Risky Honors

Most educators today are likely to proclaim a commitment to teaching critical thinking. Willingness to take intellectual risks such as questioning orthodox teachings or proposing unconventional solutions is an important component of critical thinking and the larger project of liberal education, yet the reward structures of educational institutions may actually function to discourage such risk-taking. In light of the extra importance placed on grades and high-stakes entrance exams in an increasingly competitive educational marketplace, this problem might presumably be magnified among honors students. This essay concludes by calling on honors educators and other interested parties to contribute their voices, their questions, and their proposed solutions to a new JNCHC Forum focusing on the tension among talented students between taking intellectual risks and a desire to avoid the personal struggle and possible failure that sometimes come from taking such risks

Computation of epidemic final size distributions

We develop a new methodology for the efficient computation of epidemic final size distributions for a broad class of Markovian models. We exploit a particular representation of the stochastic epidemic process to derive a method which is both computationally efficient and numerically stable. The algorithms we present are also physically transparent and so allow us to extend this method from the basic SIR model to a model with a phase-type infectious period and another with waning immunity. The underlying theory is applicable to many Markovian models where we wish to efficiently calculate hitting probabilities.Comment: final published versio

Inference of epidemiological parameters from household stratified data

We consider a continuous-time Markov chain model of SIR disease dynamics with two levels of mixing. For this so-called stochastic households model, we provide two methods for inferring the model parameters---governing within-household transmission, recovery, and between-household transmission---from data of the day upon which each individual became infectious and the household in which each infection occurred, as would be available from first few hundred studies. Each method is a form of Bayesian Markov Chain Monte Carlo that allows us to calculate a joint posterior distribution for all parameters and hence the household reproduction number and the early growth rate of the epidemic. The first method performs exact Bayesian inference using a standard data-augmentation approach; the second performs approximate Bayesian inference based on a likelihood approximation derived from branching processes. These methods are compared for computational efficiency and posteriors from each are compared. The branching process is shown to be an excellent approximation and remains computationally efficient as the amount of data is increased

The Expression Problem, Gracefully

The “Expression Problem” was brought to prominence by Wadler in 1998. It is widely regarded as illustrating that the two mainstream approaches to data abstraction — procedural abstraction and type abstraction— are complementary, with the strengths of one being the weaknesses of the other. Despite an extensive literature, the origin of the problem remains ill-understood. I show that the core problem is in fact the use of global constants, and demonstrate that an important aspect of the problem goes away when Java is replaced by a language like Grace, which eliminates them

Better Refactoring Tools for a Better Refactoring Strategy

Refactoring tools can improve the speed and accuracy with which we create and maintain software – but only if they are used. In practice, tools are not used as much as they could be; this seems to be because they do not align with the refactoring strategy preferred by the majority of programmers: floss refactoring. We propose five principles that characterize successful floss refactoring tools – principles that can help programmers to choose the most appropriate refactoring tools and also help toolsmiths to design more usable tools