Automated quality control
Data Audit
The website audits canonical files at build time for schema gaps, duplicate keys, country coverage, year coverage, missingness and unexpected provenance labels.
Data pipeline readyAdd the two canonical master CSVs to
data/raw/. The site will populate automatically on the next build.Data status →Latest schema
Missing: iso3, country, asof_year, identity_z, identity_level, identity_rank, identity_20y, identity_3y, identity_source, drive_z, drive_level, drive_rank, drive_20y, drive_3y, grit_z, grit_level, grit_rank, grit_20y, grit_3y, combo_avg_z, combo_avg_level, combo_avg_rank, combo_avg_20y, combo_avg_3y, combo_mult, combo_mult_rank, combo_mult_20y, combo_mult_3y, identity_core_z, identity_core_provenance, identity_fracture_z, openness_exposure_z, openness_exposure_provenance
Latest duplicates
No duplicate ISO3 keys detected.
Historical duplicates
No duplicate country-year keys detected.
Key-field missingness
| Latest field | Missing | Historical field | Missing |
|---|---|---|---|
identity_z | — | identity | — |
drive_z | — | drive | — |
grit_z | — | grit | — |
combo_avg_z | — | combo_avg | — |
identity_fracture_z | — | identity_fracture | — |
openness_exposure_z | — | openness_exposure | — |
Identity provenance — latest
{}Openness provenance — historical
{}Audit scope: passing these checks means the files match expected structural rules. It does not prove the underlying source data or model is substantively correct; statistical validation remains separate.