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
0Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5137211344
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Obi Ogbanufe (openalex, provider refresh)
- Ogbanufe, Obi (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Labor Markets: 1 paper
Claim outcomes
- Governance And Regulation: 1 paper
- Ai Safety And Ethics: 1 paper
- Adoption Rate: 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 |
|---|---|---|---|
| New York’s mandated bias audits for hiring algorithms are weakened by major demographic data gaps—missingness in audit reports ranges from under 3% to over 50%—undermining the validity of reported fairness metrics. The authors argue many audits risk being symbolic and recommend using audit outputs for red‑teaming, improved data quality, and stronger oversight to make audits meaningful.openalex | Ogbanufe, Obi provider id |
2026-06-14 | 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.