor at all, such as a referee. This takes us into issues surrounding the apportioning of causal responsibility.
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  30. The Scientific Study of Society, by Max Steuer. Kluwer Academic Publishers, 2003, XIII + 464 Pages. [REVIEW]Anna Alexandrova & Robert Northcott - 2004 - Economics and Philosophy 20 (2):375-381.
  31.  43
    Innateness and Science.Robert Northcott - unknown
    Although a huge range of definitions has accumulated in the philosophy, biology and psychology literatures, no consensus has been reached on exactly what innateness amounts to. This has helped fuel an increasing skepticism, one that views the concept as anachronistic and actually harmful to science. Yet it remains central to many life sciences, and to several public policy issues too. So it is correspondingly urgent that its philosophical underpinnings be properly cleaned up. In this paper, I present a new approach (...)
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