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
5Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5100919939
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Li Fangyu (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Inequality: 1 paper
- Labor Markets: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Wages: 1 paper
- Inequality: 1 paper
- Other: 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 |
|---|---|---|---|
| Specialized digital skills pay off: workers with vocational data, programming or automation expertise earn roughly 14% more—far above the 6% premium for general digital literacy—and the reward is largest in Korea's big Chaebol where the premium approaches 19%, while advanced skills help TVET graduates close the gap with university peers.openalex | Li Fangyu provider id |
2026-03-14 | 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.