You’re probably underrepresented in the U.S. Senate.

Rico Gardaphe
qri.io
Published in
5 min readNov 13, 2020

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…but how badly?

This post is a follow-up to my first piece exploring the disparities of power and representation across U.S. states in the Electoral College and the U.S. Senate. The stars of that post were the cases of Wyoming v. California, and Vermont v. Texas (pairings intended to show the most dramatic disparities). In this post, I thought I’d zoom out a bit and offer a view on the full landscape of states.

“The Virtue of a Proportional Response”

First, I’d like to acknowledge that I understand the U.S. Senate never was proportional, was not designed to be proportional, will likely never be proportional, and perhaps should not be proportional. I offer this analysis principally to explore an interesting question (how far off are various states’ representation in the US senate today from a proportional arrangement?), and to educate myself and others on the current state of affairs.

To that end, I built the table below showing each U.S. state and the percentage of representation/power it has today compared to what each might under a perfectly proportional system.

If a proportional allocation of power is the goal, then 100% would be the goal for each state. States below 100% are ‘underrepresented’ today, and states above 100% are ‘overrepresented.’

For example, North Dakota has 860% of the representation or power it ‘should’ have in the Senate (Should is in quotes, again presuming proportionality is the goal). It is 760% over-represented.

Here’s how I calculated those percentages:

Proportional Ratio: Under a perfectly proportional system, America’s 327 million residents would be represented by 100 senators at a ratio of 3.27M per Senator.

Present-Day Ratio: I calculated this ratio (population per Senator) by dividing each state’s current population by its count of Senators (2).

I then divided each state’s Present-Day Ratio by its Proportional Ratio and built this table. If a state is proportionally well-represented today, that ratio should be close to 1, or 100%. States below 100% are ‘under-represented’ (in red), states above 100% are over-represented (in green).

Finally, I graphed the results.

Plot the Dots

The graph below shows U.S. states along the X-axis, and their relative percentages of their populations’ under or over-representation in the Senate along the Y-axis. If a state is below the green dotted line, set at the now familiar 100%, it is underrepresented, and if the state is above it, it is overrepresented.

The graph above tells a dramatic story about the states in the upper right-hand corner, but it leaves the false impression that the states crowded near the dotted green line (from California to Kentucky) are in the same ‘representation ballpark.’

I assure you, they are not.

The Population Price (Per Senator)

Here’s essentially the same information presented above, but more simply. Below is a graph sorted by each state’s ratio of its population per Senator. I simply took each state’s population and divided it by two. I also coded each bar (red, blue, purple or grey) with the political party breakdown of its Senate delegation in the 117th Congress (the next Congress).

If we allow for the idea of paying a ‘population price’ per Senator, the states above the dotted green line pay too much (their populations are above the average of 6.55M of perfectly proportional system), the states below the dotted green line are getting a deal on representation.

The US has 327m residents and 100 Senators, giving us a ratio of 3.275m residents per Senator under a proportional system. The green line in the graph above is set to that ratio, showing which states’ ratios fall above or below it.

It’s worth noting that the first (and most populous) nine states from the left (California, Texas, Florida, New York, Pennsylvania, Illinois, Ohio, Georgia, & North Carolina) represent over half of the total US population. Yes, 50% of the population are represented by just 18% of the Senators.

From this data alone it’d be inaccurate to conclude that ‘blue’ states are disadvantaged in the Senate and red states are advantaged, although that’s probably true today. First, a state’s Senate delegation is only one way to define its ‘redness’ or ‘blueness,’ and the binary nature of the two colors betray the competitiveness of any given race in any given year. Second, Congressional (House) delegations are more nuanced (ignoring the warping that happens via gerrymandering) and are determined 3 times as often (every two years vs. every six years). There are more reasons. I’m just saying, you can’t ONLY use this analysis to say one party or the other suffers more or less because of the structural design of the Senate.

Solutions

I don’t have them. Sorry. My only goal here was to crunch the data (linked below) in an effort to educate myself and anyone else about the existing disparities in representation. For now, there seems to be enough work just convincing folks that this is a problem (in my circles anyway). You may think Vermont’s 46x advantage over Texas in the Senate is not a problem, but at least now you know the scale of the advantage.

I’ll close out this two-part series of Senate bashing by directing you to some articles that explore this issue further. Some even lay out interesting scenarios for resolving the problems that arise from the wacky system we’ve designed for ourselves.

Get the data

Surely there are other interesting factors aside from gross population (GDP contributions by state, income data, age distribution, population density, etc.) you can use to say something interesting about our states and how they’re represented.

I encourage you to play with the data I’ve made available and run some comparisons of your own. I’ve published the dataset I built & used on qri cloud — a platform for publishing and discovering open data projects:

You’re free to download my data, subscribe to updates (as I publish new versions), or continue the conversation there by filing an issue.

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Rico Gardaphe
qri.io

Head of Business Development for Qri — free and open source dataset versioning software. Former strategy consultant and Obama White House staffer.