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Coverage

56,681 of 56,681 columns decided — 100.0% · 12,642 bound (22.3%) · 0 still unread

Bound: 12,642; 22.3%; a concept was found and asserted for the column.
Refused: 32,953; 58.1%; the column was read and no concept fits. A verdict, not a gap.
Insufficient: 11,086; 19.6%; read, but the evidence did not settle it.
Unanalysed: 0; 0.0%; nobody has read this column yet.

56,681 columns in the coverage ledger · read from /api/field-coverage on citytap-prod · source last observed Oct 11, 2026, 3:37 AM

3,026 datasets, 56,681 catalogued fields, 0 of them still unread. Every band below is a share of that, worst first. Open one to see its datasets.

School Zones 2024-2025 (High School)

ruu9-egea

Fields catalogued

Understood

Checked, no match

Nobody has looked

Every field decided — Every field carries a verdict — which does not mean every field is understood.

Every field in this dataset

Covered and uncovered alike, in the order the publisher lists them. A field with no verdict is one nobody has looked at yet.

Field	Type	What we know	Meaning	How it was decided	Shared term
sch_name SCH_NAME	Text	Checked, no match	—	value_domain_read Citywide High School Choice×48	—
boro Boro	Number	Understood	place.borough Borough	value_domain_read	borough
the_geom	MultiPolygon	Understood	geometry.area Areal geometry	dictionary_read Geospatial column used for mapping	—
boro_text Boro_Text	Text	Understood	place.borough Borough	dictionary_read Letter code for the NYC borough	—
hsid_no HSID_No	Number	Checked, no match	—	dictionary_read Unique internal identifier	—
catchment CATCHMENT	Number	Checked, no match	—	value_profile card=2 nonnull=80 null=0 smallest=0 largest=1 top[2]={0×44; 1×36}	—
zoned_dist ZONED_DIST	Text	Not enough to tell	—	value_profile	—
schooldist SCHOOLDIST	Text	Not enough to tell	—	value_profile	—
dbn DBN	Text	Understood	identifier.school_dbn School DBN	value_profile District Borough Number	—
label Label	Text	Checked, no match	—	value_domain_read smallest=08X405 largest=31R460	—
remarks Remarks	Text	Checked, no match	—	value_profile top[1]={Citywide High School Choice×48}	—
initials INITIALS	Text	Understood	actor.person_name Person name	dictionary_read_underspecified Initials of the person creating the zone	—
edit_date EDIT_DATE	Calendar date	Understood	time.period.month Month	value_profile Date the zone was edited	—