Uncertainty about the rest of the sentence

A word-by-word human sentence processing complexity metric is presented. This metric formalizes the intuition that comprehenders have more trouble on words contributing larger amounts of information about the syntactic structure of the sentence as a whole. The formalization is in terms of the conditional entropy of grammatical continuations, given the words that have been heard so far. To calculate the predictions of this metric, Wilson and Carroll's (1954) original entropy reduction idea is extended to infinite languages. This is demonstrated with a mildly context-sensitive language that includes relative clauses formed on a variety of grammatical relations across the Accessibility Hierarchy of Keenan and Comrie (1977). Predictions are derived that correlate significantly with repetition accuracy results obtained in a sentence-memory experiment (Keenan & Hawkins, 1987).     

Selecting the number of classes under latent class regression: a factor analytic analogue

Recently, the regression extension of latent class analysis (RLCA) model has received much attention in the field of medical research. The basic RLCA model summarizes shared features of measured multiple indicators as an underlying categorical variable and incorporates the covariate information in modeling both latent class membership and multiple indicators themselves. To reduce complexity and enhance interpretability, one usually fixes the number of classes in a given RLCA. Often, goodness of fit methods comparing various estimated models are used as a criterion to select the number of classes. In this paper, we propose a new method that is based on an analogous method used in factor analysis and does not require repeated fitting. Two ideas with application to many settings other than ours are synthesized in deriving the method: a connection between latent class models and factor analysis, and techniques of covariate marginalization and elimination. A Monte Carlo simulation study is presented to evaluate the behavior of the selection procedure and compare to alternative approaches. Data from a study of how measured visual impairments affect older persons’ functioning are used for illustration.This work was supported by National Institute on Aging (NIA) Program Project P01-AG-10184-03. The author wishes to thank Dr. Karen Bandeen-Roche for her stimulating comments and helpful discussions, and Drs. Gary Rubin and Sheila West for kindly making the Salisbury Eye Evaluation data available.     

The Enhanced Agentic Diversity Perspective (EADP): An appeal for Co-creating an accommodative social space so that diversity unlocks innovativeness rather than problems

We propose in this article an Enhanced Agentic Diversity Perspective (EADP), which is derived from the concept of agentic resources in social relational theory. EADP recognizes that all human beings are equally agents, that agentic expressions differ due to variation of individual access to power resources (individual, relational and cultural) and that the current social conditions serve to promote agentic diversity by enhancing all the three domains of power resources. In addition, EADP comprises a proposal for the development of accommodative social spaces. We argue that only in an accommodative social space can diversity unlock innovation; otherwise, it serves as a source for conflict. A constructive, nonhierarchical account of diversity, such as EADP is needed under current social conditions for the optimal becoming of idiosyncratic human agents as well as human society as a whole.     

TEACHING SELF-ADMINSTRATION OF NASOGASTRIC TUBE INSERTION TO AN ADOLESCENT WITH CROHN DISEASE

We examined the effectiveness of simulation training to teach an adolescent male with Crohn disease to self-administer nasogastric tube insertion. Nasogastric tube insertion was taught using simulation training, after which self-insertion skills were assessed. Results across skill components indicated that this subject was able to self-administer insertion of the nasogastric tube.     

Jury simulation studies: To exclude or not to exclude participants based on a lack of comprehension of the case?

Jury simulation research has been the subject of longstanding criticism in regards to ecological validity. One additional factor that has received little attention that may also impact the generalizability of this research relates to excluding participants based on their memory of, or their attention paid to, the case. In order to determine how common this exclusion is, the authors conducted a scoping review of jury simulation studies within the last 10 years across three major legal psychology journals. The review revealed variability in if and how studies excluded on the basis of poor attention or for failing manipulation or general memory checks. In addition, studies that did exclude on this basis varied greatly in the proportion of the sample that was excluded. Recommendations are provided in order to assist jury researchers in future with how best to manage exclusions on the basis of juror memory and attention.     

Using an AI creativity system to explore how aesthetic experiences are processed along the brain’s perceptual neural pathways

With the increased sophistication of AI techniques, the application of these systems has been expanding to ever newer fields. Increasingly, these systems are being used in modeling of human aesthetics and creativity, e.g. how humans create artworks and design products. Our lab has developed one such AI creativity deep learning system that can be used to create artworks in the form of images and videos. In this paper, we describe this system and its use in studying the human visual system and the formation of aesthetic experiences. Specifically, we show how time-based AI created media can be used to explore the nature of the dual-pathway neuro-architecture of the human visual system and how this relates to higher cognitive judgments such as aesthetic experiences that rely on these divergent information streams. We propose a theoretical framework for how the movement within percepts such as video clips, causes the engagement of reflexive attention and a subsequent focus on visual information that are primarily processed via the dorsal stream, thereby modulating aesthetic experiences that rely on information relayed via the ventral stream. We outline our recent study in support of our proposed framework, which serves as the first study that investigates the relationship between the two visual streams and aesthetic experiences.     

Dominance Measuring Method Performance under Incomplete Information about Weights

In multi‐attribute utility theory, it is often not easy to elicit precise values for the scaling weights representing the relative importance of criteria. A very widespread approach is to gather incomplete information. A recent approach for dealing with such situations is to use information about each alternative's intensity of dominance, known as dominance measuring methods. Different dominance measuring methods have been proposed, and simulation studies have been carried out to compare these methods with each other and with other approaches but only when ordinal information about weights is available. In this paper, we use Monte Carlo simulation techniques to analyse the performance of and adapt such methods to deal with weight intervals, weights fitting independent normal probability distributions or weights represented by fuzzy numbers. Moreover, dominance measuring method performance is also compared with a widely used methodology dealing with incomplete information on weights, the stochastic multicriteria acceptability analysis (SMAA). SMAA is based on exploring the weight space to describe the evaluations that would make each alternative the preferred one. Copyright © 2012 John Wiley & Sons, Ltd.     

Context effects in multi-alternative decision making: empirical data and a Bayesian model

For decisions between many alternatives, the benchmark result is Hick's Law: that response time increases log-linearly with the number of choice alternatives. Even when Hick's Law is observed for response times, divergent results have been observed for error rates-sometimes error rates increase with the number of choice alternatives, and sometimes they are constant. We provide evidence from two experiments that error rates are mostly independent of the number of choice alternatives, unless context effects induce participants to trade speed for accuracy across conditions. Error rate data have previously been used to discriminate between competing theoretical accounts of Hick's Law, and our results question the validity of those conclusions. We show that a previously dismissed optimal observer model might provide a parsimonious account of both response time and error rate data. The model suggests that people approximate Bayesian inference in multi-alternative choice, except for some perceptual limitations.