Service data by race would identify a handful of people

The situation

A DSD analyst is asked to report service outcomes by race and language for a rural county. In several groups the count is below ten. Leadership wants the numbers next week.

What to notice first

• Small groups can be identified from aggregate tables.
• Suppression protects people and must be explained, not hidden.
• Qualitative evidence can carry what the numbers cannot.

Questions to ask before acting

1. What is the smallest group you will report, and who set that rule?
2. What will change based on the answer, and does that need the county-level cut?
3. What do people's accounts add where numbers are suppressed?

Practical next moves

• Measuring without surveillance — program page /resources/pn-measurement-without-surveillance
• Intersectionality foundations — program page /resources/lm-intersectionality-foundations

Who to involve

The data owner and your privacy lead set suppression rules. State the limits in the report.