# Introduction to Environmental Justice through EJ Screen

Temporarily rendered here: https://hutchdatascience.org/Environmental_Justice/

## Target Audience

This module is made to provide opportunities for students, especially underserved and minority students, at higher education facilities to explore and critically think about environmental justice data using EJScreen and other tools. It targets the lower division level (undergraduate) students, across a variety of disciplines (e.g., biology, social science). "Marketing" could focus on HBCUs, historically-women’s colleges, community colleges, etc. But, it is open to anyone and should be adaptable for that purpose.

### Dissemination Ideas
- Present idea at [ESA Life Discovery](https://www.esa.org/ldc/) education share fair
- Publish in education journal like [CourseSource](https://qubeshub.org/community/groups/coursesource/)
- Run a [QUBES hub](https://qubeshub.org/) site
- Apply for something like an [NSF IUSE](https://beta.nsf.gov/funding/opportunities/improving-undergraduate-stem-education-directorate) to gain funding to engage (i.e. pay) instructor to pilot the modules at different levels
- Share with colleagues at HBCUs, community-colleges, tribal colleges, etc.
- Share with networks ([BEDE Network](https://qubeshub.org/community/groups/bede), [EDSIN](https://qubeshub.org/community/groups/edsin/), [BLUE](https://www.biodiversityliteracy.com/), [EREN](https://erenweb.org/), etc.)

## Instructor Guide - Nate

We want to work **with** faculty to create something relevant to them. We will employ a model of feedback and continuous integration using surveys.

## Learning Outcomes

Learning outcomes by subject:
When students complete this module, they will be able to:

### STEM Courses

#### Tier 1 (Intro level)

- Explain how environmental indices can affect their community
- Evaluate the differences in the tools (EJScreen vs CEJST vs state-based(?) tools)
- And the benefits/drawbacks of the tools and how underlying data influences results (e.g., EJScreen uses census data - that is biased)
- Evaluate the positives and negatives of abstracting a place to one number
- Understand how weighting can impact results
- Question policy-makers and land managers on environmental justice issues
- Collaboratively develop action plans to move forward from their findings (wording of this sentence?)

*prerequisite knowledge*

none

#### Tier 2 (Mid level)

- Access data through R
- Execute pre-written example code and interpret the results
- Construct and modify R code to test hypotheses
- Choose a place and tell a story about why it is identified as an EJ place. What is missing? Is there a place that you thought would show up in EJ screen but does not? What data gap makes that happen?

#### Tier 3 (Upper Division)

- Work with
- Make maps with R of environmental data

### Social Science:

Geared towards students who:
* Never have made a map before

#### Tier 1:

* Explain how environmental data science tools reflect our understandings of race and can both perpetuate and challenge racism
* Interpret maps
* Navigate the EJScreen tool and/or other similar tools to answer relevant, student-generated research questions about environmental (in)justice
* Understand how these can benefit their own community and neighborhood

#### Tier 2:

#### Tier 3:

## Assessment

### Student assessment

- Exam questions
- Guided questions for any pre reading
- Guided worksheet for students throughout module
- Individual or collaborative project
- Low-pressure quiz questions

### Assessment & evolution of the module itself

- Survey of students pre- and post- course (self efficacy, excitement for data science, data science is relevant to me, etc)
- Survey of faculty/instructors that are actually teaching the course
- Incorporate feedback into further development of the module

# Module - Tier 1

When organizations/governments need to make decisions that impact communities, they have to take a lot of information and condense it. It is not practical to go out to every site and measure every environmental variable in every location that they want to make a decision about. It costs money and takes time, both of which are always limited. The government/organizations will often look to easily-accessible data to make decisions about whether/how to do potentially damaging actions that impact the environment.

We are going to show you one tool that people use to make decisions that can impact your community, [EJ Screen](https://ejscreen.epa.gov/). EJ Screen is an environmental justice screening and mapping tool.

Future Data Sources for similar modules:
- [Environmental Justice Index](https://www.atsdr.cdc.gov/placeandhealth/eji/index.html)
- [EJ Atlas](https://ejatlas.org/)
- [Climate Change data APIs](https://github.com/KKulma/climate-change-data)

# Module - Tier 2

# Module - Tier 3

# Appendix

## Resources

[ejscreen R package](http://ejanalysis.github.io/ejscreen/)

Google slides for instructor to give background: https://docs.google.com/presentation/d/1hGCkesvIgccjunUQzVRuHEp1aZNIDyMW9BdAonpN40M/edit#slide=id.p

Background readings (and/or intro lecture?) to frame:
* What is EJ and why is it relevant?
* What is EJScreen?
* Why was this tool created and how is it used (and by who)?
* What data was used/is used for the tool?
* What are the general outputs of the tool? - general * overview, diving into issues and understanding later

Google slides for lecture for class to give students background
Guided worksheet for readings to help students break them down (and key with example answers)
Clearly commented code that underlies the module with potential variations

Definitions and government resources: AY Environmental and Climate Justice Definitions and History WebQuest

Global Environmental Justice Atlas https://ejatlas.org/

There is page an EJScreen Office Hours & Training

This is a very helpful breakdown on EJ Screen

One activity could be to analyze EJ screen through algorithmic ecology: https://stoplapdspying.medium.com/the-algorithmic-ecology-an-abolitionist-tool-for-organizing-against-algorithms-14fcbd0e64d0

Example of citizen science x socially engaged art practices (listening to climate stories, documenting phenology:) https://phenology.umn.edu/

Pollinator / environmental awareness x art internship for youth https://plainsartbuzzlab.wixsite.com/buzzlab/about-us

Integrating indigenous science to learning promoting inclusive science https://futurumcareers.com/what-if-indigenous-science-were-part-of-the-science-curriculum

Environmental Justice Dashboards https://pubhealthgis.uic.edu/environmental-justice/