I'm reviewing the original Philadelphia Tenants Union proposal that was proposed by David Thompson and Tim Horras for the Philly Socialists in August 2015. At that time, Tim Horras was chair of the organization. And David Thompson currently is chair.

For the record, I'm currently a dues-paying, but inactive, Philly Socialists member. I was very active in August 2015 and before.

Their proposal (see below) might have been slightly modified (before adoption) to include more of a time line.

This is a great map of redlining in the US in 1935 and 1940. They've digitized historical data for large cities.

Longer version of this article for statisticians (Open Office format)

Introduction

I have developed a very tentative prediction model for the Philadelphia District Attorney's race and the Democratic primary on May 16, 2017.

The incumbent, Seth Williams, dropped out due to corruption. This left the city with a wide-open race. The Democratic party establishment has not endorsed anyone. Instead individual Democratic leaders have spread their support among the seven candidates.

My model is based on several weighted factors. The weights are somewhat arbitrary. For instance, I would give polling more weight if there were independent polls and more polls in general.

This super high resolution map of US presidential election results (2008, 2012, and 2016) by precinct is amazing.

It's by Decision Desk HQ which is a pro-Democrat polling and analysis organization with a strong record.

Larry Krasner is running for Philadelphia District Attorney on a platform of ending mass incarceration. He is a long-time defense attorney who has defended numerous activists in court and has longstanding ties to social movements.

Cross-posted from Energy Justice

I recently updated the Income Layer on Justice Map to use the latest 2011-2015 American Community Survey data.

You can view the data by county or by census tract (roughly 4000 people). While census tracts provide higher resolution that helps us identify areas of environmental injustice, unfortunately the confidence interval is much larger. So there is a lot of noise in the data. If you are looking at the income layer and see a random checkerboard of blue and red - that is noisy data.

As part of this process, I added a Income Change layer that shows the change in median household income between the first period (2006-2010) and a second period (2011-2015).

It is easiest to see the trend in changing income by looking at the counties. The census tract data is even noisier than the regular income data, as the confidence interval is approximately twice as large. However where there are strong trends - like gentrification in DC and Philadelphia you can easily see them at the tract level.

Click on the map to learn how income has been changing in your community!

Change in Median Household Income

A couple comments on Trump's presidential election win.

1. Clinton won the popular vote by an estimated 2.09%. This election was the results of a very recent bias in the Electoral College that favors Republicans. A very small percent of the US population are swing voters (5-10%) and a small shift can result in a large change due to our winner-take-all system. There isn't necessarily a need to do analysis of "Why did Trump Win / Clinton lose" or to change our fundamental priorities.

In the 2016 general presidential election, the Green party candidates for State Auditor and State Treasurer beat the Libertarians (including the well-known Gary Johnson). But presidential candidate Jill Stein did not fare as well due to strategic voting against Trump.

I live right next to the center of Green Party support in West Philly!

Category Breaks used in the maps: 0.25%, 0.5%, 0.75%, 1%, 1.5%, 2%, 2.5%.
Click on the image for a high resolution one.

Early findings on 2016 Presidential Election
I have a county-level model that I used to predict the outcome of the Democratic Presidential Primary ahead of the election, and also a real-time model that estimated the state-wide swing based on the county swings. I used this model to make a significant amount of money betting/predicting the outcome on PredictIt.org. I also created my own real-time model for the presidential general election and used that (and the NYT real-time model) to make more money on PredictIt.