This is the kind of WSU research that makes you stop and look at your own street differently. The takeaway is blunt: in Spokane County, the places nobody wants to live near, the wastewater plant, the Superfund sites, are sitting in neighborhoods where people have less education. That's not an accident. That's a pattern. And a team from WSU just built a new way to measure it.
The study, published in *Urban Sustainability*, ran the numbers on 13 socioeconomic variables across Spokane, then mapped the distance to 22 "desirable" facilities (parks, fire stations, a hospital) and five "undesirable" ones (the wastewater plant, four Superfund sites). The good news: parks and hospitals are placed pretty fairly, central and accessible across income levels. The bad news: every single undesirable facility landed closest to the two clusters with the lowest education levels. That's not a coincidence you can explain away with "well, the landfill was here first." It's a structural problem, and WSU researchers just gave planners a tool to stop repeating it.
This is the kind of work that doesn't make the scoreboard, but it matters more than most. While our Volleyball fights through five sets, shows Pullman grit in thriller and Owen Eshelman and Branden Ganashamoorthy made the scoreboard hurt a little less, a team in Pullman was coding a fairness metric from scratch. That's the same grit. Different arena.
What sticks with me is the method. Lead author Stephanie Kane and the team didn't just look at income or race alone. They built a composite score from 13 variables, education, income, demographics, and then clustered neighborhoods by that score. That's more honest than most city planning data. It catches the fact that a low-income neighborhood with a high school diploma is not the same as a low-income neighborhood with a GED, and those two neighborhoods might be getting treated differently by the same zoning map. The researchers even had to write custom Python code for one of the measurements. That's a Coug detail. That's a grad student in a basement office saying, "the existing tools aren't good enough, so I'll build a better one."
Here's the specific thing to watch: this method can be rerun as demographics shift. Spokane is growing. Pullman is growing. If city planners use this, they can catch a new landfill proposal before it lands in the same old neighborhood. If they don't, the data will show exactly who got left out again. That's the point. Not a vague hope. A measurable standard. Go Cougs.