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
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5089948231
ORCID evidence
Observed aliases (2)
- Carlo Perrotta (openalex, provider refresh)
- Carlo Perrotta (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Labor Markets: 1 paper
- Org Design: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Task Allocation: 1 paper
- Governance And Regulation: 1 paper
- Market Structure: 1 paper
- Ai Safety And Ethics: 1 paper
- Organizational Efficiency: 1 paper
- Regulatory Compliance: 1 paper
- Skill Acquisition: 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 |
|---|---|---|---|
| Off‑the‑shelf LLMs remain structurally general-purpose even after customization, and embedding them in government prototypes like Redbox creates persistent governance, procurement and cultural frictions; these dynamics shift public‑sector labor toward oversight and vendor‑management roles and raise regulatory and lock‑in costs that may blunt efficiency gains.openalex | Carlo Perrotta provider id |
2026-09-09 | 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.