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Multiplex Network Analysis for Complex Governance Systems Using Surveys and Online Behavior.

Published in Policy Studies Journal, 2018

Research in complex governance systems has long been constrained by the limitations of surveys as a source of relational data. We investigate the extent to which passively-collected online data can replicate the inferences based on survey network data. We compare a survey-based measure of an environmental governance network to two web-based measures of the network: Twitter and hyperlink network data using correlations calculated using quadratic assignment procedure and exponential random graph models. We find a statistically significant but fairly weak correlation among the network measuers. There are broad similarities in tie-formation patterns across network measures, but several important instances of divergence as well.

Recommended citation: Hayes, A.L., & Scott, T.A. (2018). "Multiplex Network Analysis for Complex Governance Systems Using Surveys and Online Behavior." Policy Studies Journal, 46(2), 327-353. https://doi.org/10.1111/psj.12210

The role of scientific expertise in local adaptation to projected sea level rise

Published in Environmental Science & Policy, 2018

We survey city and town government officials and department heads to determine the prevalence of sea level rise (SLR) planning at the local level, the extent to which scientists are involved in the planning process, and perceptions about effective expert involvement. We find that planning is widespread (47 of 71 surveyed governments) and expert knowledge is generally utilized (38 of 47 local governments). Our results indicate expert input is most effective when experts make scientific information more accessible. Expertise coming from academic or government organizations beyond the local government are underutilized relative to reported needs, suggesting potential gains from additional knowledge-sharing.

Recommended citation: Hayes, A. L., Heery, E. C., Maroon, E., McLaskey, A. K., & Stawitz, C. C. (2018). "The role of scientific expertise in local adaptation to projected sea level rise." Environmental Science & Policy, 87, 55-63. https://doi.org/10.1016/j.envsci.2018.05.012

Efficacy, Action, and Support for Reducing Climate Change Risks

Published in Risk Analysis: An International Journal, 2018

We estimate the relationship between efficacy perception, climate change concern, and climate change mitigation policy support using both an MTurk sample and a nationally-representative sample. Previous literature has been ambiguous in defining efficacy. We find two key efficacy dimensions: self efficacy (how easy something is to accomplish) and response efficacy (how effective an action is) as well as two key actor levels: personal and government/collective. Perceived government and collective response efficacy is the strongest predictor of climate change policy support, though personal self efficacy is also positively associated with policy support.

Recommended citation: Bostrom, A., Hayes, A.L., & Crosman, K.M. (in press). "Efficacy, Action, and Support for Reducing Climate Change Risks.." Risk Analysis. https://doi.org/10.1111/risa.13210

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teaching

Quantitative Analysis I (Teaching Assistant)

M.P.A. Course, University of Washington, Evans School, 2017

The first course in a two-course quantitative methods sequence that each Masters of Public Affairs student at the University of Washington’s Evans School is required to take. Because no previous statistics or programming experience is required this course introduces students to concepts in probability and descriptive summary statistics that will then be used in the following course as well as an introduction to statistical programming.

Quantitative Analysis II (Teaching Assistant)

M.P.A. Course, University of Washington, Evans School, 2017

The second course in a two-course quantitative methods sequence that each Masters of Public Affairs student at the University of Washington’s Evans School is required to take. Students come from diverse academic backgrounds with a wide range of previous quantitative analysis experience. This course is designed to give students practice in conducting quantitative analysis and to help them become critical consumers of quantitative analyses produced by others.