From the hash-bound evidence releases
Recorded claims
Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.
A series of nationally representative U.S. surveys conducted through late 2024 reports rapid generative-AI adoption at work and at home, with adoption patterns varying by industry and shaped by firm climate and policy.
Scope: publisher-deposited abstract metadata; universe: U.S. population ages 18–64, with workplace results among employed respondents; unit: survey respondent; period: through late 2024; sample denominator is not stated in the captured abstract
The Crossref abstract describes nationally representative U.S. surveys of generative-AI use at work and at home and examines how firm climate and policies relate to adoption patterns.
Scope: publisher-deposited abstract-level metadata
Structured relationships
In-corpus citations
Only source-supplied cites relationships whose two endpoints are admitted are shown. Invocation evidence remains a separate relationship.
Cites (5)
- Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality
- The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers
- AI, Skill, and Productivity: The Case of Taxi Drivers
- The Uneven Impact of Generative AI on Entrepreneurial Performance
- Who Is AI Replacing? The Impact of Generative AI on Online Freelancing Platforms
Cited by (2)
Boundaries
Limitations & independence
Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.
Recorded limitations
- Abstract-level Crossref metadata only; the publisher landing page could not be retained because public retrieval was access-blocked.
- The abstract does not state survey sample denominators; numerical adoption rates are not carried forward.
- Full text was not inspected.
- Abstract-level Crossref metadata only; numerical adoption estimates are not restated here; the publisher Articles in Advance listing returned an access challenge.
Source independence
publisher-only