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:
A5147458217
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Yiran Li (openalex, provider refresh)
- Yiran Li (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Inequality: 1 paper
- Labor Markets: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Employment: 1 paper
- Innovation Output: 1 paper
- Adoption Rate: 1 paper
- Automation Exposure: 1 paper
- Inequality: 1 paper
- Skill Acquisition: 1 paper
- Task Allocation: 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 |
|---|---|---|---|
| Cities with dense skill networks absorb AI shocks by reallocating workers into skill-adjacent jobs, but the process raises inequality; sparse-network rural areas and compute-poor developing regions lack local alternatives and risk prolonged job and participation losses unless policy invests in infrastructure, skill connectivity and portable protections.openalex | Yiran Li provider id |
2026-08-19 | 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.