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
5Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5133733934
ORCID evidence
Observed aliases (2)
- O. M Kulhanik (openalex, provider refresh)
- Оксана КУЛЬГАНІК (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Adoption Rate: 1 paper
- Firm Productivity: 1 paper
- Output Quality: 1 paper
- Skill Acquisition: 1 paper
- Task Allocation: 1 paper
- Task Completion Time: 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 |
|---|---|---|---|
| U.S. productivity shows eight postwar cycles and signs of an 'AI phase' in which organisational frictions blunt AI's macroeconomic payoff. Micro gains from faster task execution and learning are offset by task expansion, multitasking and institutional misalignment, preventing those gains from raising aggregate productivity.semantic_scholar | O. M Kulhanik orcid |
Fetched 2026-07-13 | 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.