The effect of self-generated information on the plausibility of unlikely autobiographical events

Plausibility of unlikely events was investigated using a pre-test and post-test of the Life Events Inventory (Garry, et al, 1996). Students (N = 55) at the University of Nevada, Las Vegas completed two sessions, including a plausibility scenario phase in which they were asked to describe four events chosen by the researcher from the pre-test on the basis of reported plausibility. Two of the events were rated low in plausibility and two were rated high in plausibility. Results indicate that plausibility ratings increase more for low rated items when participants are asked to describe those items than for control items which are not described

A note on p-values interpreted as plausibilities

P-values are a mainstay in statistics but are often misinterpreted. We propose a new interpretation of p-value as a meaningful plausibility, where this is to be interpreted formally within the inferential model framework. We show that, for most practical hypothesis testing problems, there exists an inferential model such that the corresponding plausibility function, evaluated at the null hypothesis, is exactly the p-value. The advantages of this representation are that the notion of plausibility is consistent with the way practitioners use and interpret p-values, and the plausibility calculation avoids the troublesome conditioning on the truthfulness of the null. This connection with plausibilities also reveals a shortcoming of standard p-values in problems with non-trivial parameter constraints.Comment: 13 pages, 1 figur

Extending the Harper Identity to Iterated Belief Change

The field of iterated belief change has focused mainly on revision, with the other main operator of AGM belief change theory, i.e. contraction, receiving relatively little attention. In this paper we extend the Harper Identity from single-step change to define iterated contraction in terms of iterated revision. Specifically, just as the Harper Identity provides a recipe for defining the belief set resulting from contracting A in terms of (i) the initial belief set and (ii) the belief set resulting from revision by ¬A, we look at ways to define the plausibility ordering over worlds resulting from contracting A in terms of (iii) the initial plausibility ordering, and (iv) the plausibility ordering resulting from revision by ¬A. After noting that the most straightforward such extension leads to a trivialisation of the space of permissible orderings, we provide a family of operators for combining plausibility orderings that avoid such a result. These operators are characterised in our domain of interest by a pair of intuitively compelling properties, which turn out to enable the derivation of a number of iterated contraction postulates from postulates for iterated revision. We finish by observing that a salient member of this family allows for the derivation of counterparts for contraction of some well known iterated revision operators, as well as for defining new iterated contraction operators

Difficulties of Simplicity

This paper attempts to show that the doctrine of divine simplicity suffers from difficulties which undermine its plausibility. The main difficulties explored are Plantinga’s problem of double identification, Pruss’ multiple attributes problem, and Schmitt’s co-specificity problem. In more recent years, defenders of the doctrine have offered a way out of these problems by interpreting it in light of a truthmaker account of predication. This paper analyzes this recent defense, among others, and attempts to show that this new interpretation of divine simplicity still has problems which undermine the plausibility of the doctrine

Modeling Semantic Plausibility by Injecting World Knowledge

Distributional data tells us that a man can swallow candy, but not that a man can swallow a paintball, since this is never attested. However both are physically plausible events. This paper introduces the task of semantic plausibility: recognizing plausible but possibly novel events. We present a new crowdsourced dataset of semantic plausibility judgments of single events such as "man swallow paintball". Simple models based on distributional representations perform poorly on this task, despite doing well on selection preference, but injecting manually elicited knowledge about entity properties provides a substantial performance boost. Our error analysis shows that our new dataset is a great testbed for semantic plausibility models: more sophisticated knowledge representation and propagation could address many of the remaining errors.Comment: camera-ready draft (with link to data), Published at NAACL 2018 as a conference paper (oral