Republicans are requesting a liberal Wisconsin judge recuse herself from potentially considering reviewing the Badger State’s congressional maps.
Earlier this month, Democrats asked the Wisconsin Supreme Court to reconsider the state’s congressional maps, using the high court’s opinion in a separate elections maps lawsuit as reason to consider a redo over Wisconsin’s congressional maps.
But five members of Wisconsin’s GOP congressional delegation filed a motion Tuesday asking Justice Janet Protasiewicz to recuse herself from hearing the case, pointing to comments she made when she was a candidate running for a spot on the court last year as reason to not weigh in.
Among some of the comments Republicans pointed to included her calling the state’s maps “rigged” and saying she “would certainly welcome the opportunity to have a fresh look at our maps.” However, neither she, nor her Republican opponent, detailed how they would vote on a potential case while on the campaign trail.
The true answer is to use maps created via Shortest Splitline.
How it works is easy. You take a map of the population of the state and then draw the shortest line possible that splits the population in half. You then continue this exercise until you have enough districts to satisfy the number of elected positions. For odd numbers of districts, you separate one district in to 1/3ds via the shortest lines possible.
This would fix almost every state’s gerrymander problems.
The next fix seems counter intuitive, but is not if you learn some basic history. We expand the size of congress. Expand it massively. See, then the constitution was written, it was assumed that the size of congress would grow to better represent the will of the growing population.
The problem started in 1920. WW1 had just ended, and it played havoc on the census. This led to a bitter fight in congress over how many seats to award each state. Now, because of the arguing, there was no 1920 congressional apportionment (the assigning of the number of Representatives in the House)
The arguing and fighting lasted until 1929. Congress decided that they were not going to start the 1930 apportionment without finishing the 1920 apportionment, but still couldn’t agree on a new number of Representatives, so they said “fuck it” and passed the 1929 Permanent Apportionment Act. This froze the size of the House at 435 members (The number from 1910). It’s been stuck at that level ever since, even with adding two new states and more than tripling the population since then.
This little quirk of law makes it so much easier to gerrymander control of the House today than it was when the term was invented. And all it would take to fix it is a single act of congress. Just one law to reapportion the House with a larger number. But then you have a fight over how many… Except that you can use any number of algorithms to automatically distribute seats.
AlphaPhoenix has a video about this, showing how even techniques that are designed to create geometrically simplistic districts can absolutely be manipulated to get you practically any election result you want, with sufficient input data and well-defined goals.
There’s more than enough fuzz in the “shortest possible line” idea to allow for manipulation. And those shortest possible lines will often, by nature, divide population centers, cracking urban voices that tend to have different political opinions than the non-urban voices that will be more likely to be packed by this system. It’s easy to imagine that this algorithm will systemically favor conservatives because of how they don’t tend to live in cities.
Algorithmically-decided districts will also inherently ignore communities, both historic and demographic, again creating a high cracking likelihood and creating outsized representation to the dominant political groups.
These tech-bro-thinking solutions will never be the answer. The answer to redistricting* is to have a controlled political process with checks and balances. Nonpartisan commissions, transparent review,
You’re using “algorithmically-decided districts” to mean “districts decided by algorithms that only look at population”. You can absolutely create algorithms that take communities into consideration. You can absolutely create algorithms that reduce the amount of manipulation allowed.
What you can’t do is create truly nonpartisan groups. As long as you leave the decision in human hands, because it is so important, there will be humans out there trying to manipulate the results for their own benefit.
If you truly want a long-term solution, you should be looking at an algorithmic solution. Maybe it already exists. Maybe it doesn’t.
No, I’m not. Again, the video I referenced if you want to know what most influenced my thinking on the subject.
The problem is, the algorithms only factor into consideration the things they’re programmed to consider. They have to also be told how to weight and consider these properties.
By relying on algorithmic approaches, all you have done is change gerrymandering from the art of line-drawing into the art of algorithm design. It’s not really any different in terms of outputs. All a bad actor needs to do it figure out the initial weights to specify – which can easily be made to look innocuous – to get the election results they want. And with any remotely competent approach, they can work backwards from their result to discover initial weights that will achieve that goal. So long as the process is allowed to be partisan, this will be what will happen. Right now they’re fucking overt about it because they have been able to get away with it. In the near future, they’ll be WAY more cagey and subtle about it and lawsuits like this Wisconsin one will become harder and harder to win.
And merely deciding what weights you do and don’t consider and how they compare to each other is an inherently partisan process. There’s SO MANY criteria for deciding which groups should not be split or can be split by these algorithm lines. This is just cracking and packing in a different form.
On the flip-side, a transparent and non/multi-partisan process resists these kinds of machinations in the first place. A more manual line-drawing process is much harder to do partisan cartography stenography with.
The data scientists should stick to evaluating the maps. They should stay WELL clear of designing them.
Let’s say that you have the best possible group of humans making the map. How do they do it? If you can explain it, that is an algorithm. If it’s an algorithm, it can be run by a computer. If you can’t explain it, then how can it really be the best?
Speaking of transparency, there is nothing more transparent than an open source algorithm.
And as for the weights, that is an optimization that can be specified without human intervention.
Technophobia isn’t a sufficient reason to double down on a system that we’ve seen over and over to be completely broken.
It is absolutely not. That is not true. The optimization is a political question because what is “optimal” is a political question.
If you have a theoretically-perfect algorithm, you don’t even need to have the elections. That’s an unnecessary abstraction; it can just pick the winners directly.
Leave the personal attacks off. There’s no technophobia here – I just have a different (and I believe much better) understanding of the technology’s inputs and outputs.
With a nonpartisan or multipartisan approach, there is no need for a “best” group of humans. You have innate checks and balances on the political process. Without a nonpartisan or multipartisan process, you plainly don’t.
The way optimization works is that you have a desired outcome, and you adjust inputs until you reach an optimal outcome. This is a specific area where algorithms are known to be effective. The desired outcome can be anything that is measurable. Whatever a person who looks at the result could possibly use to criticize it, for example.
You cannot simply dismiss an algorithmic solution. In fact, given enough time, it’s guaranteed that an algorithmic solution will be the best available solution. I don’t know how to refer to a person who denies this obvious fact, so I use the term technophobic. It could be simple ignorance or it could be some sort of irrational state of mind, but I think that’s all encompassed by the term technophobic.
There is still no objective measure of what is optimal for this problem. But I can tell you aren’t listening.
Yes that is why you have to run an optimization algorithm. To find the best known solution based on measurable results. I suggest you read up on numerical analysis.
And I am listening. I simply know a great deal more about this subject than you do, so your perception of this conversation is quite different from mine.