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: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5121619373
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Zihan Dong (openalex, provider refresh)
- Zihan Dong (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Labor Markets: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Other: 1 paper
- Governance And Regulation: 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 |
|---|---|---|---|
| Generative AI is reshaping city labor markets by changing the tasks people do, not simply cutting jobs: fine-grained vacancy and firm-adoption data from 2018–2025 show skill bundles shifting toward collaboration and coordination as GenAI diffuses across cities.openalex | Zihan Dong provider id |
2025-12-31 | 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.