2. Models Presented

ABSTRACT This chapter introduces the two theoretical models to be applied to qualitative and quantitative data in the case study of Dodge Morgan. We present the five-factor model (FFM) and the life-story model (LSM) separately, with attention to their differing origins, assumptions, and utilities. We briefly trace the development and resurgence of the factor-analytic FFM and delineate the extent of its current influence in the field of personality. We discuss individual factors and consider the ways in which the model can be expected to be useful as well as limited in application to the individual. We next present the genealogy of the narrative, constructivist LSM and describe its components; we also discuss its contrasting strengths and limitations.     

6. The Life Voyage

ABSTRACT Chapter 6 applies the five-factor model and the life-story model as complementary perspectives to the multiple data sources collected for the case study of Dodge Morgan. We integrate the two models to create a new level of analysis that captures differing aspects of experience. We develop a holistic personality analysis of Morgan, interpreting his childhood, young manhood, adventures in Alaska and on the boat Coaster, his return to the mainland and embrace of business and entrepreneurship, and his solo circumnavigation. We address questions of voyage outcomes with reference to the quantitative analyses of his voyage log; we consider not only the external journey but also his internal psychological issues and developmental tasks.     

Comparing Locomotion With Lever-press Travel In An Operant Simulation Of Foraging

An operant model of foraging was studied. Rats searched for food by pressing on the left lever, the patch, which provided one, two, or eight reinforcers before extinction (i.e., zero reinforcers). Obtaining each reinforcer lowered the probability of receiving another reinforcer, simulating patch depletion. Rats traveled to another patch by pressing the right lever, which restored reinforcer availability to the left lever. Travel requirement changed by varying the probability of reset for presses on the right lever; in one condition, additional locomotion was required. That is, rats ran 260 cm from the left to the right lever, made one response on the right lever, and ran back to a fresh patch on the left lever. Another condition added three hurdles to the 260-cm path. The lever-pressing and simple locomotion conditions generated equivalent travel times. Adding the hurdles produced longer times in patches than did the lever-pressing and simple locomotion requirements. The results contradict some models of optimal foraging but are in keeping with McNair's (1982) optimal giving-up time model and add to the growing body of evidence that different environments may produce different foraging strategies.     

Stochastic ordering using the latent trait and the sum score in polytomous IRT models

In a restricted class of item response theory (IRT) models for polytomous items the unweighted total score has monotone likelihood ratio (MLR) in the latent trait. MLR implies two stochastic ordering (SO) properties, denoted SOM and SOL, which are both weaker than MLR, but very useful for measurement with IRT models. Therefore, these SO properties are investigated for a broader class of IRT models for which the MLR property does not hold.In this study, first a taxonomy is given for nonparametric and parametric models for polytomous items based on the hierarchical relationship between the models. Next, it is investigated which models have the MLR property and which have the SO properties. It is shown that all models in the taxonomy possess the SOM property. However, counterexamples illustrate that many models do not, in general, possess the even more useful SOL property.Hemker's research was supported by the Netherlands Research Council, Grant 575-67-034. Junker's research was supported in part by the National Institutes of Health, Grant CA54852, and by the National Science Foundation, Grant DMS-94.04438.     

CONTRACTUALISM AND ANIMALS

Philosophical Studies -     

Need probability affects retention: A direct demonstration

Recent memory theory has emphasized the concept ofneed probability—that is, the probability that a given piece of learned information will be tested at some point in the future. It has been proposed that, in real-world situations, need probability declines over time and that the memory-loss rate is calibrated to match the progressive reduction in need probability (J. R. Anderson & Schooler, 1991). The present experiments were designed to examine the influence of the slope of the need-probability curve on the slope of the retention curve. On each of several trials, subjects memorized a list of digits, then retained the digits in memory for 1, 2, 4, 8, or 16 sec. Some trials ended with a recall test; other trials ended with the message, “no test.” In Experiment 1, the likelihood of encountering a memory test (i.e., the need probability) was made to either increase or decrease as the retention interval increased; in Experiment 2, need probability either was flat (invariant across retention intervals) or decreased as the retention interval increased. The results indicated that the shape of the need-probability curve influenced the slope of the retention curve (Experiment 1) and that the effect became larger as the experimental session progressed (Experiment 2). The findings support the notion that memory adapts to need probabilities and that the rate of forgetting is influenced by the slope of the need-probability curve. In addition, all of the forgetting curves approximated a power function, suggesting that need probability influences the slope but not the form of forgetting.