Californians Weigh in on PG&E, Wildfires, and Shutoffs
Change Research California Poll: October 15-October 18, 2019
Key Takeaways:
Californians have lost faith in large, Wall Street-driven publicly traded companies to put people first. The plurality of Californians (40%) want the basics — light, power and public safety — to be managed by smaller, regional utilities that will prioritize community interest over investor interest.
Voters don’t believe in the large utilities’ ability to handle future blackouts. Just 32% believe that utilities know best and should retain autonomy. An equal share believe state regulators should have that power when these outages occur. Another 33% are not sure.
Sample and Methodology _ California 10_1
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Management of wildfire season and the shut downs is clearly dragging down elected officials with only 47% of Californians disapproving of Governor Gavin Newsom’s handling the electrical shutdowns, though his numbers were better than “local elected officials” who came in at 52%.
When asked what they would like to happen if similar levels of fire danger were to occur, 55% of respondents would be willing to lose power for several days, while 18% of respondents would rather risk a wildfire. 27% of respondents said they were unsure. Republicans were more likely to be willing to risk a wildfire, with 32% of Republicans saying that they would rather risk a wildfire, while only 11% of Democrats and 17% of Independents said that they would rather take the risk.
PG&E had a 49% unfavorable rating when we started polling in California in February of this year. 8 months later that has risen to 61% unfavorable. Just 9% rate them favorably. This rejection of PG&E transcends party – 59% unfavorable with Democrats, 65% with Independents, and 61% with Democrats.
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Change Research surveyed 2,605 likely general election voters in California. The margin of error as traditionally calculated is ± 1.9% for the full sample. Change Research reaches voters via targeted online ads that point people to an online survey instrument. Our Bias Correct Engine dynamically delivers large samples that accurately reflect the demographics of a population. Post-stratification was done on age, gender, ethnicity, region, 2016 primary and presidential vote, and self-reported social media use.