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
1/1Semantic Scholar citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2303903894
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- N. Reznikova (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Inequality: 1 paper
- Innovation: 1 paper
- Labor Markets: 1 paper
- Productivity: 1 paper
Claim outcomes
- Market Structure: 1 paper
- Fiscal And Macroeconomic: 1 paper
- Organizational Efficiency: 1 paper
- Automation Exposure: 1 paper
- Firm Productivity: 1 paper
- Governance And Regulation: 1 paper
- Inequality: 1 paper
- Social Protection: 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 |
|---|---|---|---|
| AI agents could sever the centuries-old link between population trends and GDP growth by acting as economic actors in their own right, creating an expanding 'algorithmic' population and new pressures on pensions, taxation and international competitiveness. Policymakers must measure agent productivity (cFTE), energy use (AEP) and reconsider fiscal and market rules to manage the geoeconomic and social consequences.semantic_scholar | N. Reznikova provider id |
Fetched 2026-05-02 | 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.