Name: datasci-congressional-data
Owner: SFBrigade
Description: CSUMB in Collaboration with C4SF Data Science Working Group work together to solve problems with Congressional Data
Created: 2017-12-14 02:22:03.0
Updated: 2018-05-10 20:04:15.0
Pushed: 2018-05-10 20:04:17.0
Homepage: null
Size: 30780
Language: Jupyter Notebook
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This project is a part of the Data Science Working Group at Code for San Francisco in collaboration with CSUMB Computer Science students who are completing their capstone project. Other DSWG projects can be found at the main GitHub repo.
Campaign finance in the U.S is the key to the system of corruption that has now wrecked our government. Members and candidates for Congress spend anywhere between 30% to 70% of their time raising money to get themselves (re)elected. But who and how many people actually contribute to these campaigns?
It turns out that only a tiny fraction of the 1% are actually “relevant funders” of congressional campaigns. In other words, 150,000 Americans wield enormous power over this government. Furthermore, our government is supposed to represent the public, but with so few making meaningful financial contributions, how do we know if our elected officials are not answering to special demands these “funders” make?
This challenge and the problems we face is described beautifully in Lawrence Lessig's TED Talk in which he discusses the problems of Campaign Finance in America as the number one issue that blocks progress on every other issue.
The goals of this project are to use data and technology to (1) provide more transparency of campaign finance at the local, state, or even federal level and (2) investigate how campaign finance contributions affect elected officials' behavior. Our current problem statements can be found here.
As an optional component to this project, Challenge.gov is currently sponsoring a Congressional Data Competition. The Challenge framing is actually quite broad: the goal is to create an application, website visualization, or other digital creation that helps analyze Congressional data. As an optional component, we can have as a deliverable to submit to this competition (there is a $5,000 prize)!
This project broadly decomposes into client/server and data eng/sci tasks:
We recently extracted the client/server code into it's own repo (for cloning efficiency on Travis).
The data eng/sci code is housed in this repo.
Other Roles Include:
Please go to the Onboarding docs to start contributing to this project!
| Time | Milestone | |———— |——| | December 2017 |
Team Leads (Contacts) : [Full Name](https://github.com/[github handle])(@slackHandle)
| Week | Name | Slack Handle | |———— |——|———— | | 01/03/2018 - 01/09/2018 | Vincent La | @vincela14 | | 01/10/2018 - 01/16/2018 | Erik Eldridge | @erikeldridge | | 01/17/2018 - 01/23/2018 | Vincent La | @vincela14 | | 01/24/2018 - 01/30/2018 | Vincent La | @vincela14 | | 01/31/2018 - 02/06/2018 | Vincent La | @vincela14 | | 02/07/2018 - 02/13/2018 | Vincent La | @vincela14 | | FUTURE DATE | YOUR NAME | YOUR SLACK HANDLE |
|Name | Slack Handle | |———|—————–| |[Full Name](https://github.com/[github handle])| @johnDoe | |[Full Name](https://github.com/[github handle]) | @janeDoe |
#datasci-congressdata
Note while the main focus of this project will be on campaign finance, there are undoubtedly other very interesting questions using congressional data. Some additional ideas include: