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
3Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2444938984
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Guanlun Qiao (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Inequality: 1 paper
- Labor Markets: 1 paper
Claim outcomes
- Employment: 1 paper
- Other: 1 paper
- Inequality: 1 paper
- Task Allocation: 1 paper
- Wages: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar 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 |
|---|---|---|---|
| AI adoption in China’s manufacturing sector raises hiring and pay but deepens internal wage gaps; firms deploying AI show higher employment and wages, yet gains concentrate in technical and service roles while pay dispersion widens, with stronger job gains in regions with developed AI ecosystems and supportive policies.openalex | Guanlun Qiao provider id |
2026-06-26 | 0 |
Citation observation summary
Semantic Scholar 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.