cohort
Which population slices may be looked at
definition`: dimensions, membership rules and validity windows of cohorts · `floors`: minimum cohort sizes per sensitivity of the underlying data
This meta-model describes how the state of a population is sensed without exposing any person in it: statistics are computed over cohorts, never below a minimum cohort size, with suppression and noise where counts run thin. It is its own model because aggregation is a distinct trade with its own artifacts: cohort definitions, k-floors, noise budgets and disclosure review are reusable machinery that many consumers rely on, and the guarantees only hold if that machinery is modelled and checked in one place.
Which population slices may be looked at
definition`: dimensions, membership rules and validity windows of cohorts · `floors`: minimum cohort sizes per sensitivity of the underlying data
Turning members into numbers safely
measures`: statistics computed over cohorts and their methods · `protection`: cell suppression, noise addition and privacy budget accounting
What actually leaves
review`: pre-release disclosure checks against floors and budgets · `publication`: released series with method and provenance attached
Catalogue-native findings must describe the information grouped by each layer. This legacy version does not declare them separately.
Questions, artifact requirements and serial naming rules are required by Vercy vNext; they remain unassigned in this reference version.
Format-independent core. Concrete artifact formats and naming prefixes are not declared in this legacy version.
CRUD procedures and interface bindings are not declared in this legacy version.
A statistics office steward archetype operates the model within its statutory mandate: it computes and releases, but the underlying data stays with its owners, and the steward's own reads run under S2 contracts and land in the S4 log like anyone else's.