simd2020v2_population

Population of the data zone in the SIMD 2020v2 shapefile (NRS small-area estimates for 2017), the weight behind the computed bands. The data zone's figure, repeated on every postcode in the zone; never sum it or weight by it across rows

Table	Type	Nullable	Category	In the CSV export	SQL Server type
history table (postcode_simd_history, SPD)	int16	no	Scottish Government SIMD	yes	smallint
main table (postcode_simd, SSPL)	int16	no	Scottish Government SIMD	yes	smallint

Provenance (the same in both tables)

Each table runs its own copy of the table-level checks, named .history. and .main..

Where it comes from

Input	Field	Condition	Reaches the row by
data.gov.uk/SG_SIMD_2020/SG_SIMD_2020.dbf (pinned, SHA256 3eb0f27aa4aa…)	sape2017: 2017 NRS small area population estimates (SIMD 2020v2 glossary; reviewed (AI-assisted review, 2026-10-02, record))		DataZone2011Code = datazone

Scope: the row itself.

What was done to it: copied. The data zone's population in this edition's shapefile, the weight behind the computed bands; the zone's figure on every postcode in it. (code: simd_ingest/core/govscot.py: read_gov_edition)

How it is checked (what each check tests; whether a build passed it is in that build's manifest.json["checks"])

• source.hash.data.gov.uk/SG_SIMD_2020/SG_SIMD_2020.dbf: the pinned file's SHA256 equals the registry's: the bytes are exactly the ones reviewed
• govscot.2020v2.columns_present: every declared shapefile column is in the file
• govscot.2020v2.key_unique: each data zone appears once in the shapefile table
• join.<table>.gov.2020v2.every_record_matched: every record found its data zone in the edition: no empty cell
• readback.<table>.attached_values: every attached value in the saved file is looked up again from the sources and equal
• govscot.2020v2.population.integral: every population is a whole number
• govscot.2020v2.population_nonnegative: no population is negative

Why: computed-weighted-domain-bands