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Activity Number: 132 - SLDS CSpeed 1
Type: Contributed
Date/Time: Monday, August 9, 2021 : 1:30 PM to 3:20 PM
Sponsor: Section on Statistical Learning and Data Science
Abstract #318958
Title: Worldwide Statistics Without Borders and Client to Consultant Bridge Collaboration: Statistical Storytelling in the Time of COVID
Author(s): Michal Czapski and Joshua Derenski and Stephen Godfrey* and Michelle Vanchu-Orosco
Companies: Statistics Without Borders and Statistics Without Borders and Statistics Without Borders and Greater Victoria Coalition to End Homelessness; SWB
Keywords: machine learning; multistage data pipeline; partnerships; community service; Client to Consultant Bridge; Statistics Without Borders

Statistics Without Borders (SWB) supported Client to Consultant Bridge (C2CB) in telling their data story in meaningful, impactful ways. As customers sheltered in place and businesses closed doors in response to COVID-19, the impact to small businesses was expected to be devastating. The SWB-C2CB collaboration addressed this challenge by assisting businesses in finding relevant aid opportunities among numerous programs by U.S. federal, state and local governments, corporations and philanthropies.

SWB and C2CB built a data pipeline using machine learning techniques to automatically curate a national list of such programs and present users with results to efficiently research and find offerings most relevant to them. While this project curated business-relief grants, it is a proof-of-concept for a low-cost data pipeline using machine learning techniques with automated website relevancy classification.

C2CB is a volunteer organization of management consultants helping small U.S. businesses impacted by COVID 19. SWB collaborates on projects providing pro bono expert help to nonprofit organizations and governmental agencies with research, statistical analyses and survey design.

Authors who are presenting talks have a * after their name.

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