At Cohesion Strategy, I help funders and grantees build unlikely partnerships that promote long-term change across divides. Given language has become so loaded with partisan meaning, getting the framing right can be tricky.
Our language often carries implicit biases, shaping our perceptions and interactions. In other words, if we hear someone use the term “social justice,” we might also assume that person shops at Whole Foods, wears Prana brand clothes, and votes the Democratic ticket. This is what Lilliana Mason calls a “mega identity.” All this loaded language helps us figure out where we “fit” in society, but also we tend to get trapped by these identity sets. As my friend Amy McIsaac over at Philanthropy for Active Civic Engagement (PACE) puts it, “Words used to be words, but now it seems like they are signals.”
Those signals can hinder communication and collaboration, leading to missed opportunities for progress. Here’s an example: a few years ago I was working with a group of religious freedom advocates from across the ideological spectrum. Yes, they were divided on a number of issues. But they also had an opportunity to build consensus on many shared goals.
But their framing language inadvertently alienated each other. In other words, they couldn’t build an alliance on fighting words.
Because we tend to get trapped in our bubbles, it can be hard to know how the language you’re using is perceived by your intended audience. That’s where PACE’s Civic Language Perceptions Project can help.
PACE has run this language perception survey several times since 2019. The survey tries to understand Americans’ perceptions of various civic terms, including whether words tend to unite or divide us, or motivate us toward civic action. Since civic language is a big part of most efforts for social change, it’s worth taking a gander. The new data dashboard is out from the survey late last year, accessible here.
Let’s take an example. Say you are trying to improve outcomes for underserved minorities in a rural, red-leaning place that has struggled with racial tensions. This project could be framed in a variety of ways. PACE’s data dashboard will let you look see how the terms “belonging,” “community,” and “racial equity,” are perceived by folks you’d need to buy in for success: registered Republicans in rural communities.
Here are the cross tabs on those terms by political party, filtered by rural respondents. The visualization is so clear.
Belonging:
Community:
Racial Equity:
Rural Republicans respond much more positively to terms like "community" than "racial equity.” Framing the project in language that makes these folks feel positively is good strategy.
The possibilities with this data are manifold, plus, it’s fun to play with the stacked bar charts (#nerd). However, if playing with data and reading through statistics to land on better framing is not your happy place, you can try using Pluralytics, an AI tool that helps you revise language to appeal to your audience. PACE has partnered with them, and there’s a fascinating snippet about how it works starting at about the 44 minute mark of this deep dive on the term Patriotism, here.
If you are looking to expand your skillset in building unlikely partnerships that promote long-term change across divides, get in touch with us here at Cohesion Strategy. We're here to support your endeavors in bridging divides and driving long-term impact.
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