Lesson 2: Who Is Missing From the Data?

About 30 minutes — Activity-based lesson

What You Will Learn

This lesson covers:

Who gets counted and who gets left out
Invisible populations: people without internet, without addresses, without documentation
How missing representation leads to wrong conclusions
Activity: examine a dataset and identify who might be missing

Who gets counted and who gets left out

This section covers the key ideas about who gets counted and who gets left out. Discuss with your group or family and explore the concepts together.

Invisible populations: people without internet, without addresses, without documentation

This section covers the key ideas about invisible populations: people without internet, without addresses, without documentation. Discuss with your group or family and explore the concepts together.

How missing representation leads to wrong conclusions

This section covers the key ideas about how missing representation leads to wrong conclusions. Discuss with your group or family and explore the concepts together.

Activity: examine a dataset and identify who might be missing

This section covers the key ideas about activity: examine a dataset and identify who might be missing. Discuss with your group or family and explore the concepts together.

Check Your Understanding

1. Why are some people missing from data?

Answer: Because data collection often relies on internet access, fixed addresses, phone numbers, or participation in institutions. People without these are systematically undercounted.

2. What happens when groups are missing from data?

Answer: Decisions based on that data ignore their needs. Medical treatments tested mostly on men may not work the same for women. Products designed for one skin tone may not work for others.

3. How can we include missing voices?

Answer: By actively seeking out underrepresented groups, using multiple collection methods, partnering with communities, and always asking 'who is not represented here?'

4. What is the connection to Amana (stewardship)?

Answer: Just as Amana teaches us to care for what is entrusted to us, data stewardship means responsibly including and protecting all people in our data practices.

Key Takeaways

Who gets counted and who gets left out
Invisible populations: people without internet, without addresses, without documentation
How missing representation leads to wrong conclusions
Activity: examine a dataset and identify who might be missing

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