“Know What to Do If You Encounter a Flash Flood”: Mental Models Analysis for Improving Flash Flood Risk Communication and Public Decision Making

Understanding how people view flash flood risks can help improve risk communication, ultimately improving outcomes. This article analyzes data from 26 mental models interviews about flash floods with members of the public in Boulder, Colorado, to understand their perspectives on flash flood risks and mitigation. The analysis includes a comparison between public and professional perspectives by referencing a companion mental models study of Boulder‐area professionals. A mental models approach can help to diagnose what people already know about flash flood risks and responses, as well as any critical gaps in their knowledge that might be addressed through improved risk communication. A few public interviewees mentioned most of the key concepts discussed by professionals as important for flash flood warning decision making. However, most interviewees exhibited some incomplete understandings and misconceptions about aspects of flash flood development and exposure, effects, or mitigation that may lead to ineffective warning decisions when a flash flood threatens. These include important misunderstandings about the rapid evolution of flash floods, the speed of water in flash floods, the locations and times that pose the greatest flash flood risk in Boulder, the value of situational awareness and environmental cues, and the most appropriate responses when a flash flood threatens. The findings point to recommendations for ways to improve risk communication, over the long term and when an event threatens, to help people quickly recognize and understand threats, obtain needed information, and make informed decisions in complex, rapidly evolving extreme weather events such as flash floods.     

THE IMPACT OF SCHOOL RACIAL COMPOSITIONS ON NEIGHBORHOOD RACIAL COMPOSITIONS: EVIDENCE FROM SCHOOL REDISTRICTING

I use data surrounding public school redistricting to study how school racial compositions affect neighborhood racial compositions. This redistricting followed from the end of court‐ordered busing for racial desegregation, significantly changing the racial composition of the assigned school for many neighborhoods. Over a 5‐year period, the impact of an increase in the percent black of the assigned elementary school on the percent black of the neighborhood was positive. The effects increased over time, consistent with a simple model of short‐run neighborhood racial dynamics. These results have implications for potential effects of school racial desegregation policy changes on neighborhood racial compositions. (JEL H75, I28, R23)     

Amplification of Sensitivity Analysis in Matched Observational Studies

A sensitivity analysis displays the increase in uncertainty that attends an inference when a key assumption is relaxed. In matched observational studies of treatment effects, a key assumption in some analyses is that subjects matched for observed covariates are comparable, and this assumption is relaxed by positing a relevant covariate that was not observed and not controlled by matching. What properties would such an unobserved covariate need to have to materially alter the inference about treatment effects? For ease of calculation and reporting, it is convenient that the sensitivity analysis be of low dimension, perhaps indexed by a scalar sensitivity parameter, but for interpretation in specific contexts, a higher dimensional analysis may be of greater relevance. An amplification of a sensitivity analysis is defined as a map from each point in a low dimensional sensitivity analysis to a set of points, perhaps a 'curve,' in a higher dimensional sensitivity analysis such that the possible inferences are the same for all points in the set. Possessing an amplification, an investigator may calculate and report the low dimensional analysis, yet have available the interpretations of the higher dimensional analysis.     

EFFECTS OF EXPOSURE ON PREVALENCE AND CUMULATIVE RELATIVE RISK: DIRECT AND INDIRECT EFFECTS IN A RECURSIVE HAZARD MODEL

This paper outlines decomposition methods for assessing how exposure affects prevalence and cumulative relative risk. Let     x     denote a vector of exogenous covariates and suppose that a single dimension of time   t   governs two event processes     T ₁  and   T ₂.    If the occurrence of the event     T ₁    determines entry into the risk of the event     T ₂,    then subgroup variation in     T ₁    will affect the prevalence     T ₂,    even if subgroups in the population are otherwise identical. Although researchers often acknowledge this phenomenon, the literature has not provided procedures to assess the magnitude of an exposure effect of     T ₁    on the prevalence of     T ₂.    We derive decompositions that assess how variation in exposure generated by direct and indirect effects of the covariates     x     affect measures of absolute and relative prevalence of     T ₂.    We employ a parametric but highly flexible specification for baseline hazard for the     T ₁  and   T ₂    processes and use the resulting parametric proportional hazard model to illustrate the direct and indirect effects of family structure when     T ₁    is age at first sexual intercourse and     T ₂    is age at a premarital first birth for data on a cohort of non-hispanic white U.S. women.     

Analyzing the Homeland Security of the U.S.-Mexico Border

We develop a mathematical optimization model at the intersection of homeland security and immigration, that chooses various immigration enforcement decision variables to minimize the probability that a terrorist can successfully enter the United States across the U.S.-Mexico border. Included are a discrete choice model for the probability that a potential alien crosser will attempt to cross the U.S.-Mexico border in terms of the likelihood of success and the U.S. wage for illegal workers, a spatial model that calculates the apprehension probability as a function of the number of crossers, the number of border patrol agents, and the amount of surveillance technology on the border, a queueing model that determines the probability that an apprehended alien will be detained and removed as a function of the number of detention beds, and an equilibrium model for the illegal wage that balances the supply and demand for work and incorporates the impact of worksite enforcement. Our main result is that detention beds are the current system bottleneck (even after the large reduction in detention residence times recently achieved by expedited removal), and increases in border patrol staffing or surveillance technology would not provide any improvements without a large increase in detention capacity. Our model also predicts that surveillance technology is more cost effective than border patrol agents, which in turn are more cost effective than worksite inspectors, but these results are not robust due to the difficulty of predicting human behavior from existing data. Overall, the probability that a terrorist can successfully enter the United States is very high, and it would be extremely costly and difficult to significantly reduce it. We also investigate the alternative objective function of minimizing the flow of illegal aliens across the U.S.-Mexico border, and obtain qualitatively similar results.     

Sick building syndrome and perceived indoor environmental quality: A survey of apartment buildings in Hong Kong

The outbreak of a highly communicable disease, SARS, in Asia in 2003 has revealed the health risk of living in a high-density environment. To show the important connection between human health and environmental quality, this study surveys the prevalence of sick building syndrome (SBS) among apartment residents and their evaluation of indoor environmental quality (IEQ). Based on a sample of 748 households living in Hong Kong, two interesting findings are revealed: (1) nasal discomfort was the commonest home-related SBS symptom despite the absence of any central ventilation system in apartment buildings; (2) noise, rather than ventilation, was the major IEQ problem perceived by residents. Our statistical analysis further showed that residents with SBS symptoms were less satisfied with their IEQ than those without. That is, despite a positive evaluation of specific IEQ criteria with respect to the building residents lived in, if they reported feeling SBS related symptoms, the overall IEQ evaluation of their building could still be negative. This perception bias gives rise to a sample selection problem in measuring perceived IEQ, which has implications on housing management practices and the formulation of a healthy housing policy.     

The Collapsing Choice Theory: Dissociating Choice and Judgment in Decision Making

Decision making theory in general, and mental models in particular, associate judgment and choice. Decision choice follows probability estimates and errors in choice derive mainly from errors in judgment. In the studies reported here we use the Monty Hall dilemma to illustrate that judgment and choice do not always go together, and that such a dissociation can lead to better decision-making. Specifically, we demonstrate that in certain decision problems, exceeding working memory limitations can actually improve decision choice. We show across four experiments that increasing the number of choice alternatives forces people to collapse choices together, resulting in better decision-making. While choice performance improves, probability judgments do not change, thus demonstrating an important dissociation between choice and probability judgments. We propose the Collapsing Choice Theory (CCT) which explains how working memory capacity, probability estimation, choice alternatives, judgment, and regret all interact and effect decision quality.      

Revisions of the Fish Invasiveness Screening Kit (FISK) for its Application in Warmer Climatic Zones,with Particular Reference to Peninsular Florida

The initial version (v1) of the Fish Invasiveness Scoring Kit (FISK) was adapted from the Weed Risk Assessment of Pheloung, Williams, and Halloy to assess the potential invasiveness of nonnative freshwater fishes in the United Kingdom. Published applications of FISK v1 have been primarily in temperate‐zone countries (Belgium, Belarus, and Japan), so the specificity of this screening tool to that climatic zone was not noted until attempts were made to apply it in peninsular Florida. To remedy this shortcoming, the questions and guidance notes of FISK v1 were reviewed and revised to improve clarity and extend its applicability to broader climatic regions, resulting in changes to 36 of the 49 questions. In addition, upgrades were made to the software architecture of FISK to improve overall computational speed as well as graphical user interface flexibility and friendliness. We demonstrate the process of screening a fish species using FISK v2 in a realistic management scenario by assessing the Barcoo grunter Scortum barcoo (Terapontidae), a species whose management concerns are related to its potential use for aquaponics in Florida. The FISK v2 screening of Barcoo grunter placed the species into the lower range of medium risk (score = 5), suggesting it is a permissible species for use in Florida under current nonnative species regulations. Screening of the Barcoo grunter illustrates the usefulness of FISK v2 as a proactive tool serving to inform risk management decisions, but the low level of confidence associated with the assessment highlighted a dearth of critical information on this species.