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
4Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2314109809
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Aylin Caliskan (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
- Task Completion Time: 1 paper
- Decision Quality: 1 paper
- Governance And Regulation: 1 paper
- Hiring: 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 recommendations shorten resume review and blunt the benefits of extra scrutiny: without recommendations, extra viewing raises selection odds by about 3–4% and reviewers spend up to 55.6% longer inspecting resumes; completing an implicit-bias test beforehand reduces racial disparities in review time and predicts how people engage with AI screening.arxiv | Aylin Caliskan provider id |
2026-06-20 | 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.