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Daniel Steel [53]Daniel Patrick Steel [1]
  1.  41
    Across the Boundaries: Extrapolation in Biology and Social Science.Daniel Steel - 2008 - Oxford University Press.
    Inferences like these are known as extrapolations.
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  2. Epistemic Values and the Argument From Inductive Risk.Daniel Steel - 2010 - Philosophy of Science 77 (1):14-34.
    Critics of the ideal of value‐free science often assume that they must reject the distinction between epistemic and nonepistemic values. I argue that this assumption is mistaken and that the distinction can be used to clarify and defend the argument from inductive risk, which challenges the value‐free ideal. I develop the idea that the characteristic feature of epistemic values is that they promote, either intrinsically or extrinsically, the attainment of truths. This proposal is shown to answer common objections to the (...)
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  3.  53
    Environmental Justice, Values, and Scientific Expertise.Daniel Steel & Kyle Powys Whyte - 2012 - Kennedy Institute of Ethics Journal 22 (2):163-182.
  4.  52
    Acceptance, Values, and Inductive Risk.Daniel Steel - 2013 - Philosophy of Science 80 (5):818-828.
    The argument from inductive risk attempts to show that practical and ethical costs of errors should influence standards of evidence for accepting scientific claims. A common objection charges that this argument presupposes a behavioral theory of acceptance that is inappropriate for science. I respond by showing that the argument from inductive risk is supported by a nonbehavioral theory of acceptance developed by Cohen, which defines acceptance in terms of premising. Moreover, I argue that theories designed to explain how acceptance can (...)
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  5. Indeterminism and the Causal Markov Condition.Daniel Steel - 2005 - British Journal for the Philosophy of Science 56 (1):3-26.
    The causal Markov condition (CMC) plays an important role in much recent work on the problem of causal inference from statistical data. It is commonly thought that the CMC is a more problematic assumption for genuinely indeterministic systems than for deterministic ones. In this essay, I critically examine this proposition. I show how the usual motivation for the CMC—that it is true of any acyclic, deterministic causal system in which the exogenous variables are independent—can be extended to the indeterministic case. (...)
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  6. Bayesian Confirmation Theory and The Likelihood Principle.Daniel Steel - 2007 - Synthese 156 (1):53-77.
    The likelihood principle (LP) is a core issue in disagreements between Bayesian and frequentist statistical theories. Yet statements of the LP are often ambiguous, while arguments for why a Bayesian must accept it rely upon unexamined implicit premises. I distinguish two propositions associated with the LP, which I label LP1 and LP2. I maintain that there is a compelling Bayesian argument for LP1, based upon strict conditionalization, standard Bayesian decision theory, and a proposition I call the practical relevance principle. In (...)
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  7. Philosophy and the Precautionary Principle: Science, Evidence, and Environmental Policy.Daniel Steel - 2014 - Cambridge University Press.
    Scholars in philosophy, law, economics and other fields have widely debated how science, environmental precaution, and economic interests should be balanced in urgent contemporary problems, such as climate change. One controversial focus of these discussions is the precautionary principle, according to which scientific uncertainty should not be a reason for delay in the face of serious threats to the environment or health. While the precautionary principle has been very influential, no generally accepted definition of it exists and critics charge that (...)
     
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  8.  41
    Acceptance, Values, and Probability.Daniel Steel - 2015 - Studies in History and Philosophy of Science Part A 53:81-88.
  9.  74
    Social Mechanisms and Causal Inference.Daniel Steel - 2004 - Philosophy of the Social Sciences 34 (1):55-78.
    Several authors have claimed that mechanisms play a vital role in distinguishing between causation and mere correlation in the social sciences. Such claims are sometimes interpreted to mean that without mechanisms, causal inference in social science is impossible. The author agrees with critics of this proposition but explains how the account of how mechanisms aid causal inference can be interpreted in a way that does not depend on it. Nevertheless, he shows that this more charitable version of the account is (...)
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  10.  84
    A New Approach to Argument by Analogy: Extrapolation and Chain Graphs.Daniel Steel & S. Kedzie Hall - 2010 - Philosophy of Science 77 (5):1058-1069.
    In order to make scientific results relevant to practical decision making, it is often necessary to transfer a result obtained in one set of circumstances—an animal model, a computer simulation, an economic experiment—to another that may differ in relevant respects—for example, to humans, the global climate, or an auction. Such inferences, which we can call extrapolations, are a type of argument by analogy. This essay sketches a new approach to analogical inference that utilizes chain graphs, which resemble directed acyclic graphs (...)
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  11.  21
    A Bayesian Way to Make Stopping Rules Matter.Daniel Steel - 2003 - Erkenntnis 58 (2):213--227.
    Disputes between advocates of Bayesians and more orthodox approaches to statistical inference presuppose that Bayesians must regard must regard stopping rules, which play an important role in orthodox statistical methods, as evidentially irrelevant.In this essay, I show that this is not the case and that the stopping rule is evidentially relevant given some Bayesian confirmation measures that have been seriously proposed. However, I show that accepting a confirmation measure of this sort comes at the cost of rejecting two useful ancillaryBayesian (...)
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  12.  46
    Can a Reductionist Be a Pluralist?Daniel Steel - 2004 - Biology and Philosophy 19 (1):55-73.
    Pluralism is often put forth as a counter-position to reductionism. In this essay, I argue that reductionism and pluralism are in fact consistent. I propose that there are several potential goals for reductions and that the proper form of a reduction should be considered in tandem with the goal that it aims to achieve. This insight provides a basis for clarifying what version of reductionism are currently defended, for explicating the notion of a fundamental level of explanation, and for showing (...)
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  13.  91
    Cartwright on Causality: Methods, Metaphysics and Modularity.Daniel Steel - 2010 - Economics and Philosophy 26 (1):77-86.
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  14.  3
    Collaborative Efforts With Opioid Users to Promote Competence and Voluntariness in Clinical Trials With Injectable Opioid Assisted Treatment.Kirsten Marchand, Daniel Steel & Eugenia Oviedo-Joekes - 2017 - American Journal of Bioethics 17 (12):W1-W3.
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  15.  3
    Our Life Depends on This Drug: Competence, Inequity, and Voluntary Consent in Clinical Trials on Supervised Injectable Opioid Assisted Treatment.Daniel Steel, Kirsten Marchand & Eugenia Oviedo-Joekes - 2017 - American Journal of Bioethics 17 (12):32-40.
    Supervised injectable opioid assisted treament prescribes injectable opioids to individuals for whom other forms of addiction treatment have been ineffective. In this article, we examine arguments that opioid-dependent people should be assumed incompetent to voluntarily consent to clinical research on siOAT unless proven otherwise. We agree that concerns about competence and voluntary consent deserve careful attention in this context. But we oppose framing the issue solely as a matter of the competence of opioid-dependent people and emphasize that it should be (...)
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  16. What If the Principle of Induction Is Normative? Formal Learning Theory and Hume's Problem.Daniel Steel & S. Kedzie Hall - 2010 - International Studies in the Philosophy of Science 24 (2):171-185.
    This article argues that a successful answer to Hume's problem of induction can be developed from a sub-genre of philosophy of science known as formal learning theory. One of the central concepts of formal learning theory is logical reliability: roughly, a method is logically reliable when it is assured of eventually settling on the truth for every sequence of data that is possible given what we know. I show that the principle of induction (PI) is necessary and sufficient for logical (...)
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  17.  30
    Comment on Hausman & Woodward on the Causal Markov Condition.Daniel Steel - 2006 - British Journal for the Philosophy of Science 57 (1):219-231.
    Woodward present an argument for the Causal Markov Condition (CMC) on the basis of a principle they dub ‘modularity’ ([1999, 2004]). I show that the conclusion of their argument is not in fact the CMC but a substantially weaker proposition. In addition, I show that their argument is invalid and trace this invalidity to two features of modularity, namely, that it is stated in terms of pairwise independence and ‘arrow-breaking’ interventions. Hausman & Woodward's argument can be rendered valid through a (...)
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  18.  13
    Homogeneity, Selection, and the Faithfulness Condition.Daniel Steel - 2006 - Minds and Machines 16 (3):303-317.
    The faithfulness condition (FC) is a useful principle for inferring causal structure from statistical data. The usual motivation for the FC appeals to theorems showing that exceptions to it have probability zero, provided that some apparently reasonable assumptions obtain. However, some have objected that, the theorems notwithstanding, exceptions to the FC are probable in commonly occurring circumstances. I argue that exceptions to the FC are probable in the circumstances specified by this objection only given the presence of a condition that (...)
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  19.  8
    Causality, Causal Models, and Social Mechanisms.Daniel Steel - 2011 - In Ian Jarvie Jesus Zamora Bonilla (ed.), The Sage Handbook of the Philosophy of Social Sciences. pp. 288.
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  20. Bayesian Statistics in Radiocarbon Calibration.Daniel Steel - 2001 - Proceedings of the Philosophy of Science Association 2001 (3):S153-.
    Critics of Bayesianism often assert that scientists are not Bayesians. The widespread use of Bayesian statistics in the field of radiocarbon calibration is discussed in relation to this charge. This case study illustrates the willingness of scientists to use Bayesian statistics when the approach offers some advantage, while continuing to use orthodox methods in other contexts. The case of radiocarbon calibration, therefore, suggests a picture of statistical practice in science as eclectic and pragmatic rather than rigidly adhering to any one (...)
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  21.  38
    Methodological Individualism, Explanation, and Invariance.Daniel Steel - 2006 - Philosophy of the Social Sciences 36 (4):440-463.
    This article examines methodological individualism in terms of the theory that invariance under intervention is the signal feature of generalizations that serve as a basis for causal explanation. This theory supports the holist contention that macro-level generalizations can explain, but it also suggests a defense of methodological individualism on the grounds that greater range of invariance under intervention entails deeper explanation. Although this individualist position is not threatened by multiple-realizability, an argument for it based on rational choice theory is called (...)
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  22.  20
    The Precautionary Principle and the Dilemma Objection.Daniel Steel - 2013 - Ethics, Policy and Environment 16 (3):321-340.
    The dilemma objection charges that ?weak? versions of the precautionary principle (PP) are vacuous while ?strong? ones are incoherent. I respond that the ?weak? versus ?strong? distinction is misleading and should be replaced with a contrast between PP as a meta-rule and PP proper. Meta versions of PP require that the decision-making procedures used for environmental policy not be susceptible to paralysis by scientific uncertainty. Such claims are substantive because they often recommend against basing environmental policy decisions on cost?benefit analysis. (...)
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  23. Naturalism and the Enlightenment Ideal : Rethinking a Central Debate in the Philosophy of Social Science.Daniel Steel & S. Kedzie Hall - 2010 - In P. D. Magnus & Jacob Busch (eds.), New Waves in Philosophy of Science. Palgrave-Macmillan.
    The naturalism versus interpretivism debate the in philosophy of social science is traditionally framed as the question of whether social science should attempt to emulate the methods of natural science. I show that this manner of formulating the issue is problematic insofar as it presupposes an implausibly strong unity of method among the natural sciences. I propose instead that what is at stake in this debate is the feasibility and desirability of what I call the Enlightenment ideal of social science. (...)
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  24.  13
    Mechanisms and Functional Hypotheses in Social Science.Daniel Steel - 2005 - Philosophy of Science 72 (5):941-952.
  25.  79
    Cartwright on Causality: Methods, Metaphysics and Modularity Hunting Causes and Using Them: Approaches in Philosophy and Economics , Nancy Cartwright. Cambridge University Press, 2008, X + 270 Pages. [REVIEW]Daniel Steel - 2010 - Economics and Philosophy 26 (1):77-86.
  26. Rethinking the Interpretivism Versus Naturalism Debate in the Philosophy of Social Science.Daniel Steel - manuscript
    The naturalism versus interpretivism debate in social science is traditionally framed as the question of whether social science should attempt to emulate the methods of natural science. I argue that this manner of formulating the issue is problematic insofar as it presupposes an implausibly strong unity of method among the natural sciences. I propose instead that the core question of the debate is the extent to which reliable causal inference is possible in social science, a question that cannot be answered (...)
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  27.  87
    Testability and Ockham's Razor: How Formal and Statistical Learning Theory Converge in the New Riddle of Induction. [REVIEW]Daniel Steel - 2009 - Journal of Philosophical Logic 38 (5):471 - 489.
    Nelson Goodman’s new riddle of induction forcefully illustrates a challenge that must be confronted by any adequate theory of inductive inference: provide some basis for choosing among alternative hypotheses that fit past data but make divergent predictions. One response to this challenge is to distinguish among alternatives by means of some epistemically significant characteristic beyond fit with the data. Statistical learning theory takes this approach by showing how a concept similar to Popper’s notion of degrees of testability is linked to (...)
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  28.  35
    Extrapolation, Uncertainty Factors, and the Precautionary Principle.Daniel Steel - 2011 - Studies in History and Philosophy of Science Part C 42 (3):356-364.
    This essay examines the relationship between the precautionary principle and uncertainty factors used by toxicologists to estimate acceptable exposure levels for toxic chemicals from animal experiments. It shows that the adoption of uncertainty factors in the United States in the 1950s can be understood by reference to the precautionary principle, but not by cost-benefit analysis because of a lack of relevant quantitative data at that time. In addition, it argues that uncertainty factors continue to be relevant to efforts to implement (...)
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  29.  5
    Scientists’ Attitudes on Science and Values: Case Studies and Survey Methods in Philosophy of Science.Daniel Steel, Chad Gonnerman & Michael O'Rourke - 2017 - Studies in History and Philosophy of Science Part A 63:22-30.
    This article examines the relevance of survey data of scientists’ attitudes about science and values to case studies in philosophy of science. We describe two methodological challenges confronting such case studies: 1) small samples, and 2) potential for bias in selection, emphasis, and interpretation. Examples are given to illustrate that these challenges can arise for case studies in the science and values literature. We propose that these challenges can be mitigated through an approach in which case studies and survey methods (...)
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  30. What If the Principle of Induction is Normative? Means-Ends Epistemology and Hume's Problem.Daniel Steel - manuscript
    I develop a critique of Hume’s infamous problem of induction based upon the idea that the principle of induction (PI) is a normative rather than descriptive claim. I argue that Hume’s problem is a false dilemma, since the PI might be neither a “relation of ideas” nor a “matter of fact” but rather what I call a contingent normative statement. In this case, the PI could be justified by a means-ends argument in which the link between means and end is (...)
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  31. Mind Changes and Testability: How Formal and Statistical Learning Theory Converge in the New Riddle of Induction.Daniel Steel - manuscript
    This essay demonstrates a previously unnoticed connection between formal and statistical learning theory with regard to Nelson Goodman’s new riddle of induction. Discussions of Goodman’s riddle in formal learning theory explain how conjecturing “all green” before “all grue” can enhance efficient convergence to the truth, where efficiency is understood in terms of minimizing the maximum number of retractions or “mind changes.” Vapnik-Chervonenkis (VC) dimension is a central concept in statistical learning theory and is similar to Popper’s notion of degrees of (...)
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  32.  10
    Climate Change and Second-Order Uncertainty: Defending a Generalized, Normative, and Structural Argument From Inductive Risk.Daniel Steel - 2016 - Perspectives on Science 24 (6):696-721.
    This article critically examines a recent philosophical debate on the role of values in climate change forecasts, such as those found in assessment reports of the Intergovernmental Panel on Climate Change. On one side, several philosophers insist that the argument from inductive risk, as developed by Rudner and Douglas among others, applies to this case. AIR aims to show that ethical value judgments should influence decisions about what is sufficient evidence for accepting scientific hypotheses that have implications for policy issues. (...)
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  33. Extrapolation, Capacities, and Mechanisms.Daniel Steel - manuscript
    (Chapter 5 of Across the Boundaries, forthcoming, from Oxford University Press) This chapter argues that previous accounts of extrapolation, either by reference to capacities or mechanisms, do not adequately address the challenges confronting extrapolation. It then begins the account of how the mechanisms-approach can be developed so as to do better. The central concept in this account is what I term comparative process tracing.
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  34.  5
    Accepting an Epistemically Inferior Alternative? A Comment on Elliott and McKaughan.Daniel Steel - 2016 - Philosophy of Science 83 (4):606-612.
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  35. Inductive Rules, Background Knowledge, and Skepticism.Daniel Steel & S. Kedzie Hall - unknown
    This essay defends the view that inductive reasoning involves following inductive rules against objections that inductive rules are undesirable because they ignore background knowledge and unnecessary because Bayesianism is not an inductive rule. I propose that inductive rules be understood as sets of functions from data to hypotheses that are intended as solutions to inductive problems. According to this proposal, background knowledge is important in the application of inductive rules and Bayesianism qualifies as an inductive rule. Finally, I consider a (...)
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  36. With or Without Mechanisms A Reply to Weber.Daniel Steel - 2007 - Philosophy of the Social Sciences 37 (3):360-365.
    This reply to Erik Weber's commentary agrees that mechanisms are important for causal inference in social science, but argues that Weber makes the mistake that was the main focus of my original essay: inferring that since a problem cannot be solved without mechanisms, it can be solved with them. As it stands, this inference is invalid since the problem might be unsolvable with or without mechanisms. Any claim about the usefulness of mechanisms for some purpose requires an adequate account of (...)
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  37.  90
    Inductive Rules Are No Problem.Daniel Steel - manuscript
    This essay defends the view that inductive reasoning involves following inductive rules against objections that inductive rules are undesirable because they ignore background knowledge and unnecessary because Bayesianism is not an inductive rule. I propose that inductive rules be understood as sets of functions from data to hypotheses that are intended as solutions to inductive problems. According to this proposal, background knowledge is important in the application of inductive rules and Bayesianism qualifies as an inductive rule. Finally, I consider a (...)
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  38.  29
    Making Time Stand Still: A Response to Sober's Counter-Example to the Principle of the Common Cause.Daniel Steel - 2003 - British Journal for the Philosophy of Science 54 (2):309-317.
    In a recent article, Elliot Sober responds to challenges to a counter-example that he posed some years earlier to the Principle of the Common Cause (PCC). I agree that Sober has indeed produced a genuine counter-example to the PCC, but argue against the methodological moral that Sober wishes to draw from it. Contrary to Sober, I argue that the possibility of exceptions to the PCC does not undermine its status as a central assumption for methods that endeavor to draw causal (...)
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  39.  11
    Bayesianism and the Value of Diverse Evidence.Daniel Steel - 1996 - Philosophy of Science 63 (4):666-674.
    In a recent essay (1995), Andrew Wayne charges that Bayesian attempts to account for the rule that, ceteris paribus, diverse evidence confirms better than narrow evidence are inadequate. I reply to these criticisms and argue that, on the contrary, one of the Bayesian approaches considered by Wayne does an excellent job of explaining why, and under what circumstances, diverse evidence is valuable.
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  40.  4
    AIC and the Challenge of Complexity: A Case Study From Ecology.Remington J. Moll, Daniel Steel & Robert A. Montgomery - 2016 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 60:35-43.
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  41.  7
    Testability and Ockham’s Razor: How Formal and Statistical Learning Theory Converge in the New Riddle of Induction.Daniel Steel - 2009 - Journal of Philosophical Logic 38 (5):471-489.
    Nelson Goodman's new riddle of induction forcefully illustrates a challenge that must be confronted by any adequate theory of inductive inference: provide some basis for choosing among alternative hypotheses that fit past data but make divergent predictions. One response to this challenge is to distinguish among alternatives by means of some epistemically significant characteristic beyond fit with the data. Statistical learning theory takes this approach by showing how a concept similar to Popper's notion of degrees of testability is linked to (...)
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  42.  19
    On Not Changing the Problem: A Reply to Howson.Daniel Steel - 2011 - International Studies in the Philosophy of Science 25 (3):285 - 291.
    Howson's critique of my essay on Hume's problem of induction levels two main charges. First, Howson claims that I have attributed to him an error that he never made, and in fact which he warned against in the very text that I cite. Secondly, Howson argues that my proposed solution to Hume's problem is flawed on technical and philosophical grounds. In response to the first charge, I explain how Howson's text justifies attributing to him the claim that the principle of (...)
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  43.  16
    The Facts of the Matter: A Discussion of Norton's Material Theory of Induction.Daniel Steel - 2005 - Philosophy of Science 72 (1):188-197.
  44.  15
    Review of Sandra D. Mitchell, Unsimple Truths: Science, Complexity, and Policy[REVIEW]Daniel Steel - 2010 - Notre Dame Philosophical Reviews 2010 (5).
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  45.  7
    Causal Inference and Medical Experiments.Daniel Steel - 2011 - In Fred Gifford (ed.), Philosophy of Medicine. Elsevier. pp. 16--159.
  46.  7
    Precaution and Proportionality: A Reply to Turner.Daniel Steel - 2013 - Ethics, Policy and Environment 16 (3):344-348.
    (2013). Precaution and Proportionality: A Reply to Turner. Ethics, Policy & Environment. ???aop.label???. doi: 10.1080/21550085.2013.844572.
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  47.  11
    Warfare and Western Manufactures: A Case Study of Explanation in Anthropology.Daniel Steel - 1998 - Philosophy of Science 65 (4):649-671.
    I use an explanation of Yanomami warfare given by the anthropologist Brian Ferguson as a case study to compare the merits of the causal and unification approaches to explanation. I argue that Ferguson's insistence on explaining actual occurrences and patterns of Yanomami warfare together with his claim that all of his generalizations are statistical raises difficulties for the unification approach, because of its commitment to "deductive chauvinism." Moreover, I show that there are serious difficulties involved in comparing the "unifying power" (...)
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  48.  2
    Extrapolation, Uncertainty Factors, and the Precautionary Principle.Daniel Steel - 2011 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 42 (3):356-364.
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  49.  1
    A Reply to Jones.Daniel Steel - 1998 - Philosophy of Science 65 (4):682-687.
  50. The Philosophy of Social Science Reader.Francesco Guala & Daniel Steel (eds.) - 2010 - Routledge.
    _The Philosophy of Social Science Reader_ is an outstanding, comprehensive and up-to-date collection of key readings in the philosophy of social science, covering the essential issues, problems and debates in this important interdisciplinary area. Each section is carefully introduced by the editors, and the readings placed in context. The anthology is organized into seven clear parts: Values and Social Science Causal Inference and Explanation Interpretation Rationality and Choice Individualism Norms Cultural Evolution. Featuring the work of influential philosophers and social scientists (...)
     
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