The Town and the Gown

Community support for campus approaches to sustainable energy use: The role of “town–gown” relationships  by Katherine McComas

(Full text)

Key Takeaways: 

Cornell and Ithaca

  • In so called town-gown relations, the towns often feel dominated by the gowns (the schools). Many factors and details affect town support for university endeavors, including fairness and self-efficacy. 
  • Often the power structure of the university is unknown and abstract to the town residents as they don’t know who exactly makes the decisions. 
  • Of the six the energy solutions (bioenergy, carbon offsets, enhanced geothermal systems, forest carbon sequestration, urban park-and-ride, and wind power), the middle four were equally supported while wind power was the most favored and carbon offsets were perceived negatively and thought of as paying to pollute. 
  • The most important factor measured was self efficacy, which had a greater impact than any type of fairness. Fairness pertains to how the process is perceived and how people believe they’d be treated by those in power. Self efficacy pertains to ones own belief in being able to cause change.
  • Support for solutions also increased as the physical distance away from the individual increased. 
  • For university to marshall its community support, the best way to do so is to be proactive in seeking out and incorporating community input. This input should make the community feel heard without being talked down to or patronized.

Town-gown relations refer to a university and its native town relationship. For major universities it can often feel like they dominate the local culture and economy. Or in some places, like Ithaca, like the the university *is* the local culture. Universities, since they are nonprofit, don’t pay taxes while they enjoy local government benefits. And when a major decision such as a power source for the university is up to decide, its not uncommon for town residents to feel like its a one way street where they have no say in the matter. Despite this, town support remains important as lack of it can delay and derail University efforts or lead to a buttered community.

If Cornell University is the gown, its Ithaca that comprises the town, and the Ithaca Cornell relationship has been tested a few times over. Cornell laid out plans for a lake source cooling program in the late 90s which would use the latent energy in local Cayuga Lake to help cool Cornell and the local high school, before returning the water at a slightly higher temperature. Many Ithaca residents didn’t trust the plan and worried about the effects it would have on the lake and marine life it encompassed. An opposition campaign picked up steam (excuse the pun) and even became the beneficiary of a high profile Ralph Nader visit. The Lake Source Cooling was after much rigamarole ultimately implemented and now widely considered a success, even if pockets of Ithaca residents still mistrust it. Ithaca and Cornell didn’t stop colliding there, as their recent history includes the of scrapping plans to build wind turbines and the 2005 parking lot that Cornell gave several concessions on. All of this engendered Cornell wanting to improve their relation with Ithaca by opening dialog with Ithaca.

Cornell’s Lake Source Cooling Plant

Fast forward to the current tense and Cornell is trying to achieve net zero carbon emissions status. Its an ambitious plan for such a large campus, and one that could impact the community in ways that effect air quality, roads, and power sources. Many of these changes would be subject to local ordinances that require town support or votes. So Cornell researchers wanted to see, what shapes peoples support for an a relationship like this?

Well, in short, many factors. Fairness was believed to be a key factor influencing support. Since many in the town feel voiceless, how fair they perceive the process should be a key ways for them to feel respected and give their approval. This feeling of fairness allows the residents to indirectly “vote” on issues. Fairness in this case includes how the fair the process is believed to be (procedural fairness), that the information involved is accurate and openly communicated (informational fairness) and how an individual believes they’d be personally treated by the decision makers (personal fairness).

The study itself consisted of mailing a questionnaire to inhabitants of Ithaca and Tompkins county (since Cornell stretches past Ithaca in parts). There were six different versions of the questionnaire, each testing support for a different energy technologies or changes that could help Cornell achieve their stated goal of net zero carbon emissions. The questionnaires were the same except for the the energy solution describing and each came with a definition of it, to avoid people essentially guessing or going with just a “gut feel.” The majority were not familiar with the technologies aside from wind power – things that included bioenergy, carbon offsets, enhanced geothermal systems, forest carbon sequestration, urban park-and-ride, and wind power.

Of the six conditions, the middle four were perceived about the same, while carbon offsets and wind power were at the bookends. Carbon offsets was the least supported, as they are generally viewed as paying to pollute and don’t seem like an actual positive to many. Wind power was significantly better received than the others, maybe because its viewed as renewable and is extremely visible and well known.

The main findings of interest is how things like fairness and other factors affect the town gown relationship, one that is defined by having a sort of abstract power structure. But fairness wasn’t the biggest factor. Fairness was certainly a factor, like in most community settings, and people are more supportive of any decision if they believe it was fair. The biggest factor was self efficacy, or how much an individual believed could affect the situation. This fairness and self efficacy paint a picture of community members simply wanting to have a voice in the matter, and not feel marginalized. There was a knowledge gap, people may not know who exactly the leaders were, but still have opinions. The most important factor was not fairness, but rather “self efficacy,” the researchers found. Also as important was how the combined with the cost and reliability of the solution was perceived. In other words, people supported with what seemed the best most complete idea.

Support also increased as the solutions physically moved father away from them. People loved wind, but weren’t so crazy about wind turbines nearby. This was more a case of not in my backyard (the commonly heard NIMBY) as opposed to outright lack of support (not in anyone’s back yard).

Aside from wind power’s support, there were other smaller factors that showed. Men were more supportive in general, as were those who leaned liberal. People who lived with university employees were actually less supportive of the initiatives, possible cynical about the university always getting what they want.

The most supported university plans were ones that benefited the community as well. This shouldn’t be surprising given the findings about fairness and self efficacy. So the best way to marshall support is to solicit community input, and actually incorporate it. Or give a way for a dialog between the town and the gown, while not patronizing or reminding community members “how lucky they are.” Inspire trust and let people be heard, all with the goal of proactively laying a foundation of trust.

Of course, as is usually the case with research like this, the factors tested can only account for so much of the difference among opinions. In this case it was 30%, which was a significant finding. Given the details and factors that can affect support and those that were unmeasured, such as value systems, risks associated, sense of place, beliefs about climate change, etc, 30% is still pretty sizable. Without further research its hard to know how generalizable the findings are. But given the diversity of the sample, its clear fairness and self-efficacy matter a lot and similar findings can be replicated in many other settings.

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