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
0Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2363155923
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- D. Priya (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Inequality: 1 paper
- Labor Markets: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Inequality: 1 paper
- Employment: 1 paper
- Governance And Regulation: 1 paper
- Hiring: 1 paper
- Market Structure: 1 paper
- Organizational Efficiency: 1 paper
- Skill Acquisition: 1 paper
- Skill Obsolescence: 1 paper
- Task Allocation: 1 paper
- Task Completion Time: 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 hiring tools accelerate and cheapen recruitment for firms in India but rewire access to entry-level jobs: opaque filtering and a premium on digital signals disadvantage many fresh graduates and marginalized applicants, risking greater inequality and urban concentration of opportunities.openalex | D. Priya provider id |
2026-08-05 | 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.