With Hurricane Sandy slowing fading from the media’s limited attention span, it is time for advocates to “widen the lens” and tell a more persistent and compelling story about the effects of climate change. One way to do this is to use social math.
Grist.org has a great social math example based on the latest weather data from the National Oceanic and Atmospheric Administration (NOAA). The original data from NOAA states:
“The average temperature across land and ocean surfaces during October was 14.63°C (58.23°F). This is 0.63°C (1.13°F) above the 20th century average and ties with 2008 as the fifth warmest October on record. The record warmest October occurred in 2003 and the record coldest October occurred in 1912. This is the 332nd consecutive month with an above-average temperature.”
To contextualize this data so that the public has a better idea of what this actually means, Grist writes:
“If you were born in or after April 1985, if you are right now 27 years old or younger, you have never lived through a month that was colder than average.”
Social math involves making numerical information more meaningful for the public. It is about making concrete comparisons of information to familiar concepts. Grist.org succeeds in communicating the temporal trends in warming by comparing this data to the age of a young adult.
Where the rest of the article falls short, however, is in using social math as part of a well-framed story. If you simply contextualize data without also integrating other framing elements, such as values, metaphors, and solutions, then it is likely that the public may feel apathetic or helpless in regards to what that data means for them. The rest of the article compares the effects of hurricanes to droughts and concludes by saying:
“There’s not much else to say. At this point, we’re just doctors taking a fading pulse. Or, I suppose, tracking a rising fever.”
Wow. Talk about depressing.
At FrameWorks, we are working with informal science educators at zoos and aquariums throughout the country to help them better communicate climate science through framing. When translating science data into social math, we recommend:
1- using values to help the public understand why this information is important,
2- making concrete comparisons of information to familiar concepts, and
2- enabling the public to understand the broader impact of the information and consider appropriate solutions.
So, while we do think using this example of comparing weather changes over time to the life span of a young person is good, we would propose that the rest of the story include:
1- tested values of responsible management (e.g. “We know we need to responsibly manage the hurricane and drought effects of climate change),
2- a tested metaphor of “heat-trapping blanket” to connect causes (fossil fuel consumption) to warming trends, and
3- linking the story to solutions that match the scale of the problem (clean technology, renewable energy, and energy conservation).
When joined with tested framing elements, social math has the power to connect meaningless data into meaningful impact. And, in this example that links time to effects, it has the power to turn an episodic story about one storm into a story that is about the long-term future of our society.