<commit_before>---
layout: event
categories:
  - events
links:
title: "Using Data to Close the SNAP and EITC Participation Gap in NYC"
description: "Several members of the Civic Analytics team join us to talk about how their modeling work helped explore usage of public benefits in New York City."
speakers:
- <NAME> - Senior Applied Data Scientist
- <NAME> - Applied Data Scientist
- <NAME> - Applied Data Scientist
image: /images/events/255-civis.png
date: 2017-05-23T18:00:00-06:00
event_id: 255
youtube_id:
agenda: https://docs.google.com/document/d/1ueik_hJzJUif8NapH6vVG7q7YwduPaZUBZ1p6jw46d4/edit#
sponsor: <a href='https://twilio.com/'>Twilio</a>
published: true
---

In 2016, Civis Analytics' Applied Data Science team worked with the Robin Hood Foundation, one of the largest poverty-fighting foundations in New York City, to find out which neighborhoods in New York City were under-participating in two public benefits: SNAP, formerly known as food stamps, and the Earned Income Tax Credit.

In order to help the Robin Hood Foundation figure out how best to target its resources and do outreach through canvassing and community organizing, Civis used Census data from the American Community Survey to identify which areas had a high number of eligible participants who were not claiming benefits.

Civis used models to improve our estimates and bring in additional information about the communities. In this talk, Civis will discuss how they approached the problem, data and modeling challenges we encountered along the way, and introduce some of the findings from their work!<commit_msg>edit copy<commit_after>---
layout: event
categories:
  - events
links:
title: "Using Data to Close the Safety Net Participation Gap in NYC"
description: "Several members of the Civic Analytics team join us to talk about how their modeling work helped explore usage of public benefits in New York City."
speakers:
- <NAME> - Senior Applied Data Scientist
- <NAME> - Applied Data Scientist
- <NAME> - Applied Data Scientist
image: /images/events/255-civis.png
date: 2017-05-23T18:00:00-06:00
event_id: 255
youtube_id:
agenda: https://docs.google.com/document/d/1ueik_hJzJUif8NapH6vVG7q7YwduPaZUBZ1p6jw46d4/edit#
sponsor: <a href='https://twilio.com/'>Twilio</a>
published: true
---

In 2016, Civis Analytics' Applied Data Science team worked with the Robin Hood Foundation, one of the largest poverty-fighting foundations in New York City, to find out which neighborhoods in New York City were under-participating in two public benefits: SNAP, formerly known as food stamps, and the Earned Income Tax Credit.

In order to help the Robin Hood Foundation figure out how best to target its resources and do outreach through canvassing and community organizing, Civis used Census data from the American Community Survey to identify which areas had a high number of eligible participants who were not claiming benefits.

Civis used models to improve our estimates and bring in additional information about the communities. In this talk, <NAME>, <NAME> and <NAME> will discuss how they approached the problem, data and modeling challenges we encountered along the way, and introduce some of the findings from their work!
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