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
6Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2501822834
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Damiano Giallongo (semantic scholar, source metadata)
Topics and outcomes in this view
Assessment themes
- Inequality: 1 paper
- Labor Markets: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Automation Exposure: 1 paper
- Inequality: 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 |
|---|---|---|---|
| AI exposure is gendered: broader AI concentrates in high-paid, male-dominated occupations, but language models are relatively more prevalent across female-dominated roles — raising risks that lower-paid women could face disproportionate automation, wage compression and stalled career progression.semantic_scholar | Damiano Giallongo provider id |
2026-09-18 | 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.