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For this reason they may appear to be more relevant to scientific evidence. These authors also agree that the value of Bayesian networks rests more clearly on their relational aspects rather than in the calculations of probabilities or degrees of belief based on Bayesian updating.

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Both Fox and Lagnado note that there is increasing empirical evidence that people are neither good estimators of probability nor good Bayesian updaters. However, the directionality that Bayesian networks capture does give some insight into at least some types of evidential reasoning -- for example, the way that jurors make judgments.

Lagnado notes that empirical studies strongly suggest that the order in which evidence is received makes a difference to the role it is given in causal model. Empirical studies on discrediting evidence suggest that jurors group evidence based on directionality -- they treat evidence as cohering independently of causal relatedness so long as the evidence shares a common direction.

They use causal models to explain away discredited evidence and will tend to explain away evidence that shares the same directionality as the evidence that is discredited In other words, jurors do not integrate evidence in a fully Bayesian way. Lagnado suggests that the grouping that jurors appear to do allows for conservation of mental energy specifically memory. He concludes by hypothesizing that we use Bayesian networks for determining interrelations among causal relations but use coherence-based reasoning when we make inferences.

Terence Anderson's "Generalisations and Evidential Reasoning" examines the usefulness of Wigmore charts for the analysis of evidence in fields other than law by applying it to an argument for a hypothesis in Assyriology.

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He concludes that "the principal barriers to cross-disciplinary analysis and communication stemmed from the fact that the outsider does not share the stock of knowledge and the knowledge-based generalisations, that are common and shared by those within the discipline" Anderson's essay would seem to support the point about form and content that I made above.

What is taken as evidence within one discipline may be seen as a principle of inference in another. Of Inference Networks and Onto-Epistemology" closes out this second group of essays. Tillers argues that while Schum's goal of a science of evidence might be possible in some subject areas, there are at least three areas where it is unlikely to work: inference about human meaning, unconscious inference implicit , and inference in the special sciences.

For Tiller, the lesson of these exceptions has to do with the inherent intentionality of human interaction with the world and the consequent humility that we should maintain about the limitations of human reason in understanding that world. The next two articles are focused on evidence-based policy -- one of the ostensive motivators for the project.

I would have liked for policy to be a more prominent theme in the volume and I take this lack to be one of its weaknesses. Practical reason intersects with rhetoric and so a scientistic approach is not fully able to capture important features of policy decision-making. They illustrate the point with an empirical study. The authors report that they charted the way that priorities were "named and framed" in the belief that a "study of 'evidence in use' is a study of language in use. They conclude that within the context of the forum, the voices of the experts became evidence and resulted in different policies than might have been the case otherwise.

While the power of randomized controlled trials is clearly established in large-scale pharmaceutical studies, for example though such studies may have other problems , it is less clear that they should be treated as the "gold standard" of evidence for social policy decisions. A primary goal of the essay is to provide a theory of evidence for use that is accessible to policy-makers -- those who are the potential users of such a theory of evidence.

To make this clear, Cartwright and Stegenga distinguish three questions. When are evidence claims credible? When is a credible claim relevant to the truth of a claim to effectiveness?

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What is the probability that a policy will be effective given a body of evidence of varying credibility relevant in different ways? Cartwright and Stegenga take three principles from philosophy of science and apply them to formulate their theory of evidence for use: truth values for causal counterfactuals are fixed by a causal model; causes are INUS conditions Insufficient but Necessary parts of Unnecessary but Sufficient conditions J.

Mackie ; and the importance of understanding how causes operate and operate together causal mechanisms The key benefits that come from the first two principles are an appreciation of the complexity of causality, a way to think about that complexity through causal modeling , and sensitivity to the multitude of factors that may be causally relevant in any given situation Mackie's INUS condition.

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  8. They emphasize the importance of seeing causes as INUS conditions. They offer as an example, the class-size reduction policy implemented in California in the early s. The program was intended to improve learning based on evidence that a lower student to teacher ratio improved learning. But the policy was implemented quickly, forcing the hiring of under-trained teachers who were less effective in the classroom.

    A more careful consideration of causal interactions might have led to anticipation of the way the negative effects of this policy could counteract the expected positive effects These borrowed philosophical ideas are developed into three principles. The first two of which are primarily concerned with facilitating causal reasoning around policy-making. They note that policy-makers are typically not interested in how a particular policy produces an effect but rather that it does. However, they argue that understanding how the effect is produced is crucial to knowing whether it will be produced in a particular context.

    Given the Leverhulmes Trust's original call for proposals, this essay and the previous one seem more directed to the concerns that gave rise to the evidence project in the first place. The Cartwright and Stegenga essay also gets my recommendation because it is a genre of philosophy of science that we are beginning to see more of and one which I heartily endorse -- philosophy of science in practice. The theory of evidence for use that they propose is explicitly intended for users of knowledge, not those who produce it, although I think it is not necessarily a bad thing for producers of knowledge to be thinking about these issues as well.

    That just makes our job hard. We need to do the best we can to help those who need to evaluate effectiveness do so as well as possible, even if the process will inevitably be flawed. Recognising that it will be flawed means making clear that policy effectiveness judgments will almost never be very secure; and so far as possible, one should hedge one's bets on them Colquhoun's essay is a defense of randomized controlled trials in precisely the area where they are most successful -- large scale pharmaceutical studies--and so seems to completely miss the point of recent criticisms of such trials.

    In addition, he appears to equate all philosophy of science with postmodernism. The remaining articles deal with various discipline-specific issues of evidence. The first of these by Hasok Chang and Grant Fisher deals with a philosophical problem. This idea is not new -- for example, Helen Longino's contextual empiricism provides an account of evidence that is context dependent -- however their account of how context functions does have some new elements. As a reminder, the paradox is that, since "All ravens are black" is formally equivalent to "All non-black things are non-ravens", a white shoe or any other non-black, non-raven should serve as evidence for "All ravens are black".

    Chang and Fisher agree with Hempel that in fact the white shoe does confirm "All ravens are black" sometimes, but not always -- it depends on context. They offer three levels of analysis to spell out a role for context in determining when observations are evidence. The first level solution involves awareness of the fact that observations must be rendered as propositions in order to participate as evidence think of the H-D model of confirmation, which they work with in the essay for the sake of simplicity.

    On Popper's view, the distinctive mark of scientific inquiry concerns the by the introduction of an auxiliary hypothesis that allows for the generation of. Book file PDF easily for everyone and every device. You can. These ways represent a fundamental aspect of the nature of science and the use of hypothesis and theories, the kinds of logic used, and much more.

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    Scientific inquiry is not easily described apart from the context of particular investigations. Price may vary. Yet formal Statistical Inference versus Decision Making. An Introduction to Bayesian Inference. Chapter 22 Introduction To Communication Theory. The analogy with physical theories is deeper than a mere analogy of method. The Logic of Comparative Social Inquiry.

    In the verisimilitude framework, scientific inquiry is conceived of, in part, as a process where inference methods ought to be calibrated 1 Introduction New Essays in Logic and Philosophy of Science. Jorge M.


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