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
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5103032035
ORCID evidence
Observed aliases (4)
- Sarah Roberts (openalex, provider refresh)
- Sarah Roberts (openalex, source metadata)
- Sarah T. Roberts (openalex, provider refresh)
- Sarah T. Roberts (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Human Ai Collab: 1 paper
- Inequality: 1 paper
Claim outcomes
- Inequality: 1 paper
- Ai Safety And Ethics: 1 paper
- Consumer Welfare: 1 paper
- Governance And Regulation: 1 paper
- Market Structure: 1 paper
- Worker Satisfaction: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex 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 |
|---|---|---|---|
| Treating people as data entrenches inequality: a multidisciplinary review finds that mainstream AI and design practices simplify sociocultural complexity into labels and metrics, reproducing historical injustices and shifting harms onto multiply marginalized groups; the paper urges participatory, disaggregated impact assessment and intersectional welfare frameworks for policy and economic analysis.openalex | Sarah T. Roberts provider id |
2026-07-30 | 0 |
Citation observation summary
OpenAlex 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.