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
3Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2277754585
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Marco Rondina (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Inequality: 1 paper
- Labor Markets: 1 paper
Claim outcomes
- Hiring: 1 paper
- Ai Safety And Ethics: 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 |
|---|---|---|---|
| A GPT-5 audit finds similar job and industry recommendations for simulated male and female applicants but uses markedly gendered language — women described as empathetic and relational, men as analytical and leadership-oriented, raising fairness concerns for AI-assisted hiring.arxiv | Marco Rondina provider id |
2026-03-12 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 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.