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 →
2Distinct papers
2Unique collaborators
2/2Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
23985569
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- F. Stephany (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Labor Markets: 2 papers
- Skills Training: 2 papers
- Adoption: 1 paper
- Inequality: 1 paper
- Productivity: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Skill Acquisition: 1 paper
- Employment: 1 paper
- Ai Safety And Ethics: 1 paper
- Automation Exposure: 1 paper
- Inequality: 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 |
|---|---|---|---|
| Workers who pair specialised expertise with cross-domain skills — those on the 'diversity frontier' — learn faster, gain promotions and move into lower-automation roles; specialising or generalising alone is less adaptive.arxiv | F. Stephany provider id |
2026-08-03 | 0 |
| Women in the UK lag men in generative-AI adoption largely because they worry more about societal risks—not because of access or skills; boosting optimism about AI could raise young women's GenAI use from about 13% to 33%, markedly narrowing the gender gap.semantic_scholar | F. Stephany provider id |
Fetched 2026-03-15 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 2 of 2 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.