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
- Semantic Scholar:
2443859571
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Mehmet Arif Koşar (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Labor Markets: 1 paper
- Productivity: 1 paper
Claim outcomes
- Employment: 1 paper
- Other: 1 paper
- Job Displacement: 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 |
|---|---|---|---|
| Contrary to alarmist accounts, automation has often increased employment: highly automated countries in the reviewed literature show rising numbers and shares of workers, driven by productivity gains, higher real incomes and the creation of complementary and new jobs.openalex | Mehmet Arif Koşar provider id |
2026-06-21 | 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.