Climates of Resistance

Environmental Racism and Collective Action

Week 3

Measuring Inequality

Feedback: Identity Introspections, Part I

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• really great work, all in all - thank you for sharing!�
• make sure that you always read the entirety of the assignment brief �(points were only missed for the sub-point of criteria #5 asking you to consider some of your goals for this semester/motivation for being in this class)�
• If you’re unsure of any of the feedback or scores, let me know; �I’m happy to discuss further!�

Session 3A: Understanding Statistics

to appreciate the need for evidence-based policymaking around environmental justice issues

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agenda:

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• launching Unit 2 on Disparate Distribution�
• review of demographics from Learning Logs�
• statistical literacy workshop�

Demographics

What are ‘demographics’?

What’s with the census?

There are some questionable origins…

It’s not just America!

What’s at stake?

Lies, damned lies, and statistics

Can we trust demographic statistics?

numbers can go wrong at several points:

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• collection�
• analysis�
• communication

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and this may happen intentionally or unintentionally...

Where could demographics go wrong?

Issue #1: Undercounting Groups

Issue #1: Undercounting Groups

from your Learning Logs:�

• “‘the value of filling out a census form at over $4,000’ is a shocking statistic”�
• “undercounted communities affected by environmental hazards will receive less funding, leaving them even more vulnerable to environmental risks”�

Issue #2: Engineering Numbers

remember that race is socially constructed - and can be politically altered

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• blood quantums�
• one-drop rule�

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Issue #2: Engineering Numbers

remember that race is socially constructed - and can be politically altered

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• blood quantums�
• one-drop rule�

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from your Learning Logs:�

• “both 'blood quantums' for Indigenous tribes and the 'one-drop rule' for Black people in America work to enforce racial boundaries, limit opportunities & resources for marginalized groups, and serve the interests of those in power”�
• “I didn’t know that the concept of ‘passing’ came from this rule.”�
• “could easily contribute to oppression wars”

Issue 3: Distrusting Surveys

Issue 3: Distrusting Surveys

from your Learning Logs:�

• “I honestly feel a little bit less educated on racism issues than I might have thought before”�
• the push and pull creates an impossibility for marginalised groups…how can they ‘win’?

Issue #4: Changing Categories

sometimes it’s not malicious…

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• who is ‘Hispanic’?�

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but when words and their meaning change, so too will reported numbers

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Issue #4: Changing Categories

sometimes it’s not malicious…

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• who is ‘Hispanic’?�

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but when words and their meaning change, so too will reported numbers

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from your Learning Logs:�

• “census data has value only in relation with other statistics/studies” [note from Becca: true of most all information, really…]�

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Issue #5: Contexts and Resources

What do other countries do?

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different categories; different capacities for counting and collecting

Common Missteps �with Statistics

Error #1: Correlation and Causation

Error #1: Correlation and Causation

• correlation: a statistical relationship between two variables�
• causation: a dependent relationship between two variables�
• ≠

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Error #1: Correlation and Causation

tylervigen.com/spurious-correlations

divorce rate in Maine correlates (0.993) with the per capita consumption of margarine...

divorce rate

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consumption of margarine

Error #1: Correlation and Causation

biostat.jhsph.edu/courses/bio621/misc/Chocolate%20consumption%20cognitive%20function%20and%20nobel%20laurates%20(NEJM).pdf

Error #2: Mixing Sources and Methods

biostat.jhsph.edu/courses/bio621/misc/Chocolate%20consumption%20cognitive%20function%20and%20nobel%20laurates%20(NEJM).pdf

martingrandjean.ch/nobel-chocolate-correlation

Error #3: Comparing Apples and Oranges

• mixing units�
• mixing scales�

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Error #4: Misunderstanding Scale

Scroll...and then keep scrolling…

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tinyurl.com/scale-3a

Error #4: Misunderstanding Scale

Error #4: Misunderstanding Scale

a trillion is one thousand billion…

this Tweet critique is not accurate

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one million = one thousand thousand

1,000,000

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one billion = one thousand million

1,000,000,000

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one trillion = one million million

1,000,000,000,000

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giving 7.5 billion people 1 billion each:

7,500,000,000,000,000,000

the general principle of the Tweet is entirely reasonable - but getting the maths wrong provides ammunition to claims that environmental racism isn’t real, the class divide isn’t as big a problem as people say, etc.

Error #4: Misunderstanding Scale

Error #5

Error #5: Aggregating “Average”

statnews.com/2021/02/18/u-s-life-expectancy-fell-�by-a-year-in-the-first-half-of-2020-cdc-report-finds

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Error #6: Ignoring Context

All models are wrong…

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...but some are useful

All models are wrong...

Demographic statistics are like maps and models: they represent things. In doing so, they -

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• simplify the world�
• reduce multifaceted identities to one-dimensional factors �
• become easily open to misinterpretation

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What do statistics do?

...but some are useful

• they help us understand the world (accurately, so long as they’re done right)�
• they bring attention to important issues�
• they guide decision-making

Why are statistics important?

Session 3B: Appraising Access

to identify realities in the (mis)use and provision of food, water, energy, and other resources

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agenda:

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• identification of contemporary patterns in environmental racism�
• consideration of how numbers are used to impact change�
• preparation for Statistical Story assignment

The Navajo Water Project

a partial telling of Diné Bahaneʼ, the Navajo origin story

Statistical Story Preparation

The Navajo Water Project

grab a piece of paper and sketch one of these statistics:

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• more than 30% of Navajo families don’t have running water in their homes��
• 27% of the Navajo Nation have high levels of uranium in their urine��
• only 1/52 Secretaries of the US Interior have been Indigenous

The rules:

• You need to visually represent the statistic
• No words or numbers can appear on your paper
• You can use any kind of graphic set-up you want, but you won't be able to explain anything to the viewer
• The quality of your drawing/artistic skill level does not matter, I promise - this is about the creative idea behind how to visually represent the number

The Navajo Water Project

contextualise the statistics

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• more than 30% of Navajo families don’t have running water in their homes
• more than 2/3 of water systems in WV have the worst quality in the US�
• 27% of the Navajo Nation have high levels of uranium in their urine� nationally, it’s just 5%
• where is the study from? how big is sample size?�
• only 1/52 Secretaries of the US Interior have been Indigenous
• 2.09% of the US population is Native American

Looking Ahead:

Assignment Overview

tell me a story...

Our second unit explores trends in environmental racism, looking at Disparate Distribution in environmental access and allocations, risks and resources.

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Your primary assignment for this unit asks you to summarise your learning by:

1. identifying a statistic that is particularly meaningful or shocking;
2. using that data to communicate the reality of contemporary environmental injustice to a non-academic audience via visual representation; and
3. writing a news-style report contextualising the information and its validity.

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This assignment will support you in achieving Learning Objective 3: � Evaluate evidence-based patterns of environmental racism.

Example Infographic

Example Infographic

visuals that represent the numbers

label/explainer of the statistic (measurement, population parameters)

graphic credits

missing: citation!

should link ncbi.nlm.nih.gov/pmc/articles/PMC5323239/

text annotations

Example Infographics

stories here and here

story here

Example Infographics

story here

story here

Assignment Requirements

• identify an evidence-based trend in environmental racism �at least one statistic; ideally, several that confirm the same pattern (like having multiple people giving you quotes for a news article)�
• evaluate quantitative claims about systemic injustice �why and how is this reliable (“it’s a well-known source” won’t cut it; think about methodology)�
• communicate statistics in a visually appealing manner �you aren’t being graded for graphic skills, but the image should correspond to the information�
• tell a ‘story’ through data �make me care and tell me what the numbers mean�
• share information in an accessible way for diverse audiences�think about which terms to use, and how to convince doubters

Preparation for Next Session

• Week 4 Learning Log on “Exposing Hazards” completed��
• let us know how things are going via the Feedback Form��
• feel free to explore these issues more with Becca during Office Hours

See you next week!