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: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2402549088
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Deborah Elohozino Otighi (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
- Governance And Regulation: 1 paper
- Adoption Rate: 1 paper
- Employment: 1 paper
- Other: 1 paper
- Automation Exposure: 1 paper
- Fiscal And Macroeconomic: 1 paper
- Inequality: 1 paper
- Innovation Output: 1 paper
- Market Structure: 1 paper
- Skill Acquisition: 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 |
|---|---|---|---|
| Robot taxation is a blunt instrument for Nigeria: it could buy time for workers and raise revenue but risks hampering innovation and driving production abroad; for now, modest fees paired with retraining incentives and infrastructure investment are the pragmatic alternative.openalex | Deborah Elohozino Otighi provider id |
2025-12-27 | 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.