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  1. Are Rcts the Gold Standard?Nancy Cartwright - 2007 - Biosocieties 1:11-20.
    The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...)
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  • Modelling Mechanisms with Causal Cycles.Brendan Clarke, Bert Leuridan & Jon Williamson - 2014 - Synthese 191 (8):1-31.
    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 (...)
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  • Evidence-Based Policy: What’s to Be Done About Relevance? [REVIEW]Nancy Cartwright - 2009 - Philosophical Studies 143 (1):127 - 136.
    How can philosophy of science be of more practical use? One thing we can do is provide practicable advice about how to determine when one empirical claim is relevant to the truth of another; i.e., about evidential relevance. This matters especially for evidence-based policy, where advice is thin—and misleading—about how to tell what counts as evidence for policy effectiveness. This paper argues that good efficacy results, which are all the rage now, are only a very small part of the story. (...)
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  • Causation.David K. Lewis - 1973 - Journal of Philosophy 70 (17):556-567.
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  • Causation as Influence.David K. Lewis - 2000 - Journal of Philosophy 97 (4):182-197.
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  • Measuring Effectiveness.Jacob Stegenga - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 54:62-71.
    Measuring the effectiveness of medical interventions faces three epistemological challenges: the choice of good measuring instruments, the use of appropriate analytic measures, and the use of a reliable method of extrapolating measures from an experimental context to a more general context. In practice each of these challenges contributes to overestimating the effectiveness of medical interventions. These challenges suggest the need for corrective normative principles. The instruments employed in clinical research should measure patient-relevant and disease-specific parameters, and should not be sensitive (...)
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  • Down with the Hierarchies.Jacob Stegenga - 2014 - Topoi 33 (2):313-322.
    Evidence hierarchies are widely used to assess evidence in systematic reviews of medical studies. I give several arguments against the use of evidence hierarchies. The problems with evidence hierarchies are numerous, and include methodological shortcomings, philosophical problems, and formal constraints. I argue that medical science should not employ evidence hierarchies, including even the latest and most-sophisticated of such hierarchies.
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  • On Coherent Sets and the Transmission of Confirmation.Franz Dietrich & Luca Moretti - 2004 - Philosophy of Science 72 (3):403-424.
    In this paper, we identify a new and mathematically well-defined sense in which the coherence of a set of hypotheses can be truth-conducive. Our focus is not, as usually, on the probability but on the confirmation of a coherent set and its members. We show that, if evidence confirms a hypothesis, confirmation is "transmitted" to any hypotheses that are sufficiently coherent with the former hypothesis, according to some appropriate probabilistic coherence measure such as Olsson’s or Fitelson’s measure. Our findings have (...)
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  • A Probabilistic Theory of Coherence.Branden Fitelson - 2003 - Analysis 63 (3):194–199.
    Let E be a set of n propositions E1, ..., En. We seek a probabilistic measure C(E) of the ‘degree of coherence’ of E. Intuitively, we want C to be a quantitative, probabilistic generalization of the (deductive) logical coherence of E. So, in particular, we require C to satisfy the following..
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  • Why There's No Cause to Randomize.John Worrall - 2007 - British Journal for the Philosophy of Science 58 (3):451-488.
    The evidence from randomized controlled trials (RCTs) is widely regarded as supplying the ‘gold standard’ in medicine—we may sometimes have to settle for other forms of evidence, but this is always epistemically second-best. But how well justified is the epistemic claim about the superiority of RCTs? This paper adds to my earlier (predominantly negative) analyses of the claims produced in favour of the idea that randomization plays a uniquely privileged epistemic role, by closely inspecting three related arguments from leading contributors (...)
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  • On Three Measures of Explanatory Power with Axiomatic Representations.Michael P. Cohen - 2016 - British Journal for the Philosophy of Science 67 (4):1077-1089.
    Jonah N. Schupbach and Jan Sprenger and Vincenzo Crupi and Katya Tentori have recently proposed measures of explanatory power and have shown that they are characterized by certain arguably desirable conditions or axioms. I further examine the properties of these two measures, and a third measure considered by I. J. Good and Timothy McGrew . This third measure also has an axiomatic representation. I consider a simple coin-tossing example in which only the Crupi–Tentori measure does not perform well. The Schupbach–Sprenger (...)
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  • Confirmation, Heuristics, and Explanatory Reasoning.Timothy McGrew - 2003 - British Journal for the Philosophy of Science 54 (4):553-567.
    Recent work on inference to the best explanation has come to an impasse regarding the proper way to coordinate the theoretical virtues in explanatory inference with probabilistic confirmation theory, and in particular with aspects of Bayes's Theorem. I argue that the theoretical virtues are best conceived heuristically and that such a conception gives us the resources to explicate the virtues in terms of ceteris paribus theorems. Contrary to some Bayesians, this is not equivalent to identifying the virtues with likelihoods or (...)
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  • New Axioms for Probability and Likelihood Ratio Measures.V. Crupi, N. Chater & K. Tentori - 2013 - British Journal for the Philosophy of Science 64 (1):189-204.
    Probability ratio and likelihood ratio measures of inductive support and related notions have appeared as theoretical tools for probabilistic approaches in the philosophy of science, the psychology of reasoning, and artificial intelligence. In an effort of conceptual clarification, several authors have pursued axiomatic foundations for these two families of measures. Such results have been criticized, however, as relying on unduly demanding or poorly motivated mathematical assumptions. We provide two novel theorems showing that probability ratio and likelihood ratio measures can be (...)
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  • The ‘Big Picture’: The Problem of Extrapolation in Basic Research.Tudor M. Baetu - 2016 - British Journal for the Philosophy of Science 67 (4):941-964.
    Both clinical research and basic science rely on the epistemic practice of extrapolation from surrogate models, to the point that explanatory accounts presented in review papers and biology textbooks are in fact composite pictures reconstituted from data gathered in a variety of distinct experimental setups. This raises two new challenges to previously proposed mechanistic-similarity solutions to the problem of extrapolation: one pertaining to the absence of mechanistic knowledge in the early stages of research and the second to the large number (...)
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  • The Virtues of Randomization.David Papineau - 1994 - British Journal for the Philosophy of Science 45 (2):437-450.
    Peter Urbach has argued, on Bayesian grounds, that experimental randomization serves no useful purpose in testing causal hypothesis. I maintain that he fails to distinguish general issues of statistical inference from specific problems involved in identifying causes. I concede the general Bayesian thesis that random sampling is inessential to sound statistical inference. But experimental randomization is a different matter, and often plays an essential role in our route to causal conclusions.
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  • Economic Modelling as Robustness Analysis.J. Kuorikoski, A. Lehtinen & C. Marchionni - 2010 - British Journal for the Philosophy of Science 61 (3):541-567.
    We claim that the process of theoretical model refinement in economics is best characterised as robustness analysis: the systematic examination of the robustness of modelling results with respect to particular modelling assumptions. We argue that this practise has epistemic value by extending William Wimsatt's account of robustness analysis as triangulation via independent means of determination. For economists robustness analysis is a crucial methodological strategy because their models are often based on idealisations and abstractions, and it is usually difficult to tell (...)
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  • Causation and Evidence-Based Practive - an Ontological Review.Roger Kerry, Thor Eirik Eriksen, Svein Anders Noer Lie, Stephen D. Mumford & Rani Lill Anjum - 2012 - Journal of Evaluation in Clinical Practice 18 (5):1006-1012.
    We claim that if a complete philosophy of evidence-based practice is intended, then attention to the nature of causation in health science is necessary. We identify how health science currently conceptualises causation by the way it prioritises some research methods over others. We then show how the current understanding of what causation is serves to constrain scientific progress. An alternative account of causation is offered. This is one of dispositionalism. We claim that by understanding causation from a dispositionalist stance, many (...)
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  • Is Meta-Analysis the Platinum Standard of Evidence?Jacob Stegenga - 2011 - Studies in History and Philosophy of Science Part C 42 (4):497-507.
    An astonishing volume and diversity of evidence is available for many hypotheses in the biomedical and social sciences. Some of this evidence—usually from randomized controlled trials (RCTs)—is amalgamated by meta-analysis. Despite the ongoing debate regarding whether or not RCTs are the ‘gold-standard’ of evidence, it is usually meta-analysis which is considered the best source of evidence: meta-analysis is thought by many to be the platinum standard of evidence. However, I argue that meta-analysis falls far short of that standard. Different meta-analyses (...)
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  • Causation, Prediction, and Search.Peter Spirtes, Clark Glymour & Richard Scheines - 1996 - British Journal for the Philosophy of Science 47 (1):113-123.
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  • 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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  • Interpreting Causality in the Health Sciences.Federica Russo & Jon Williamson - 2007 - 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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  • Scientific Evidence and the Law: An Objective Bayesian Formalisation of the Precautionary Principle in Pharmaceutical Regulation.Barbara Osimani - 2011 - Journal of Philosophy, Science and Law 11:1-24.
    The paper considers the legal tools that have been developed in German pharmaceutical regulation as a result of the precautionary attitude inaugurated by the Contergan decision. These tools are the notion of “well-founded suspicion”, which attenuates the requirements for safety intervention by relaxing the requirement of a proved causal connection between danger and source, and the introduction of the reversal of proof burden in liability norms. The paper focuses on the first and proposes seeing the precautionary principle as an instance (...)
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  • Scientific Explanation and the Causal Structure of the World.Ronald N. Giere & Wesley C. Salmon - 1988 - Philosophical Review 97 (3):444.
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  • An Enquiry Concerning Human Understanding.DAVID HUME - 1901 - The Monist 11:312.
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  • Book Review: Luc Bovens and Stephan Hartmann "Bayesian Epistemology". [REVIEW]Erik J. Olsson - 2005 - Studia Logica 81 (2):289-292.
    Book Review of Luc Bovens and Stephan Hartmann *Bayesian Epistemology* by Erik J. Olsson.
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  • Hunting Side Effects and Explaining Them: Should We Reverse Evidence Hierarchies Upside Down? [REVIEW]Barbara Osimani - 2013 - Journal of Evaluation in Clinical Practice (2):1-18.
    The problem of collecting, analyzing and evaluating evidence on adverse drug reactions (ADRs) is an example of the more general class of epistemological problems related to scientific inference and prediction, as well as a central problem of the health-care practice. Philosophical discussions have critically analysed the methodological pitfalls and epistemological implications of evidence assessment in medicine, however they have mainly focused on evidence of treatment efficacy. Most of this work is devoted to statistical methods of causal inference with a special (...)
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  • Causes That Make a Difference.C. Kenneth Waters - 2007 - Journal of Philosophy 104 (11):551-579.
    Biologists studying complex causal systems typically identify some factors as causes and treat other factors as background conditions. For example, when geneticists explain biological phenomena, they often foreground genes and relegate the cellular milieu to the background. But factors in the milieu are as causally necessary as genes for the production of phenotypic traits, even traits at the molecular level such as amino acid sequences. Gene-centered biology has been criticized on the grounds that because there is parity among causes, the (...)
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  • Confirmation Via Analogue Simulation: What Dumb Holes Could Tell Us About Gravity.Radin Dardashti, Karim P. Y. Thébault & Eric Winsberg - 2017 - British Journal for the Philosophy of Science 68 (1).
    In this article we argue for the existence of ‘analogue simulation’ as a novel form of scientific inference with the potential to be confirmatory. This notion is distinct from the modes of analogical reasoning detailed in the literature, and draws inspiration from fluid dynamical ‘dumb hole’ analogues to gravitational black holes. For that case, which is considered in detail, we defend the claim that the phenomena of gravitational Hawking radiation could be confirmed in the case that its counterpart is detected (...)
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  • The No Alternatives Argument.Richard Dawid, Stephan Hartmann & Jan Sprenger - 2015 - British Journal for the Philosophy of Science 66 (1):213-234.
    Scientific theories are hard to find, and once scientists have found a theory, H, they often believe that there are not many distinct alternatives to H. But is this belief justified? What should scientists believe about the number of alternatives to H, and how should they change these beliefs in the light of new evidence? These are some of the questions that we will address in this article. We also ask under which conditions failure to find an alternative to H (...)
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  • Two Models of Models in Biomedical Research.Hugh LaFollette & Niall Shanks - 1995 - Philosophical Quarterly 45 (179):141-160.
    Biomedical researchers claim there is significant biomedical information about humans which can be discovered only through experiments on intact animal systems (AMA p. 2). Although epidemiological studies, computer simulations, clinical investigation, and cell and tissue cultures have become important weapons in the biomedical scientists' arsenal, these are primarily "adjuncts to the use of animals in research" (Sigma Xi p. 76). Controlled laboratory experiments are the core of the scientific enterprise. Biomedical researchers claim these should be conducted on intact biological systems, (...)
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  • The Central Dogma as a Thesis of Causal Specificity.Marcel Weber - 2006 - History and Philosophy of the Life Sciences 28 (4):595-610.
    I present a reconstruction of F.H.C. Crick's two 1957 hypotheses "Sequence Hypothesis" and "Central Dogma" in terms of a contemporary philosophical theory of causation. Analyzing in particular the experimental evidence that Crick cited, I argue that these hypotheses can be understood as claims about the actual difference-making cause in protein synthesis. As these hypotheses are only true if restricted to certain nucleic acids in certain organisms, I then examine the concept of causal specificity and its potential to counter claims about (...)
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  • Mechanistic Information as Evidence in Decision-Oriented Science.José Luis Luján, Oliver Todt & Juan Bautista Bengoetxea - 2016 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 47 (2):293-306.
    Mechanistic information is used in the field of risk assessment in order to clarify two controversial methodological issues, the selection of inference guides and the definition of standards of evidence. In this paper we present an analysis of the concept of mechanistic information in risk assessment by recurring to previous philosophical analyses of mechanistic explanation. Our conclusion is that the conceptual analysis of mechanistic explanation facilitates a better characterization of the concept of mechanistic information. However, it also shows that the (...)
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  • Evidence-Based Medicine Must Be ..A. La Caze - 2009 - Journal of Medicine and Philosophy 34 (5):509-527.
    Proponents of evidence-based medicine (EBM) provide the “hierarchy of evidence” as a criterion for judging the reliability of therapeutic decisions. EBM's hierarchy places randomized interventional studies (and systematic reviews of such studies) higher in the hierarchy than observational studies, unsystematic clinical experience, and basic science. Recent philosophical work has questioned whether EBM's special emphasis on evidence from randomized interventional studies can be justified. Following the critical literature, and in particular the work of John Worrall, I agree that many of the (...)
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  • V — On Defining Analogy.Mary B. Hesse - 1960 - Proceedings of the Aristotelian Society 60 (1):79-100.
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  • Thinking About Mechanisms.Peter K. Machamer, Lindley Darden & Carl F. Craver - 2000 - Philosophy of Science 67 (1):1-25.
    The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.
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  • Causation: Determination and Difference-Making.Boris Kment - 2010 - Noûs 44 (1):80-111.
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  • Ways in Which Coherence is Confirmation Conducive.Luca Moretti - 2007 - Synthese 157 (3):309 - 319.
    Recent works in epistemology show that the claim that coherence is truth conducive – in the sense that, given suitable ceteris paribus conditions, more coherent sets of statements are always more probable – is dubious and possibly false. From this, it does not follows that coherence is a useless notion in epistemology and philosophy of science. Dietrich and Moretti (Philosophy of science 72(3): 403–424, 2005) have proposed a formal of account of how coherence is confirmation conducive—that is, of how the (...)
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  • State of the Field: Measuring Information and Confirmation.Vincenzo Crupi & Katya Tentori - 2014 - Studies in History and Philosophy of Science Part A 47:81-90.
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  • You’Ve Come a Long Way, Bayesians.Jonathan Weisberg - 2015 - Journal of Philosophical Logic 44 (6):817-834.
    Forty years ago, Bayesian philosophers were just catching a new wave of technical innovation, ushering in an era of scoring rules, imprecise credences, and infinitesimal probabilities. Meanwhile, down the hall, Gettier’s 1963 paper [28] was shaping a literature with little obvious interest in the formal programs of Reichenbach, Hempel, and Carnap, or their successors like Jeffrey, Levi, Skyrms, van Fraassen, and Lewis. And how Bayesians might accommodate the discourses of full belief and knowledge was but a glimmer in the eye (...)
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  • On the Application of Inductive Logic.Rudolf Carnap - 1947 - Philosophy and Phenomenological Research 8 (1):133-148.
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  • Evidence in Medicine and Evidence-Based Medicine.John Worrall - 2007 - Philosophy Compass 2 (6):981–1022.
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  • Looking for Rules in a World of Exceptions: Reflections on Evidence-Based Practice.Ross E. G. Upshur - 2005 - Perspectives in Biology and Medicine 48 (4):477-489.
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  • Analogy and Confirmation Theory.Mary Hesse - 1964 - Philosophy of Science 31 (4):319-327.
    The argument from analogy is examined from the point of view of Carnap's confirmation theory. It is argued that if inductive arguments are to be applicable to the real world, they must contain elementary analogical inferences. Carnap's system as originally developed (theλ -system) is not strong enough to take account of analogical arguments, but it is shown that the new system, which he has announced but not published in detail (theη -system), is capable of satisfying the conditions of inductive analogy. (...)
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  • Some Varieties of Robustness.Jim Woodward - 2006 - Journal of Economic Methodology 13 (2):219-240.
    It is widely believed that robustness (of inferences, measurements, models, phenomena and relationships discovered in empirical investigation etc.) is a Good Thing. However, there are many different notions of robustness. These often differ both in their normative credentials and in the conditions that warrant their deployment. Failure to distinguish among these notions can result in the uncritical transfer of considerations which support one notion to contexts in which another notion is being deployed. This paper surveys several different notions of robustness (...)
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  • Exposing the Vanities—and a Qualified Defense—of Mechanistic Reasoning in Health Care Decision Making.Jeremy Howick - 2011 - Philosophy of Science 78 (5):926-940.
    Philosophers of science have insisted that evidence of underlying mechanisms is required to support claims about the effects of medical interventions. Yet evidence about mechanisms does not feature on dominant evidence-based medicine “hierarchies.” After arguing that only inferences from mechanisms (“mechanistic reasoning”)—not mechanisms themselves—count as evidence, I argue for a middle ground. Mechanistic reasoning is not required to establish causation when we have high-quality controlled studies; moreover, mechanistic reasoning is more problematic than has been assumed. Yet where the problems can (...)
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  • Maximal Specificity and Lawlikeness in Probabilistic Explanation.Carl G. Hempel - 1968 - Philosophy of Science 35 (2):116-133.
    The article is a reappraisal of the requirement of maximal specificity (RMS) proposed by the author as a means of avoiding "ambiguity" in probabilistic explanation. The author argues that RMS is not, as he had held in one earlier publication, a rough substitute for the requirement of total evidence, but is independent of it and has quite a different rationale. A group of recent objections to RMS is answered by stressing that the statistical generalizations invoked in probabilistic explanations must be (...)
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  • The Problem of Intransigently Biased Agents.Bennett Holman & Justin P. Bruner - 2015 - Philosophy of Science 82 (5):956-968.
    In recent years the social nature of scientific inquiry has generated considerable interest. We examine the effect of an epistemically impure agent on a community of honest truth seekers. Extending a formal model of network epistemology pioneered by Zollman, we conclude that an intransigently biased agent prevents the community from ever converging to the truth. We explore two solutions to this problem, including a novel procedure for endogenous network formation in which agents choose whom to trust. We contend that our (...)
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  • Is Meta-Analysis the Platinum Standard of Evidence?Jacob Stegenga - 2011 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 42 (4):497-507.
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  • Causation in Biology: Stability, Specificity, and the Choice of Levels of Explanation.James Woodward - 2010 - Biology and Philosophy 25 (3):287-318.
    This paper attempts to elucidate three characteristics of causal relationships that are important in biological contexts. Stability has to do with whether a causal relationship continues to hold under changes in background conditions. Proportionality has to do with whether changes in the state of the cause “line up” in the right way with changes in the state of the effect and with whether the cause and effect are characterized in a way that contains irrelevant detail. Specificity is connected both to (...)
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  • Causing Something to Be One Way Rather Than Another: Genetic Information, Causal Specificity and the Relevance of Linear Order.Barbara Osimani - unknown
    Purpose The purpose of this paper is to suggest a definition of genetic information by taking into account the debate surrounding it. Particularly, the objections raised by Developmental Systems Theory to Teleosemantic endorsements of the notion of genetic information as well as deflationist approaches which suggest to ascribe the notion of genetic information a heuristic value at most, and to reduce it to that of causality. Design/methodology/approach The paper presents the notion of genetic information through its historical evolution and analyses (...)
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