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Data Science · Data Visualization

Team A Appropriations Equity Data Science Project & Equity in Federal Budget Earmarking Processes FY24-25

SE
Client
Senator Ed Markey's Office
Government

The practice of congressionally directed spending (CDS), previously called “earmarks” describes a mechanism through which members of congress send discretionary spending directly to their district or state for a specific project such as funding an infrastructure project, an organization, or other local initiatives. FY22 was the first year of CDS funding after a decade without earmarks. This project seeks to create a repeatable process for analyzing the process of evaluating CDS requests through an equity lens. Building on the Work of Spring 2024 & Fall 2024 Projects: The Spring 2025 project will be an expansion of previous semesters’ work on a data visualization dashboard to help the Senator Markey office better understand where federal funding is being distributed across Massachusetts by merging the existing dashboard with 3 new datasets; • FY22 to FY24 CDS Awards for BU Spark • Updated Invest.gov data 12.18.2024 • Reworked Regional and Statewide Grants We will use CDS requests and earmarks interchangeably in this document. This project will follow requests through the following steps: Earmark/ CDS requests from Senator Markey’s constituents → Approved CDS requests from Senator Markey’s office put forward as sponsored requests to various committees → Committee approvals → CDS distributions to Senator Markey’s constituents The project will seek to apply an equity lens to this process and understand who is applying for earmarks and who they will benefit as well as who is NOT applying for CDS, i.e. who is not benefitting from this opportunity as well as who is getting approved and whether there are disparities at this stage of the process. We are specifically looking at equity through the lens of race

Where it ran
Fall 2024
Spring 2025
Spring 2025Tools for Data ScienceData Science
Spring 2025Spark! Data Visualization PracticumData Visualization
Fall 2024Tools for Data ScienceData Science
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