Targeted Universalism Step 3: Identify groups and places that are performing differently with respect to the goal and disaggregate them

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This series documents my experimentation with the use of Targeted Universalism (TU). I used the Othering and Belonging Institute‘s primer on the subject. There are five steps:

• Exploring TU
• Step 1: set a universal goal
• Step 2: assess general performance
• Step 3: identify groups
• Step 4: understand the structures
• Step 5: develop strategies

Over the past few months I’ve been making my way through the Targeted Universalism primer. In Step 1, I defined my goal statement for the project.

Everyone should have access to food that is free. The food should be nutritious and appropriate to them. The food should be accessible within a 15 minutes walk.

In Step 2, I learned that 23 million people in the u.s. have to travel more than 15 minutes to find a grocery store. Access to appropriate foods depends on the area where you live. And 849K people in Washington state (35.2M nationally) don’t have the food they need to thrive.

In Step 3, the goal is to group and then disaggregate people into smaller categories. This creates a granular assessment of how each group fares with food access. We then compare that group’s performance to how the general population performs. If this were real life, by the end of the process each group would design its own targeted strategy.

The primer lists a few examples of groups that may apply to this review, so I’ll start there. Those are

• rural or urban populations
• racial, ethnic, or religious minorities
• LGBTQ+ persons
• people with disabilities

making assumptions

We can’t use assumptions about a person or a category that they might be in. Any time you make an assumption about a group, you risk helping them in a way that won’t help or they don’t want. For example, many organizations speak to serving Latine populations. They may identify this group as needing extra language support. But the Latine category would include me, and I speak english as my primary language. In another scenario, I could be the only Latine person in your focus group. I’m not going to be able to speak to the needs of all Latine people. To use another identity example, I as a cis queer man in a city may not end up in the same targeted group as a trans person in a rural area.

As the primer notes, “Black children growing up in an affluent suburb may have different needs or confront different challenges than Black children growing up in a low-income urban neighborhood or inner-ring suburb that has suffered decades of disinvestment and poverty.” You can use broader demographics as a starting point for discussion. Rarely will they be the final groups that need targeted strategies.

For the purposes of Targeted Universalism, race and ethnicity are a good place to start. There will be a wide variety of needs within any one group. A few could be differences in education, ability, geography, even the hours they work in a day. Remember, race and ethnicity matter because we live in a society of built white supremacy. These artificial divisions created almost all the gaps that Targeted Universalism can solve.

how many groups is too many?

Group specificity exists to identify a strategy that meets the needs of that group. My recommendation is to create as many groups as remedies needed. For instance, some groups could be

• “People who are most comfortable communicating in Spanish”
• “People who have food allergies”
• “People who don’t have a car”
• “People who can’t drive”

Consider the last two examples as a guide for combining groups with context. If our goal was to remedy joblessness, a person with a license but no car could borrow or buy a car to get to work. But that same car would not solve the problems of a person who isn’t able to drive.

For food access, a person who can’t drive and a person who doesn’t have a car may be similar enough to use the same strategy. They both may rely on walking or public transit to receive food.

conclusion: what I would do next

Once we create the categories, it’s time to understand them. We’d calculate their relative food access compared to the baseline. We would also want to vet the information we’ve collected. Join discussions with people from the affected groups. “What data rings true for your experience? What does not make sense? What does this data leave out about you?” This will help create more targeted strategies.

I would also lead a community canvas to identify even more access barriers. Even after we start to create strategies, we’d have to stay in contact with the community. New barriers may arise, or an existing barrier may have been misunderstood.

Disaggregating in this step helps us understand the complex issues each group faces. One individual may receive many strategies based on the groups they’re in. That puts them in a much better place than if we tried a one-size-fits-all strategy.

There are two more Targeted Universalism steps left to go! I’ll address them next.