The final Project is optional. You will not be penalized for not completing the assignment. Rather, you will have the opportunity to:
- Work on a real-world, relevant example - the best way to learn data science.
- The chance to present to members of the White House Environmental Justice Advisory Council.
- A quick and efficient way to get an A+
The scope of the final project is to examine the most recent environmental justice score, published by the White House in February 2022. The score is exceedingly simple, effectively just a series of if-then statements with thresholds. For example:
IF at or above the 90th percentile for energy burden OR PM2.5 in the air AND is above the 65th percentile for low income AND at or below 20% for higher ed enrollment rate
The tool is imperfect. Can we, given the methods we've learned in this course, elucidate some of the limitations? Can we make a case for improving the tool, or even advocating for a totally different way to prioritize federal funding to address environmental injustice? Some more specific questions that may be addressed include:
- What aspects of environmental justices does the prioritization score miss?
- What are the characteristics of the communities that get left behind?
- There are some areas that are prioritized which are adjacent to other areas that are not. What are the differences between adjacent Census tracts which are prioritized versus those that are not?
- Suppose you find reports of environmental issues and underserved communities
The final product will be a Jupyter Notebook with a data narrative. Not just code. A proper narrative and description.
The final assessment will be subjective. You will either get an immediate A or we will just default to your grade based on your Lab assignments. You will be allowed to work individually or in groups of two.
The primary benefit of working on this assignment is not even necessarily the grade. If a team or individual finds something important and relevant, they will be invited to participate in a final report to one or two members of the White House Environmental Justice Advisory Council. You will also have the chance to work loosely with professional data scientists as very, very light mentors, including a former Engineering Manager at Lyft and an NYtimes-featured indigenous data scientist (both on staff at Earthrise).
Resources
- US Digital Service Github repository
- Justice40 datasets, including the input data for the score
- Climate and Economic Justice Screening Tool, including the description of the score