Evidence-Anchored Metaprompting for Competitive Epistemic Positioning: A Framework for Capability Assessment Under Evidentiary Constraints in High-Stakes Professional Contexts
A rigorous metaprompt specification that instructs AI systems to conduct evidence-anchored assessments of candidate suitability for competitive technical positions. This framework enforces epistemic discipline through evidence-limitation constraints, distinguishing between "Not Evidenced" and "Absent" capabilities. Includes structured gap analysis, competitive positioning rubrics, and application materials generation pipeline. Compliant with CARP v1.0, CEPM, and Furlow License v2.0. Validated against the requirements of competitive AI safety and intelligence analyst roles; extensible to any high-stakes professional evaluation context requiring evidence-bounded work sample portfolios.
Authors
- Ariel J. Furlow
Institutions
- Nova Research Company (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-02-23
- DOI
- https://doi.org/10.5281/zenodo.18742218
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00