Conceptual Analysis and Philosophical Naturalism

Entitlement is conceived as a kind of positive epistemic status, attaching to certain propositions, that involves no cognitive or intellectual accomplishment on the part of the beneficiary—a status that is in place by default. In this paper I will argue that the notion of entitlement—or something very like it—falls out of an idea that may at first blush seem rather disparate: that the evidential support relation can be understood as a kind of variably strict conditional (in the sense of Lewis 1973). Lewis provided a general recipe for deriving what he termed inner modalities from any variably strict conditional governed by a logic meeting certain constraints. On my proposal, entitlement need be nothing more exotic than the inner necessity associated with evidential support. Understanding entitlement in this way helps to answer some common concerns—in particular, the concern that entitlement could only be a pragmatic, and not genuinely epistemic, status.     

Divided stimulus control: a replication and a quantitative model

Four pigeons were trained on a conditional discrimination. The conditional stimuli were compounds of pairs of stimuli from two different dimensions, fast versus slow cycles of red or green stimuli, and short- versus long-duration presentations of these cycles. Across conditions, the probability of reinforcers for correctly responding to each dimension was varied from 0 to 1. Discriminability, measured by log d, for stimuli on a dimension increased as the relative frequency of reinforcers for that dimension increased, replicating the results of Shahan and Podlesnik (2006). Two further conditions showed that discriminability between stimuli on each dimension was unaffected by whether the stimuli on the other dimension varied or were constant. Finally, maximal discriminability was unchanged in a redundant-relevant cues condition in which either of the stimuli comprising a compound signaled the same correct response. Davison and Nevin's (1999) model provided an excellent quantitative account of the effect of relative reinforcer frequency on discriminability, and thus of the way in which divided stimulus control is itself controlled by relative reinforcement.     

Is reasoning from counterfactual antecedents evidence for counterfactual reasoning?

In most developmental studies the only error children could make on counterfactual tasks was to answer with the current state of affairs. It was concluded that children who did not show this error are able to reason counterfactually. However, children might have avoided this error by using basic conditional reasoning (Rafetseder, Cristi-Vargas, & Perner, 2010 Perner, J. and Rafetseder, E. 2010. “Counterfactual and other forms of conditional reasoning: Children lost in the nearest possible world”. In Understanding counterfactuals/Understanding causation, Edited by: Hoerl, C., McCormack, T. and Beck, S. R. New York: Oxford University Press.  [Google Scholar]). Basic conditional reasoning takes background assumptions represented as conditionals about how the world works. If an antecedent of one of these conditionals is provided by the task, then a likely conclusion can be inferred based only on background assumptions. A critical feature of counterfactual reasoning is that the selection of these additional assumptions is constrained by actual events to which the counterfactual is taken to be counterfactual. In contrast, in basic conditional reasoning one enriches the given antecedent with any plausible assumptions, unconstrained by actual events. In our tasks basic conditional reasoning leads to different answers from counterfactual reasoning. For instance, a doctor, sitting in the park with the intention of reading a paper, is called to an emergency at the swimming pool. The question, “If there had been no emergency, where would the doctor be?” should counterfactually be answered “in the park”. But by ignoring the doctor's intentions, and just reasoning from premises about the default location of a hospital doctor who has not been called out to an emergency, one might answer: “in the hospital”. Only by 6 years of age did children mostly give correct answers.     

A Comparison of Multilevel Imputation Schemes for Random Coefficient Models: Fully Conditional Specification and Joint Model Imputation with Random Covariance Matrices

Abstract

Literature addressing missing data handling for random coefficient models is particularly scant, and the few studies to date have focused on the fully conditional specification framework and “reverse random coefficient” imputation. Although it has not received much attention in the literature, a joint modeling strategy that uses random within-cluster covariance matrices to preserve cluster-specific associations is a promising alternative for random coefficient analyses. This study is apparently the first to directly compare these procedures. Analytic results suggest that both imputation procedures can introduce bias-inducing incompatibilities with a random coefficient analysis model. Problems with fully conditional specification result from an incorrect distributional assumption, whereas joint imputation uses an underparameterized model that assumes uncorrelated intercepts and slopes. Monte Carlo simulations suggest that biases from these issues are tolerable if the missing data rate is 10% or lower and the sample is composed of at least 30 clusters with 15 observations per group. Furthermore, fully conditional specification tends to be superior with intraclass correlations that are typical of crosssectional data (e.g., ICC?=?.10), whereas the joint model is preferable with high values typical of longitudinal designs (e.g., ICC?=?.50).     

Reflections on stimulus control

The topic of stimulus control is too broad and complex to be traceable here. It would probably take a two-semester course to cover just the highlights of that field's evolution. The more restricted topic of equivalence relations has itself become so broad that even an introductory summary requires more time than we have available. An examination of relations between equivalence and the more general topic of stimulus control, however, may reveal characteristics of both the larger and the more limited field that have not been generally discussed. Consideration of these features may in turn foster future developments within each area. I speak, of course, about aspects of stimulus control that my own experiences have made salient to me; others would surely emphasize different characteristics of the field. It is my hope that cooperative interactions among researchers and theorists who approach stimulus control from different directions will become more common than is currently typical.     

Beyond Language: Using Logic to Introduce New Philosophical Distinctions

Philosophy has to be communicable in language, and therefore, whatever it has to say must be expressible in (some) language. But in order to make progress, philosophy has to gradually extend and improve its terminological apparatus. It is argued that logical formalization is a highly useful tool for discovering and confirming distinctions that are not present in ordinary language or in pre-existing philosophical terminology. In particular, it is proposed that if two usages of a word require different logical formalizations, then that is a strong reason to distinguish between them also in informal philosophy. The distinction between two types of normative conditionals, conditional veritable norms and conditional normative rules, is used as an example to corroborate this proposal.     

What is learned from experience in a probabilistic environment?

Three experiments explored what is learned from experience in a probabilistic environment. The task was a simulated medical decision‐making task with each patient having one of two test results and one of two diseases. The test result was highly predictive of the disease for all participants. The base rate of the test result was varied between participants to produce different inverse conditional probabilities of the test result given the disease across conditions. Participants trained using feedback to predict a patient's disease from a test result showed the classic confusion of the inverse error, substituting the forward conditional probability for the inverse conditional probability when tested on it. Additional training on the base rate of the test result did little to improve performance. Training on the joint probabilities, however, produced good performance on either conditional probability. The pattern of results demonstrated that experience with the environment is not always sufficient for good performance. That natural sampling leads to good performance was not supported. Further, because participants not trained on joint probabilities did, however, know them but still committed the confusion of the inverse error, the hypothesis that having joint probabilities would facilitate performance was not supported. The pattern of results supported the conclusion that people learn all the necessary information from experience in a probabilistic environment, but depending upon what the experience was, it may interfere with their ability to recall to memory the appropriate sample set necessary for estimating or using the inverse conditional probability. Copyright © 2004 John Wiley & Sons, Ltd.