How the demographics of your neighborhood changed

The San Francisco Chronicle compares demographics in your neighborhood in 2020 against 2010. It’s a straightforward app that lets you enter an address (not just in California) and it shows you the changes at several geographic levels.

I like how snappy it is when you enter an address.

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Multiracial people counted in the census

Using unit charts, NPR shows the number of people who identify with each race or ethnicity:

[A] different kind of breakdown can show how racial groups are becoming more heterogeneous. This graphic shows the number of people who said they identified with each race, regardless of how many races they chose. For example, if a person said they identified as Black and Asian, they would appear in both racial categories.

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Race and ethnicity map of dots

CNN goes with the dot density map for their first pass on the 2020 decennial. Each dot represents a certain number of people depending on your zoom level. Color represents race or ethnicity.

Does CNN have a limited color palette that they’re allowed to use? I would’ve gone for more contrast between the light blue for white and darker-but-still-light blue for American Indian/Alaskan Native.

See also: Dustin Cable’s racial dot map from 2013 and Erica Fischer’s dot maps of the same flavor from 2010.

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Shift in white population vs. people of color

The New York Times go with the angled arrows to show the shifts in racial population. The red-orange arrows show an increase in the share of white population, and the teal arrows show an increase in the share of people of color. Longer arrows mean a greater percentage point change.

Whereas The Washington Post focused more on the changes for each demographic individually, NYT focused more on how two broad groups compared.

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Maps of racial population change

Using their peaks and valleys metaphor, The Washington Post shows the shift in racial population between 2010 and 2020. The open triangles, one for each county, show population with width, population growth with height, and fastest-growing race or ethnicity with color.

You might recognize the form from the Post’s 2016 election results, but there’s a small wrinkle when you look at the breakdowns for individual groups. The triangles flip upside down for where population decreased.

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Historical shifts in where people live

The places in the United States with the highest populations weren’t always like that. There were shifts over decades. With the recent Census release for state populations, Harry Stevens and Nick Kirkpatrick for The Washington Post go all in with a series of bump charts to show the changes in state population rankings since 1920.

They point out historical markers along the way, split it up by region, and provide an explorer at the end to look at your states of interest. In the end, it all comes down to weather and air conditioning.

Still deciding what I think about those gradient connections.

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States that gained and lost seats with 2020 count

The Census Bureau announced their state population totals, so we can see who gained and lost seats:

The tables aren’t accessible yet, but during the live conference, the bureau noted that the difference between New York losing a seat (which they did) and staying the same was only a difference of 89 people. It’ll be interesting to see these small deltas for all the states.

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Seat apportionment over time

The 2020 Census count at the state level is set for release this afternoon, April 26 at 12pm PST. While we wait, Gregory Korte and Allison McCartney, reporting for Bloomberg, show which states are expected to lose and gain representation.

I appreciate the streamgraph that shows how the distribution of seats changed over the decades, along with the bar chart mouseover so you can see the shift for each state individually.

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How your state might lose or gain representation with Census count

Harry Stevens, Tara Bahrampour and Ted Mellnik for The Washington Post look at how the upcoming Census count affects representation in the House. Montana and Rhode Island are projected to gain and lose a seat, respectively, which switches their positions in terms of seats per population.

The explanation of how counts and representation work, with a progression from abstract concept to specific cases, is on point.

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Technopolitics of the U.S. census

Dan Bouk and Danah Boyd wrote an essay on the data infrastructure and politics behind the decennial census:

Like all infrastructures, the U.S. decennial census typically lives in the obscurity afforded by technical complexity. It goes unnoticed outside of the small group of people who take pride in being called “census nerds.” It rumbles on, essentially invisible even to those who are counted. (Every 10 years, scores of people who answered the census forget they have done so and then insist that the count must have been plagued by errors since it had missed them, even though it had not.) Almost no one notices the processes that produce census data—unless something goes terribly wrong. Susan Leigh Star and Karen Ruhleder argue that this is a defining aspect of infrastructure: it “becomes visible upon breakdown.” In this paper, we unspool the stories of some technical disputes that have from time to time made visible the guts of the census infrastructure and consider some techniques that have been employed to maintain the illusion of a simple, certain count.

This process, whether we know what’s going on or not, in turn affects voices and democracy across the country. So it’s kind of important.

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