Subvocal motor activity and contextual processing

Twenty male and female subjects listened for mispronounced words while minimizing either subvocal or frontalis electromyographic activity. Stimuli were varied on size of the distortion, lexical constraint, and contextual constraint, all known to influence detections. Analysis of both the reaction time and detection data indicated that the minimization of subvocal EMG activity reduced or eliminated the effect of contextual constraint, while minimization of frontalis EMG activity resulted in the typically observed contextual constraint effect. Results indicate that subvocal activity is related to contextual processing. Additionally, reaction time data are reported that indicate that although low contextual constraint greatly slows the decision process, detectability is actually superior. A possible underlying mechanism for this reversal of the speed-accuracy trade-off is discussed.This article is partially based on the first author's Wayne State University doctoral dissertation. Special thanks go to Cathy Gross Ward, Cris Foster, and Bob Beattie for their valuable assistance during the collection of data. A preliminary version of this paper was presented at the Eastern Psychological Association meeting in Baltimore, 1982.     

Arguing for a New Form of Taxation: Lifetime Hourly Averaging

This article presents an argument for a new form of tax calculation. Firstly it is argued that Hypothetical Insurance is the best method to determine the correct type of distributive policies and the precise amounts that should be redistributed. Hourly averaging is then presented as a new candidate policy for both assisting the less economically fortunate and taxing the more economically fortunate. The article then argues that hourly averaging compares favourably against rival policies as a hypothetical insurance choice.     

Constraints and Preferences in Inductive Learning: An Experimental Study of Human and Machine Performance

The paper examines constraints and preferences employed by people in learning decision rules from preclassified examples. Results from four experiments with human subjects were analyzed and compared with artificial intelligence (AI) inductive learning programs. The results showed the people's rule inductions tended to emphasize category validity (probability of some property, given a category) more than cue validity (probability that an entity is a member of a category given that it has some property) to a greater extent than did the AI programs. Although the relative proportions of different rule types (e.g., conjunctive vs. disjunctive) changed across experiments, a single process model provided a good account of the data from each study. These observations are used to argue for describing constraints in terms of processes embodied in models rather than in terms of products or outputs. Thus AI induction programs become candidate psychological process models and results from inductive learning experiments can suggest new algorithms. More generally, the results show that human inductive generalizations tend toward greater specificity than would be expected if conceptual simplicity were the key constraint on inductions. This bias toward specificity may be due to the fact that this criterion both maximizes inferences that may be drawn from category membership and protects rule induction systems from developing over-generalizations.     

Maximalism versus Omnism about Permissibility

Roughly speaking, maximalism is the view that only certain options are to be assessed in terms of whether they have some right‐making property (such as that of producing optimal consequences), whereas omnism is the view that all options are to be assessed in terms of whether they have this property. I argue that maximalism is preferable to omnism because it provides a more plausible solution to what's known as the problem of act versions and is not subject to any significant problems of its own. If I'm right, then most moral theories, which are versions of omnism, need revision.     

Retrieval dynamics in recognition and list discrimination: Further evidence of separate processes of familiarity and recall

Two experiments tested the hypothesis that the time course of retrieval from memory is different for familiarity and recall. The response-signal method was used to compare memory retrieval dynamics in yes-no recognition memory, as a measure of familiarity, with those of list discrimination, as a measure of contextual recall. Responses were always made with regard to membership in two previous study lists. In Experiment 1 an exclusion task requiring positive responses to words from one list and negative responses to new words and words from the nontarget list was used. In Experiment 2, recognition and list discrimination were separate tasks. Retrieval curves from both experiments were consistent, showing that the minimal retrieval time for recognition was about 100 msec faster than that for list discrimination. Repetition affected asymptotic performance but had no reliable effects on retrieval dynamics in either the recognition or the list-discrimination task.