Clinical judgement, expertise and skilled coping

Medicine involves specific practical expertise as well as more general context-independent medical knowledge. This raises the question, what is the nature of the expertise involved? Is there a model of clinical judgement or understanding that can accommodate both elements? This paper begins with a summary of a published account of the kinds of situation-specific skill found in anaesthesia. It authors claim that such skills are often neglected because of a prejudice in favour of the ‘technical rationality’ exemplified in evidence-based medicine but they do not themselves offer a general account of the relation of practical expertise and general medical knowledge. The philosopher Hubert Dreyfus provides one model of the relation of general knowledge to situation-specific skilled coping. He claims that the former logically depends on the latter and provides two arguments, which I articulate in the second section, for this. But he mars those arguments by building in the further assumption that such situation-specific responses must be understood as concept-free and thus mindless. That assumption is held in place by three arguments all of which I criticize in the next section to give a unified account of clinical judgement as both practical and conceptually structured and thus justified in the face of a prejudice in favour of ‘technical rationality’

The naturalistic turn in economics: implications for the theory of finance

Economics is increasingly adopting the methodological standards and procedures of the natural sciences. The paper analyzes this 'naturalistic turn' from the philosophical perspective on naturalism, and I discuss the implications for the field of finance. The theory of finance is an interesting case in point for the methodological issues, as it manifests a paradigmatic tension between the pure theory of finance and Behavioral Finance. I distinguish between three kinds of naturalism: mark I, the reduction of behavior on psychoneural phenomena, mark II, the transfer of patterns of causal explanations from the natural sciences to the social sciences, mark III, the enrichment of the ontology from observer-independent to observer-relative facts. Building an integrated naturalistic paradigm from these three ingredients, I show that naturalism in economics will only be completed by a simultaneous linguistic turn, with language being analyzed from the naturalistic viewpoint. I relate this proposition with recent results of research into finance, especially connecting Behavioral Finance with the sociology of finance. --Naturalism,causation in economics,neuroeconomics,behavioral finance,social ontology,sociology of finance

Why do we need to employ Bayesian statistics and how can we employ it in studies of moral education?: With practical guidelines to use JASP for educators and researchers

ABSTRACTIn this article, we discuss the benefits of Bayesian statistics and how to utilize them in studies of moral education. To demonstrate concrete examples of the applications of Bayesian statistics to studies of moral education, we reanalyzed two data sets previously collected: one small data set collected from a moral educational intervention experiment, and one big data set from a large-scale Defining Issues Test-2 survey. The results suggest that Bayesian analysis of data sets collected from moral educational studies can provide additional useful statistical information, particularly that associated with the strength of evidence supporting alternative hypotheses, which has not been provided by the classical frequentist approach focusing on P-values. Finally, we introduce several practical guidelines pertaining to how to utilize Bayesian statistics, including the utilization of newly developed free statistical software, Jeffrey’s Amazing Statistics Program, and thresholding based on Bayes Factors, to scholars in the field of moral education

Parsimony versus reductionism: how can crowd psychology be introduced into computer simulation?

Computer simulations are increasingly being used to predict the behaviour of crowds. However, the models used are mainly based on video observations, not an understanding of human decision making. Theories of crowd psychology can elucidate the factors underpinning collective behaviour in human crowds. Yet, in contrast to psychology, computer science must rely upon mathematical formulations in order to implement algorithms and keep models manageable. Here we address the problems and possible solutions encountered when incorporating social psychological theories of collective behaviour in computer modelling. We identify that one primary issue is retaining parsimony in a model whilst avoiding reductionism by excluding necessary aspects of crowd psychology, such as the behaviour of groups. We propose cognitive heuristics as a potential avenue to create a parsimonious model that incorporates core concepts of collective behaviour derived from empirical research in crowd psychology

Behavioral Economics

Behavioral economics uses evidence from psychology and other disciplines to create models of limits on rationality, willpower and self-interest, and explore their implications in economic aggregates. This paper reviews the basic themes of behavioral economics: Sensitivity of revealed preferences to descriptions of goods and procedures; generalizations of models of choice over risk, ambiguity, and time; fairness and reciprocity; non-Bayesian judgment; and stochastic equilibrium and learning. A central issue is what happens in equilibrium when agents are imperfect but heterogeneous; sometimes firms “repair” limits through sorting, but profit-maximizing firms can also exploit limits of consumers. Frontiers of research are careful formal theorizing about psychology and studies with field data. Neuroeconomics extends the psychological data use to inform theorizing to include details of neural circuitry. It is likely to support rational choice theory in some cases, to buttress behavioral economics in some cases, and to suggest different constructs as well

Evolutionary robotics and neuroscience

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