Thomas R. Stewart

IPS pini: The basis for interpopulational differences in pheromone biology

Ips pini from Idaho (ID) produce (−)-ipsdienol and respond to it in the laboratory.I. pini from New York (NY) produce (+) and (−)-ipsdienol in a 65∶35 ratio and respond much more strongly to the (+) than to the (−) enantiomer. Response byI. pini-ID to (−)-ipsdienol in the laboratory was inhibited by (+)-ipsdienol, while the field response byI. pini-NY was optimal to a 50:50 mixture of (+) and (−)-ipsdienol. This differential production and response to enantiomers of ipsdienol is sufficient to account for populational specificity observed in earlier experiments and confirmed by our current work. Reciprocal hybrids of the NY and IDI. pini populations did not differ in their patterns of attraction and response; those of both types of F1 were similar to NY beetles. Thus, it appears that (+)-ipsdienol is produced by the hybrids and is necessary for their maximum response, but this supposition was not tested. The genes controlling the pheromone biology ofI. pini are not sex linked. Since previous whole-antenna and single-cell electrophysiological data show that the receptor systems of the two populations are virtually identical, response behavior seems to be governed by the central nervous system rather than by the characteristics of the olfactory receptors.

A comparison of seven methods for obtaining subjective descriptions of judgmental policy

Abstract When subjective descriptions of judgmental policies have been compared to statistical descriptions of policies, investigators have repeatedly found an imperfect correspondence between subjective and statistical measures of importance. There is reason to believe, however, that these findings may be due to the use of inadequate procedures for obtaining subjective weights. The present study, therefore, compared seven methods for obtaining subjective descriptions of cue importance. Subjective policy descriptions were found to correspond reasonably well to statistical policy descriptions for both a three-cue and a seven-cue task, but the seven methods did not differ. All methods yielded more accurate predictions of actual judgments than an arbitrary policy of equal weights on all cues.

Chapter 2 Judgment Analysis: Procedures*

Publisher Summary This chapter highlights judgment analysis (JA). It describes the steps necessary to apply JA and provide guidelines for making the numerous decisions required for a successful application. JA is also known as “policy capturing,” and is a research method that has been used in hundreds of studies of judgment and decision making including studies of multiple cue probability learning, interpersonal learning, conflict, and expert judgment. It has been found useful as an aid to judgment, particularly in cases involving conflict about technical and political issues. The goal of JA is to describe, quantitatively, the relations between someones judgment and the information, or “cues,” used to make that judgment. JA has also often been used to study judgment on unfamiliar tasks. For judgment analysis, as for all formal analytic methods, proper formulation of the problem is critical to success of the analysis. Designing the judgment task includes (1) defining the judgment of interest, (2) identifying the cues, (3) describing the context for judgment, (4) defining the distributions of the cue values, and (5) defining relations among the cues.

Judgments of photographs vs. field observations in studies of perception and judgment of the visual environment

Abstract The use of photographs as surrogates for field observations is common in studies of perception and judgment of the visual environment despite theoretically important differences between photographs and three-dimensional scenes. The few available empirical studies of the validity of photographs as representations of the visual environment have methodological weaknesses. We describe a method for investigating the representativeness of photographs that differs from previous approaches in three important respects. First, individual subjects rather than group averages are analyzed. Second, multiple judgments are obtained so that the relations among judgments of photographs can be compared with the environment. Third, a ‘lens model equation’ analysis is used to examine relations among systematic components of variation in judgments. An illustrative study of visual air quality judgments is presented. It was found that, in the case of judgments of visual air quality, photographs provide a good representation of the visual environment.

Improving Reliability of Judgmental Forecasts

All judgmental forecasts will be affected by the inherent unreliability, or inconsistency, of the judgment process. Psychologists have studied this problem extensively, but forecasters rarely address it. Researchers and theorists describe two types of unreliability that can reduce the accuracy of judgmental forecasts: (1) unreliability of information acquisition, and (2) unreliability of information processing. Studies indicate that judgments are less reliable when the task is more complex; when the environment is more uncertain; when the acquisition of information relies on perception, pattern recognition, or memory; and when people use intuition instead of analysis. Five principles can improve reliability in judgmental forecasting: 1. Organize and present information in a form that clearly emphasizes relevant information. 2. Limit the amount of information used in judgmental forecasting. Use a small number of really important cues. 3. Use mechanical methods to process information. 4. Combine several forecasts. 5. Require justification of forecasts.

Effects of improved information on the components of skill in weather forecasting

Abstract The relation between the amount and quality of information available to meteorologists and the accuracy of their forecasts of a highly uncertain event (severe weather) was investigated. In three studies, meteorologists made forecasts under a total of four different information conditions. Forecast accuracy was low, and as the amount and quality of the information increased substantially, there was a modest increase in the accuracy of forecasts. The results suggest that subjective factors, particularly the reliability of forecasts, deteriorated with additional information.

Aging and multiple cue probability learning: the case of inverse relationships.

Multiple Cue Probability Learning (MCPL) is an important cognitive ability for all age groups that, like other cognitive abilities, depends on information processing speed and working memory capacity--skills that have been found to decline with age. The relation between age and ability to learn direct and inverse probabilistic relationships was studied in two MCPL experiments involving subjects in three age groups. In the first experiment, subjects learned two three-cue tasks following the MCPL paradigm. In the first task, all cues had a direct relation (DR) with the criterion. In the second, one cue had an inverse relation (IR) with the criterion. In the DR task, older subjects were able to learn nearly as well as younger subjects. In the IR task, older subjects performed significantly worse than younger subjects due to an inability to use the inverse cue. In a second experiment involving the IR task, task information (TI) was given, that is, the relation between each cue and the criterion was explicitly described. This eliminated the need for subjects to discover the inverse relation on their own, thus reducing the burden on working memory. Provision of TI resulted in improved performance for the 20-30 and 65-75 year old groups, but not in the 76-90 year old group. Significant differences in performance among age groups remained. These results cannot be fully explained by differences in working memory capacity. It is suggested that flexibility of functioning also plays a role.

Expert Judgement and Expert Disagreement

As Hammond has argued, traditional explanations for disagreement among experts (incompetence, venality, and ideology) are inadequate. The character and fallibilities of the human judgement process itself lead to persistent disagreements even among competent, honest, and disinterested experts. Social Judgement Theory provides powerful methods for analysing such judgementally based disagreements when the experts’ judgement processes can be represented by additive models involving the same cues. However, the validity and usefulness of such representations depend on several conditions: (a) experts must agree on a problem definition, (b) experts must have access to the same information, and (c) experts must use the same organising principles. When these conditions are not met, methods for diagnosing and treating disagreement are poorly understood. As a start towards developing such an understanding, sources of expert disagreement are discussed and categorised.

A behavioral theory of insider-threat risks: A system dynamics approach

The authors describe a behavioral theory of the dynamics of insider-threat risks. Drawing on data related to information technology security violations and on a case study created to explain the dynamics observed in that data, the authors constructed a system dynamics model of a theory of the development of insider-threat risks and conducted numerical simulations to explore the parameter and response spaces of the model. By examining several scenarios in which attention to events, increased judging capabilities, better information, and training activities are simulated, the authors theorize about why information technology security effectiveness changes over time. The simulation results argue against the common presumption that increased security comes at the cost of reduced production.

A Decomposition of the Correlation Coefficient and its Use in Analyzing Forecasting Skill

Abstract Estimates of several components of forecasting skill can be obtained by combining a skill-score decomposition developed by Allan Murphy with techniques for decomposing correlation coefficients that have been employed in research on human judgment. The decomposition of the correlation coefficient requires knowledge of the information or “cues” used by the forecaster. When the cues are known, it is possible to estimate the effects of uncertainty and the forecasters consistency and use of the cues.