Earlier today I reported that URBANIZATION--DOU_CITY recovers peer-city comparison and recommended it as the primary framing. That was an over-generalisation from the one indicator I tested it on. Scoping it properly changes the picture.

Scanned 23 topic areas, 5,320 variables. Indicators carrying a DOU_CITY slice: five.

• undata/sdg/EN_ATM_PM25 — PM2.5
• undata/unicef/DM_BU_PC_DOU — built-up area per capita
• undata/unicef/DM_POP — population
• undata/sdg/AG_PRD_FIESS / AG_PRD_FIESMS — food insecurity

They cluster in indicators derived from gridded geospatial data (the GHSL settlement layer), which is the only family where a national figure can be cut by settlement type. Homicide, waste, unemployment, poverty and renewable energy have no such dimension and will not get one — they come from administrative reporting with no spatial component.

About eight more indicators carry only DOU_U (urban vs rural). DEGURBA “urban” bundles cities with towns and suburbs, so it is a coarser class, and the indicators it covers skew toward electricity access, handwashing and open defecation — little NYC relevance. Slums and school completion are the exceptions.

The comparator is tiered, not general

Tier	Comparator	Coverage
1	NYC vs national city aggregates, many countries	~5 indicators
2	NYC vs national urban aggregates	~8, mostly low NYC relevance
3	NYC vs national totals	everything else — the large majority

Tier 1 is real and PM2.5 is an excellent demo of it. The general case is still Tier 3.

That is arguably a better story than “we found city-level UN data.” It means the tool’s core job is telling a user which tier they are in and what that permits them to claim. A naive dashboard renders all three tiers as identical bar charts, and that is precisely the failure we are building against.