Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
1Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5135856725
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Victoria Matthews (openalex, provider refresh)
- Victoria Matthews (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Org Design: 1 paper
Claim outcomes
- Governance And Regulation: 1 paper
- Research Productivity: 1 paper
- Decision Quality: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| Current industry AI risk assessments are overly subjective; a socio‑technical framework translating organizational factors into measurable risk indicators can make governance demands for 'objectivity' operational — but it remains untested in practice.openalex | Victoria Matthews provider id |
2026-01-01 | 0 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.