Arnold Vedlitz

Personal efficacy, the information environment, and attitudes toward global warming and climate change in the United States.

Despite the growing scientific consensus about the risks of global warming and climate change, the mass media frequently portray the subject as one of great scientific controversy and debate. And yet previous studies of the mass publics subjective assessments of the risks of global warming and climate change have not sufficiently examined public informedness, public confidence in climate scientists, and the role of personal efficacy in affecting global warming outcomes. By examining the results of a survey on an original and representative sample of Americans, we find that these three forces-informedness, confidence in scientists, and personal efficacy-are related in interesting and unexpected ways, and exert significant influence on risk assessments of global warming and climate change. In particular, more informed respondents both feel less personally responsible for global warming, and also show less concern for global warming. We also find that confidence in scientists has unexpected effects: respondents with high confidence in scientists feel less responsible for global warming, and also show less concern for global warming. These results have substantial implications for the interaction between scientists and the public in general, and for the public discussion of global warming and climate change in particular.

Race, Ethnicity, and Political Participation: Competing Models and Contrasting Explanations

While various models have been developed to account for differences in participation levels between African-Americans and Anglos, the empirical evidence for these models is rather limited; fails to include ethnic minority groups other than African-Americans; and assumes that the models are equally effective in explaining the behavior of all individuals regardless of race or ethnicity. This paper addresses these limitations by evaluating five models of participation to determine whether factors associated with Anglo and African-American participation are also associated with Mexican-American and Asian-American participation. We find that although the models apply differentially to each of the four groups, they nonetheless account for participation differences across racial/ethnic groups.

Vulnerability and Capacity: Explaining Local Commitment to Climate-Change Policy

We examine the reasons why a US locality would voluntarily commit to the Cities for Climate Protection (CCP) campaign. Using geographic information systems analytic techniques, we map and measure a localitys vulnerability to climate-change impacts at the county level of spatial precision. We analyze multiple measures of climate-change vulnerability, including expected temperature change, extreme weather events, and coastal proximity, as well as economic variables, demographic variables, and civic-participation variables that constitute a localitys socioeconomic capacity to commit to costly climate-change policy initiatives. Bivariate and logistic regression results indicate that CCP-committed localities are quantitatively different to noncommitted localities on both climate-change risk and socioeconomic-capacity dimensions. On vulnerability measures, the odds of CCP-campaign participation increase significantly with the number of people killed and injured by extreme weather events, projected temperature change, and coastal proximity. On socioeconomic-capacity measures, the odds of CCP-campaign involvement increase with the percentage of citizens that vote Democrat and recycle, as well as the number of nonprofit organizations with an environment focus. The odds decrease in a county area as the percentage of the labor force employed in carbon-intensive industries increases.

Risk, Stress, and Capacity: Explaining Metropolitan Commitment to Climate Protection

Climate change and mitigation policies adopted by a locality indelibly impact urban form, landscape, and economy. The Cities for Climate Protection (CCP) has become a dominant movement organizing the localities to proactively address climate change. This study examines metropolitan area commitment to the CCP. Geographic information systems (GIS) and statistical techniques are used to analyze metros on dimensions of climate change risk, stress, and civic capacity. “Climate change risk” measures a metro areas coastal proximity, ecosystem sensitivity, and susceptibility to extreme weather events. “Climate change stress” summarizes transportation, energy, and production practices that adversely affect climate systems. “Civic capacity” estimates human capital and environmental concern variables that constitute a metro areas ability to commit to policy initiatives. Statistical results indicate that high stressor areas are significantly less likely to participate in the CCP campaign, and metros high in civic capacity are significantly more likely to commit to the CCP campaign.

Social vulnerability and the natural and built environment: a model of flood casualties in Texas

Studies on the impacts of hurricanes, tropical storms, and tornados indicate that poor communities of colour suffer disproportionately in human death and injury.(2) Few quantitative studies have been conducted on the degree to which flood events affect socially vulnerable populations. We address this research void by analysing 832 countywide flood events in Texas from 1997-2001. Specifically, we examine whether geographic localities characterised by high percentages of socially vulnerable populations experience significantly more casualties due to flood events, adjusting for characteristics of the natural and built environment. Zero-inflated negative binomial regression models indicate that the odds of a flood casualty increase with the level of precipitation on the day of a flood event, flood duration, property damage caused by the flood, population density, and the presence of socially vulnerable populations. Odds decrease with the number of dams, the level of precipitation on the day before a recorded flood event, and the extent to which localities have enacted flood mitigation strategies. The study concludes with comments on hazard-resilient communities and protection of casualty-prone populations.

Can We Generalize from Student Experiments to the Real World in Political Science, Military Affairs, and International Relations?

The authors conducted an experiment with a group of military officers and replicated it with a group of students at a public university in the United States. The experimental scenario dealt with a decision problem in the area of counterterrorism. The authors found that while more than one-third of students recommended doing nothing, the overwhelming majority of military officers (more than 90 percent) recommended doing something. Also, military officers exhibited less maximizing and more satisfacing decision making than students. The results show that relying on experiments with students “playing” the role of real-world national security policy makers may bias the results. The two groups are, in fact, very different. Based on student samples, it is possible to accept propositions that would not be found with samples of elite decision makers and reject propositions that may be right. However, it is possible that students can be assigned to experiments where they represent the “public” and not elites.

Collective Action, Environmental Activism, and Air Quality Policy

This article attempts to respond to Ostrom’s call for a behavioral model of collective action by generalizing the collective interest model of mass political action to explain citizen policy support and personal behavioral intentions in the context of air quality policy. The collective action problems inherent in air quality policy provide a critical research setting for testing hypotheses of the collective interest model. Key elements of the collective interest model—perceived risk, trust in policy elites, knowledge of the policy problem, and efficacy—are found to be directly, and positively, related to support of government policies and intentions to engage in personal behaviors that might improve air quality. The article discusses the implications for using the collective interest model as general behavioral theory of collective action.

Explaining Media and Congressional Attention to Global Climate Change, 1969-2005: An Empirical Test of Agenda-Setting Theory

Agenda theories suggest that problem indicator, focusing event, and information feedback enhance issue attention. However, few studies have systematically tested this. This study, using time series data and vector autoregression (VAR), examines how climate problem indicator, high-profile international event, and climate science feedback influence media and congressional attention to global warming and climate change. The findings confirm that these attention-grabbing factors indeed generally promote issue salience, but these factors may work differently across agenda venues. Attention inertia, interagenda interaction, and partisan advantage on agenda setting are also included and analyzed in the VAR modeling. Implications of the study and recommendations for future research are discussed in conclusion.

Identifying the impact of the built environment on flood damage in Texas

Floods continue to pose the greatest threat to the property and safety of human communities among all natural hazards in the United States. This study examines the relationship between the built environment and flood impacts in Texas, which consistently sustains the most damage from flooding of any other state in the country. Specifically, we calculate property damage resulting from 423 flood events between 1997 and 2001 at the county level. We identify the effect of several built environment measures, including wetland alteration, impervious surface, and dams on reported property damage while controlling for biophysical and socio-economic characteristics. Statistical results suggest that naturally occurring wetlands play a particularly important role in mitigating flood damage. These findings provide guidance to planners and flood managers on how to alleviate most effectively the costly impacts of foods at the community level.

Policy Learning for Flood Mitigation: A Longitudinal Assessment of the Community Rating System in Florida

Floods continue to inflict the most damage upon human communities among all natural hazards in the United States. Because localized flooding tends to be spatially repetitive over time, local decisionmakers often have an opportunity to learn from previous events and make proactive policy adjustments to reduce the adverse effects of a subsequent storm. Despite the importance of understanding the degree to which local jurisdictions learn from flood risks and under what circumstances, little if any empirical, longitudinal research has been conducted along these lines. This article addresses the research gap by examining the change in local flood mitigation policies in Florida from 1999 to 2005. We track 18 different mitigation activities organized into four series of activities under the Federal Emergency Management Agencys (FEMA) Community Rating System (CRS) for every local jurisdiction in Florida participating in the FEMA program on a yearly time step. We then identify the major factors contributing to policy changes based on CRS scores over the seven-year study period. Using multivariate statistical models to analyze both natural and social science data, we isolate the effects of several variables categorized into the following groups: hydrologic conditions, flood disaster history, socioeconomic and human capital controls. Results indicate that local jurisdictions do in fact learn from histories of flood risk and this process is expedited under specific conditions.