GSCO: The Global Standard Classification of Occupations — A Deterministic Multilingual Database to Solve the N² Cross-Table Problem in International Occupation Classification
GSCO: The Global Standard Classification of Occupations — A Deterministic Multilingual Database to Solve the N² Cross-Table Problem in International Occupation Classification
GSCO (Global Standard Classification of Occupations) is a deterministic multilingual database that aggregates 129 national occupation classifiers into a single ISCO-08-aligned structure to expose and resolve cross-table incoherence. The paper documents the methodology, audits 22 common professions across all 9 ISCO major groups, and demonstrates concrete cases where national taxonomies diverge irreconcilably from ISCO-08 — including renumbered major groups (South Africa OFO 2017), parser-truncation bugs (Brunei BDSOC), and absent occupations (Togo zemidjan moto-taxi, Honduras moto-taxi forestal, Guatemala bicitaxis). Includes worked examples for ISCO 2221 (nurses vs financial brokers vs medical doctors), the universal teacher/taxi-driver case, and recommendations for the ILO's ISCO-28 working group (active revision phase 2026–2028). Open dataset and per-country reports at https://gsco.io. Repository: https://github.com/Reincarnatiopedia/gsco
yoga instructor classification, moto-taxi, Zemidjan, occupation correspondence, ILO, P106, YAMAT-08, open data, cross-table problem, OZMST, International Labour Organization, BDSOC, multilingual occupation labels, open registry, taxi driver classification, global classification, ISCO-08, UEMOA, Maris Dreshmanis, occupation classification, International Standard Classification of Occupations, KldB, ISCO sub-major group, ISCO minor group, employment classification, occupation data quality, migrant credentials, qualification recognition, ISCO unit group, Šifarnik, occupation crosswalk, N-squared problem, Academy of Reincarnationology, Global Standard Classification of Occupations, JSCO, Reincarnatiopedia, occupation data harmonization, RGPH, GSCO, AFRISTAT, labor statistics, bicitaxis, ISCO-28, skill level, hypnotherapist classification, teacher classification, ROME, Wikidata bot, ISCO, national occupation registries, ANZSCO, labour statistics, professional mobility, KZBiH-08, AK-2008, occupation taxonomy, Wikidata occupations, cross-classifier mapping, Māris Drešmanis, deterministic dataset, OFO 2017
yoga instructor classification, moto-taxi, Zemidjan, occupation correspondence, ILO, P106, YAMAT-08, open data, cross-table problem, OZMST, International Labour Organization, BDSOC, multilingual occupation labels, open registry, taxi driver classification, global classification, ISCO-08, UEMOA, Maris Dreshmanis, occupation classification, International Standard Classification of Occupations, KldB, ISCO sub-major group, ISCO minor group, employment classification, occupation data quality, migrant credentials, qualification recognition, ISCO unit group, Šifarnik, occupation crosswalk, N-squared problem, Academy of Reincarnationology, Global Standard Classification of Occupations, JSCO, Reincarnatiopedia, occupation data harmonization, RGPH, GSCO, AFRISTAT, labor statistics, bicitaxis, ISCO-28, skill level, hypnotherapist classification, teacher classification, ROME, Wikidata bot, ISCO, national occupation registries, ANZSCO, labour statistics, professional mobility, KZBiH-08, AK-2008, occupation taxonomy, Wikidata occupations, cross-classifier mapping, Māris Drešmanis, deterministic dataset, OFO 2017
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