Proposed wildfire legislation in California, 2001-2020

Published: 28 September 2021| Version 1 | DOI: 10.17632/dhbgkvn5f6.1
Rebecca Miller


File includes wildfire-related bill and associated legislator, legislative process, and bill intent data from California between the 2001-2002 and 2019-2020 legislative sessions. Bill topics stem from a Latent Dirichlet Allocation (LDA) topic model using summary bill text from 294 wildfire-related bills identified by keywords and assessed for relevance from the California State Legislature. To determine whether wildfire bills overall or those in a particular topic were associated with groups of characteristics related to legislators, legislative processes, and bill text, we use logistic and linear regression, as appropriate. We repeat this logistic regression approach nine times for (1) bill outcome (i.e., pass, fail, or veto); (2) legislators (political party, originating house, co-sponsors, bipartisan sponsorship, gender, rural or not rural, and recent wildfire or no recent wildfire); (3) review by appropriations committee, (4) urgency measures, (5) state mandates, (6) wildfire cycle stage (mitigation, preparedness, response, relief, recovery, smoke); (7) holiday focus; (8) vulnerable or disadvantaged population focus; and (9) geographic focus. We use linear regression to examine non-binary data, specifically for (1) legislators (i.e., number of sessions served, number of wildfire bills proposed that session) and (2) legislative processes (how many committees reviewed the bill). These statistical analyses determined whether bills were more or less likely to have certain legislator, legislative process, and bill text characteristics.



Stanford University


Environmental Legislation