Science,politics and regulation: The trust-based approach to the demarcation problem

Drawing on literature on values in science and a case-study of UK cancer policy, this paper argues for a novel account of the demarcation project in terms of trustworthiness. The first part of the paper addresses the relationship between science, politics and demarcation. In 2010, the UK government decided to pay more for cancer drugs than for drugs for other diseases; in 2016, this Cancer Drugs Fund was reformed so as to lower the evidential standards for approving cancer drugs, rather than paying more for them. Are these two ways of treating cancer as “special” importantly different? This paper argues that, if we the argument from inductive risk seriously, they seem equivalent. This result provides further reason to doubt the notion of demarcating science from non-science. However, the second part of the paper complicates this story, arguing that considerations of epistemic trust might give us reasons to prefer epistemic communities centred around “broadly acceptable” standards, and which are “sociologically well-ordered”, regardless of inductive risk concerns. After developing these claims through the cancer case-study, the final section suggests how these concerns might motivate novel versions of the demarcation project.     

Kant and the scope of the analytic method

The paper investigates Kant's pre-critical views on the use of analytic and synthetic methods in Newtonian science and in philosophical reasoning. In his 1755/56 writings, Kant made use of two variants of the analytic method, i.e., conceptual analysis in a Cartesian (or Leibnizean) sense, and analysis of the phenomena in a Newtonian sense. His Prize Essay (1764) defends Newton's analytic method of physics as appropriate for philosophy, in contradistinction to the synthetic method of mathematics. A closer look, however, shows that Kant does not identify Newton's method with conceptual analysis, but just suggests a methodological analogy between both methods. Kant’s 1768 paper on incongruent counterparts also fits in with his pre-critical use of conceptual analysis. Here, Kant criticizes Leibniz’ relational concept of space, arguing that it is incompatible with the phenomenon of chiral objects. Since this result was in conflict with his pre-critical views about space, Kant abandoned the analytic method of philosophy in favour of his critical method. The paper closes by comparing Kant's pre-critical analytic method and the way in which he once again took up the methodological analogy between Newtonian science and metaphysics, in the preface B to the Critique of Pure Reason, in the context of his thought experiment of pure reason.     

Mathematical method and Newtonian science in the philosophy of Christian Wolff

This paper aims to illuminate Christian Wolff’s view of mathematical reasoning, and its use in metaphysics, by comparing his and Leibniz’s responses to Newton’s work. Both Wolff and Leibniz object that Newton’s metaphysics is based on ideas of sense and imagination that are suitable only for mathematics. Yet Wolff expresses more regard (than Leibniz) for Newton’s scientific achievement. Wolff’s approval of the use of imaginative ideas in Newtonian mathematical science seems to commit him to an inconsistent triad. For he rejects their use in metaphysics, and also holds that every scientific discipline must follow mathematics’ method. A facile resolution would be to suppose Wolff identifies the method of mathematics with the order in which propositions are deduced, or with “analysis” that reveals the structure of concepts. This would be to assimilate Wolff’s view to Leibniz’s (on which all mathematical propositions are ultimately derived from definitions, and definitions are justified by conceptual analysis). On this construal, mathematical reasoning involves only the understanding. But Wolff conceives mathematics’ method more broadly, to include processes of concept-formation which involve perception and imagination. Thus my way of resolving the tension is to find roles for perception and imagination in the formation of metaphysical concepts.     

Effect of Cu seed on the synthesis and characterization of FeCo alloy nano-particles by using polyol method

Fine metal particles with uniform shape,narrow size distribution and high purity are increasingly needed for specific uses in high tech industrial application.We report the direct chemical synthesis of FeCo alloy particles using the mixture of FeCl2·4H2O,Co(Ac) 2·4H2O(Ac:acetate) and NaOH in ethylene glycol,and then obtained FeCo alloy particles better dispersed by adding the polyvinylpyrrolidone(PVP) and also the size could be controlled by adding copper.The prepared nano-particles were characterized using FESEM,XRD and VSM.The mean diameter of these particles was varied in the range of submicrometer to nanometer with metal-ion concentration.FeCo particles showed the typical soft magnetic properties.     

A simple diagnostic method for the differentiation of Tamm-Horsfall glycoproteins from healthy probands and those from recurrent calcium oxalate renal stone formers

Tamm-Horsfall glycoproteins (THPs)^* from healthy probands, and those from a majority of recurrent calcium oxalate renal stone formers, reveal different properties when analyzed using isoelectric focusing. The pl-values of THPs from healthy probands are approximately 3.5 while THPs from recurrent renal stone formers have pl-values between 4.5 and 6. The two groups of THPs exhibit completely different protein patterns in IEF. This proves the structural difference of these THPs. The differences in IEF analysis allow the differentiation between THPs from healthy probands and those from recurrent calcium oxalate stone formers. These differences could possibly by used as a simple diagnostic method for the recognition of recurrent calcium oxalate renal stone formers.     

Bayesian Forecasting for Financial Risk Management,Pre and Post the Global Financial Crisis

Value‐at‐risk (VaR) forecasting via a computational Bayesian framework is considered. A range of parametric models is compared, including standard, threshold nonlinear and Markov switching generalized autoregressive conditional heteroskedasticity (GARCH) specifications, plus standard and nonlinear stochastic volatility models, most considering four error probability distributions: Gaussian, Student‐t, skewed‐t and generalized error distribution. Adaptive Markov chain Monte Carlo methods are employed in estimation and forecasting. A portfolio of four Asia–Pacific stock markets is considered. Two forecasting periods are evaluated in light of the recent global financial crisis. Results reveal that: (i) GARCH models outperformed stochastic volatility models in almost all cases; (ii) asymmetric volatility models were clearly favoured pre crisis, while at the 1% level during and post crisis, for a 1‐day horizon, models with skewed‐t errors ranked best, while integrated GARCH models were favoured at the 5% level; (iii) all models forecast VaR less accurately and anti‐conservatively post crisis. Copyright © 2011 John Wiley & Sons, Ltd.