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
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
No provider ID is stored.
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Zi-On Lee (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Inequality: 1 paper
- Labor Markets: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Automation Exposure: 1 paper
- Employment: 1 paper
- Hiring: 1 paper
- Inequality: 1 paper
- Other: 1 paper
- Skill Acquisition: 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 |
|---|---|---|---|
| Graduate employability depends less on standalone skills than on whether employers believe a candidate's net value justifies higher local costs and cannot be readily replaced by lower-cost workers or AI; the proposed VALUE Framework offers practical levers—verifiable productivity, adaptive skill-stacking, local intelligence, unoutsourceable capabilities and employer‑relevant signalling—to lower perceived substitutability.openalex | Zi-On Lee unresolved |
2026-09-01 | 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.