# gerrymandering

Published articles for gerrymandering.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Earthmover Distance

DevFeed: [Earthmover Distance](<https://devfeed.tech/articles/earthmover-distance-40419.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2018/03/05/earthmover-distance/>)

Published: 2018-03-05T08:00:15Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Code](<https://devfeed.tech/topics/code.md>), [Python](<https://devfeed.tech/topics/python.md>), [Library](<https://devfeed.tech/topics/library.md>)

Tags: [code](<https://devfeed.tech/tags/code.md>), [earthmover-distance](<https://devfeed.tech/tags/earthmover-distance.md>), [gerrymandering](<https://devfeed.tech/tags/gerrymandering.md>), [library](<https://devfeed.tech/tags/library.md>), [linear-programming](<https://devfeed.tech/tags/linear-programming.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [optimal-transport](<https://devfeed.tech/tags/optimal-transport.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [probability-theory](<https://devfeed.tech/tags/probability-theory.md>), [python](<https://devfeed.tech/tags/python.md>), [wasserstein-metric](<https://devfeed.tech/tags/wasserstein-metric.md>)

### AI overview

This tutorial explains how to measure distance between point sets with uncertain locations by treating each sample set as a discrete probability distribution. It formulates Earthmover distance as a linear program that minimizes the cost of moving probability mass between points.

### Source excerpt

Problem: Compute distance between points with uncertain locations (given by samples, or differing observations, or clusters). For example, if I have the following three "points" in the plane, as indicated by their colors, which is closer, blue to green, or blue to red? It's not obvious, and there are multiple factors at work: the red points have fewer samples, but we can be more certain about the position; the blue points are less certain, but the closest non-blue point to a blue point is green; and the green points are equally plausibly "close to red" and "close to blue.

## Notes on Math and Gerrymandering

DevFeed: [Notes on Math and Gerrymandering](<https://devfeed.tech/articles/notes-on-math-and-gerrymandering-40415.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2017/08/14/notes-on-math-and-gerrymandering/>)

Published: 2017-08-14T08:00:40Z

Content type: opinion

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [math](<https://devfeed.tech/topics/math.md>)

Tags: [gerrymandering](<https://devfeed.tech/tags/gerrymandering.md>), [legal](<https://devfeed.tech/tags/legal.md>), [math](<https://devfeed.tech/tags/math.md>), [policy](<https://devfeed.tech/tags/policy.md>), [research](<https://devfeed.tech/tags/research.md>), [us](<https://devfeed.tech/tags/us.md>)

### AI overview

The article distills ideas from the Geometry of Redistricting workshop about how mathematics might help address partisan gerrymandering. It emphasizes the need to account for legal, political, and local factors, and notes that many obvious approaches have already been tried or rejected.

### Source excerpt

Last week I was in Boston for the Geometry of Redistricting workshop. It was an optimistic gathering of over 500 mathematicians, computer scientists, lawyers, policy makers, teachers, and interested people of all stripes. There was a ton of information in the talks and subsequent discussions. I'll try to distill the main ideas and avenues for research as best I can. Unfortunately, due to how preliminary most of the technical work is, I won't be presenting any concrete code or algorithms.