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
1Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5139131766
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Jennifer Daffinee (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
- Skills Training: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Error Rate: 1 paper
- Other: 1 paper
- Task Completion Time: 1 paper
- Training Effectiveness: 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 |
|---|---|---|---|
| Advances in AI are frequently throttled by human capital and interfaces rather than model capabilities; organizations must redesign interfaces, retraining, and workflows to lift the practical performance ceiling. The paper proposes a socio-technical evaluation model and workforce-development principles to treat humans as core system components whose skills and processes shape AI productivity.openalex | Jennifer Daffinee provider id |
2026-06-22 | 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.