// scaffold.methodology
Scaffold Judgment Taxonomy Methodology & Lineage Appendix
This page documents the analytic basis of the PJRC judgment taxonomy used by Scaffold. It exists for auditors, compliance officers, ISACA reviewers, and CMMC assessors who need to verify the framework in five minutes. No marketing copy. The page is the credibility instrument.
Cluster Lineage
§ 1One row per judgment cluster. GWA codes reference O*NET Generalized Work Activity identifiers in the 30.3 release. Professional framework lineage reflects the recognized standards authority that anchors the cluster's occupational judgment requirements.
Greyed rows require data from the June 2026 Validation Report before publishing.
| Cluster | O*NET GWA Anchors | Professional Framework Lineage | AI-Exposure Stance | Defensibility Note |
|---|---|---|---|---|
| — Cluster 1 n roles | from validation report | from validation report | from validation report | from validation report |
| — Cluster 2 n roles | from validation report | from validation report | from validation report | from validation report |
| CA Compliance & Assurance n roles | from validation report | IIA International Professional Practices Framework (2024); AICPA SOC 2 Trust Services; ISACA IS Audit Standards; ISACA DTEF (ethics provisions) | AUGMENT-NOW | Evidence gathering is automatable; the independence requirement and professional skepticism standard are human-anchored per IIA Standard 1100 and ISACA IS Audit §3. Ethical judgment sub-dimension documented in Phase 4 (ABET Outcome (c), ISACA DTEF). |
| OP Operational & Process 4 roles | from validation report | Autor, Levy & Murnane (2003) routine/non-routine cognitive task taxonomy; APQC Process Classification Framework | AUGMENT-WATCH | Operational & Process judgment covers non-routine exception handling and process redesign — distinct from routine cognitive execution per ALM (2003). Cluster label is "the weakest defensively" (Validation Report); re-scoping underway in Phase 2. Role-level variance is high; label reflects modal pattern only. |
| — Cluster 5 n roles | from validation report | from validation report | from validation report | from validation report |
| — Cluster 6 n roles | from validation report | from validation report | from validation report | from validation report |
| — Cluster 7 n roles | from validation report | from validation report | from validation report | from validation report |
Note: The OP cluster framing is being tightened in Phase 2 to make explicit the non-routine/routine distinction. Current label: "AUGMENT-WATCH — modal task-level tendency, see methodology." This table reflects the v1.0 baseline prior to that update.
AI Exposure Label Definitions
§ 2Exposure is measured at the task level. Cluster-level labels represent the modal pattern across roles in the cluster — not a determination about the role itself. Each label will carry a tooltip in the Occupation panel: "AI exposure is measured at the task level. Cluster-level labels represent the modal pattern across the role's tasks, not a determination about the role itself."
Modal task pattern protected by social, creative, or relational bottlenecks not decomposable into routine cognitive sequences. AI substitution probability is low across current deployment horizons.
High task-level AI exposure on execution and monitoring tasks, but professional accountability and final judgment authority remain human-anchored by framework requirement or regulatory standard.
Mixed task-level exposure. Modal pattern unclear or trajectory is rapidly shifting. Cluster-level label is provisional — revalidate at 18-month intervals against O*NET updates and AI capability benchmarks.
Modal task pattern is routine-cognitive per ALM (2003) taxonomy. High probability of significant workflow restructuring within current deployment horizon. No cluster carries this label at v1.0.
Citation Index
§ 3- 1. [ONET-30.3] O*NET 30.3 (released October 2024). U.S. Department of Labor / Employment and Training Administration. Primary data foundation for all 25 roles and 7 cluster GWA mappings. online.onetcenter.org
- 2. [ALM-2003] Autor, D., Levy, F., & Murnane, R. (2003). "The Skill Content of Recent Technological Change: An Empirical Exploration." Quarterly Journal of Economics, 118(4), 1279–1333. Routine vs. non-routine task framework — basis for OP cluster re-scoping.
- 3. [FREY-OSBORNE-2013] Frey, C.B. & Osborne, M.A. (2013). "The Future of Employment: How Susceptible Are Jobs to Computerisation?" Oxford Martin Programme on Technology and Employment. Vocabulary anchor for AI exposure framing. Specific probability estimates not used.
- 4. [ELOUNDOU-2023] Eloundou, T., Manning, S., Mishkin, P. & Rock, D. (2023). "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models." Science, 384(6702). Task-level exposure methodology; basis for AUGMENT-NOW label criteria.
- 5. [FELTEN-2023] Felten, E., Raj, M. & Seamans, R. (2023). AI Occupational Exposure (AIOE) index. Low-substitution quartile placement referenced in RESILIENT label defensibility.
- 6. [ANTHROPIC-2025] Anthropic Economic Index (2025–2026). Observed augmentation vs. automation patterns across task categories. Used for AUGMENT-NOW / AUTOMATE-EXPOSED boundary calibration.
- 7. [BROOKINGS-2019] Muro, M., Whiton, J. & Maxim, R. (2019). "What Jobs Are Affected by AI?" Brookings Institution. Adaptive Capacity Index precedent (Phase 5 design input, not implemented at v1.0).
- 8. [ABET-2025] ABET Criteria for Accrediting Engineering Programs (2025–2026), Criterion 3 Student Outcomes (c) and (f). Ethical judgment separation precedent for Phase 4 CA sub-dimension.
- 9. [ISACA-DTEF] ISACA Digital Trust Ecosystem Framework (DTEF). Ethics provisions cited as lineage for CA cluster Ethical Judgment sub-dimension (Phase 4).
scaffold.cubelet.ai / PJRC Judgment Taxonomy v1.0 · O*NET 30.3 anchor · Maintained by GRID42 · Last reviewed June 2026
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