Framing Environmental Disaster: Environmental Advocacy and the Deepwater Horizon Oil Spill by Melissa K. Merry

Author:Melissa K. Merry [Merry, Melissa K.]
Language: eng
Format: epub
Tags: Public Policy, Social Science, Infrastructure, Political Science, Business & Economics, Environmental Policy, General
ISBN: 9781138194526
Google: QhcmjgEACAAJ
Goodreads: 26724062
Publisher: Routledge
Published: 2013-01-01T00:00:00+00:00

Relationship between Blame and Solutions

To investigate H5, it is instructive to look at Models 1 (Renewables) and 2 (Ban Drilling) in Table 4.1; these are the two leading solutions, for which I expect blame directed at America’s oil addiction and at oil companies generally to be strong predictors. As expected, the largest coefficient in the renewable energy model is “Blame Oil Addiction.” Taking the exponent of the coefficient (3.334), we see that the odds ratio for this variable is 28. In other words, the model estimates that the odds of mentioning renewable energy are 28 times higher in a communication that blames America’s addiction to oil than in one that does not blame this target. Likewise, the coefficient for oil companies is also significant, though the magnitude of the effect is less, with the odds of a communication mentioning renewable energy estimated at two times higher when oil companies are blamed than when they are not. Finally, blame directed at Congress was also a significant predictor for mentioning renewable energy. While Congress was not a prominent target in groups’ communications about the Gulf oil spill (seen in just 7.9 percent of communications), environmental groups had previously been frustrated with the lack of action in Congress on clean energy and climate change legislation. Thus, it makes sense that they would also blame Congress in the context of calling for such legislation to finally be passed. In fact, climate change legislation was mentioned in almost half (46 percent) of communications blaming Congress. The model, in turn, estimates the odds of mentioning renewable energy (which includes climate change legislation) as four times higher when Congress is blamed than when it is not. All other targets of blame, in contrast, were not significant predictors in the model, with the exception of BP, which was negatively associated with calls for renewable energy. In other words, the model suggests that blaming “one bad apple” did not fit with groups’ broader policy agenda. Together, these results provide clear support for the expectation, in H5, that blame-casting targets are tightly linked to leading solutions; they are two components of groups’ preconceived narratives, developed and ready to deploy should disaster strike.

Model 2 (Ban Drilling) also provides support for the linkage between blame-casting targets and leading solutions. As predicted in H5, blame directed at both America’s oil addiction and oil companies generally were significant predictors of calls to ban new offshore drilling. As in the renewable energy model, BP as a target of blame was negatively associated with calls to ban drilling, underscoring the fact that blaming BP did not fit with environmentalists’ policy agendas. In addition, blame directed at the Minerals Management Service and President Obama were associated with calls to ban drilling. As previously discussed, the dependent variable in this model includes calls to permanently ban new offshore drilling and to temporarily ban drilling, pending the results of an investigation of the Deepwater Horizon blowout, each of which could be associated with different targets of blame. The former

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.