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:
A5125167918
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Ye Emma Wang (openalex, provider refresh)
- Ye Emma Wang (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Inequality: 1 paper
Claim outcomes
- Task Allocation: 1 paper
- Other: 1 paper
- Inequality: 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 |
|---|---|---|---|
| Language models steer money unevenly: while fund picks are broadly consistent across investor types, LLMs recommend different investment sizes and allocate more capital to non-Black and male managers—biases that are often stronger when demographics are signaled implicitly by names.openalex | Ye Emma Wang provider id |
2026-02-06 | 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.