Turbo Pascal timing routines for the IBM microcomputer family

Two Turbo Pascal (versions 3.0 and 4.0) software timers for the IBM microcomputer family are described: one with a 55-msec resolution and another with a 1-msec resolution. Both can be implemented without additional hardware requirements. The 55-msec timer makes use of the system-time-of-day clock; the 1-msec timer is a Turbo Pascal translation of the timer described by Bührer, Sparrer, and Weitkunat (1987). The logic of each timer is shown by a short demonstration program.     

Why There Cannot be a Single Probabilistic Measure of Coherence

Bayesian Coherence Theory of Justification or, for short, Bayesian Coherentism, is characterized by two theses, viz. (i) that our degree of confidence in the content of a set of propositions is positively affected by the coherence of the set, and (ii) that coherence can be characterized in probabilistic terms. There has been a longstanding question of how to construct a measure of coherence. We will show that Bayesian Coherentism cannot rest on a single measure of coherence, but requires a vector whose components exhaustively characterize the coherence properties of the set. Our degree of confidence in the content of the information set is a function of the reliability of the sources and the components of the coherence vector. The components of this coherence vector are weakly but not strongly separable, which blocks the construction of a single coherence measure.     

An Impossibility Result for Coherence Rankings

If we receive information from multiple independent and partially reliable information sources, then whether we are justified to believe these information items is affected by how reliable the sources are, by how well the information coheres with our background beliefs and by how internally coherent the information is. We consider the following question. Is coherence a separable determinant of our degree of belief, i.e. is it the case that the more coherent the new information is, the more justified we are in believing the new information, ceteris paribus? We show that if we consider sets of information items of any size (Holism), and if we assume that there exists a coherence Ordering over such sets and that coherence is a function of the probability distribution over the propositions in such sets (Probabilism), then Separability fails to hold.     

Democratic Answers to Complex Questions – An Epistemic Perspective

This paper addresses a problem for theories of epistemic democracy. In a decision on a complex issue which can be decomposed into several parts, a collective can use different voting procedures: Either its members vote on each sub-question and the answers that gain majority support are used as premises for the conclusion on the main issue (premise based-procedure, pbp), or the vote is conducted on the main issue itself (conclusion-based procedure, cbp). The two procedures can lead to different results. We investigate which of these procedures is better as a truth-tracker, assuming that there exists a true answer to be reached. On the basis of the Condorcet jury theorem, we show that the pbp is universally superior if the objective is to reach truth for the right reasons. If one instead is after truth for whatever reasons, right or wrong, there will be cases in which the cbp is more reliable, even though, for the most part, the pbp still is to be preferred.     

Nudges and Cultural Variance: a Note on Selinger and Whyte

Selinger and Whyte argue that Thaler and Sunstein are insufficiently sensitive to cultural variance in Nudge. I construct a taxonomy of the various roles that cultural variance may play in nudges. First, biases that are exploited in nudging may interact with features that are culturally specific. Second, cultures may be more or less susceptible to certain biases. Third, cultures may resolve conflicting biases in different ways. And finally, nudge may be enlisted for different aims in different cultures.     

Measuring voting power for dependent voters through causal models

We construct a new measure of voting power that yields reasonable measurements even if the individual votes are not cast independently. Our measure hinges on probabilities of counterfactuals, such as the probability that the outcome of a collective decision would have been yes, had a voter voted yes rather than no as she did in the real world. The probabilities of such counterfactuals are calculated on the basis of causal information, following the approach by Balke and Pearl. Opinion leaders whose votes have causal influence on other voters’ votes can have significantly more voting power under our measure. But the new measure of voting power is also sensitive to the voting rule. We show that our measure can be regarded as an average treatment effect, we provide examples in which it yields intuitively plausible results and we prove that it reduces to Banzhaf voting power in the limiting case of independent and equiprobable votes.