In this paper, we explore a pattern of individual differences in performance on judgment tasks. One hundred participants completed a battery of standard judgment tasks, including multiple cue judgment and tasks based on the “heuristics and biases” and problem‐solving literature. Participants also completed tests of fluid and crystallized intelligence, forward digit span memory, and multiple cue probability learning. Confirmatory factor analyses indicated a two‐factor structure underlying performance on these tasks and tests. The two moderately correlated factors reflected a distinction between tasks requiring accurate judgments based on multiple cues (correspondence tasks) and those requiring coherent judgments (coherence tasks), in which probabilities are compared and combined. Measures of fluid and crystallized intelligence and forward digit span memory were correlated with both factors but were more associated with correspondence than with coherence. Copyright © 2011 John Wiley & Sons, Ltd.

When policy-makers use a test result with a cut-off score in a decision, the cut-off threshold may change over time. An example is the threshold of "reasonable suspicion" used to justify a police search. Hammond (1996) postulated that a decision threshold will oscillate over time in response to competing pressures from affected constituencies, as unavoidable cases of false positives (e.g., innocent people searched) and false negatives (e.g., guilty people overlooked) emerge from the uncertainty of using an imperfect test (e.g., level of evidence) to predict the actual measure of interest (e.g., guilt). The structural underpinnings of a cycling threshold are analyzed in this theory-building article. First, we present a simplified converging model of Hammond's initial insight. Then, we present three alternative models: a model with delays in policy-maker responsiveness; one with stakeholders' shifting constituencies in response to recent errors; and one with integral control representing the historical dissatisfaction of competing constituencies. The "history" model meets the theoretical requirements set out by Hammond and fits historical data regarding FBI denials of access to information regarding a third party due to privacy concerns.

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ARI has been investigating the potential that non-cognitive predictors could play in expanding the supply of highly-motivated AFQT test score category (TSC) 3B applicants. The initial research effort was known as the Expanded Enlistment Eligibility Metrics (EEEM) project, and preliminary results were encouraging: non-cognitive predictors have been tested that appear to identify a subset of TSC 3B applicants with predicted attrition (and possibly job performance) comparable to that of TSC 1-3A applicants. One concern regarding the implementation of these new predictors is whether an increase in TSC 3B applicants and a corresponding decrease in TSC 1-3A applicants would have repercussions for Army MOS TSC 1-3A goals. The objective of this effort is to estimate the effect of illustrative increases in the number of TSC 3B applicants on the allocation of applicants to their initial MOS training. The objectives were addressed with application of the Enlisted Personnel Allocation System (EPAS) model, designed to simulate the allocation / classification process. 15. SUBJECT TERMS enlisted selection and classification, Enlisted Personnel Allocation System (EPAS), non-cognitive predictors, Soldier Quality Accession Goals SECURITY CLASSIFICATION OF 19. LIMITATION OF ABSTRACT 20. NUMBER OF PAGES