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
2Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5127825983
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- A. Е. Zhanabay (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Inequality: 1 paper
- Labor Markets: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Employment: 1 paper
- Other: 1 paper
- Governance And Regulation: 1 paper
- Inequality: 1 paper
- Research Productivity: 1 paper
- Firm Productivity: 1 paper
- Job Displacement: 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 |
|---|---|---|---|
| AI's aggregate effect on jobs so far has been modest — no mass unemployment — but its gains are uneven: productivity rises concentrate with skilled workers while routine and low-skill roles face displacement, heightening labor-market polarization and calls for targeted upskilling and policy support.semantic_scholar | A. Е. Zhanabay provider id |
Fetched 2026-03-10 | 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.