Replication archive for Lester (2026) contains O*NET v30.0 Importance scores for five research occupations and pharmaceutical pipeline data sources. The Python replication script includes 14 automated verification checks, all of which pass on the included data. Ryan Lester authored this archive, which was last updated in April 2026.
Use Cases
- Construct a digitally executable task share proxy (d-hat) based on O*NET Importance scores for research occupations.
- Replicate econometric tables analyzing AI-amplified research regimes based on the provided Python script.
- Verify data integrity for pharmaceutical pipeline analysis using the 14 automated verification checks.
- Study the complementarity between AI and human tasks in research workflows based on occupational task data.
Strengths
- Includes O*NET v30.0 Importance scores, a standardized occupational database.
- Python replication script produces Tables 1, 2, and 5.1 with 14 automated verification checks.
- All 14 verification checks pass on the included data, indicating internal consistency.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Last updated 2026-04-20 18:39:25; freshness should be verified.
Provenance
- Source
- Ryan Lester Dataverse
- Collection Method
- Data compiled from O*NET v30.0 and pharmaceutical pipeline sources documented by Jayatunga et al. (2024).
- Freshness
- 2026-04-20 18:39:25