Kris Iyer's dataset contains audit recommendations extracted for a study on diagnosing governance failure through performance auditing. The repository includes the complete dataset and inter-coder comparison documentation. It was last updated on 2026-06-18 via Harvard Dataverse.
Use Cases
- Analyze patterns in audit recommendations based on the described study framework.
- Study inter-coder reliability in auditing research based on the provided comparison documentation.
- Train models to classify governance failures based on audit recommendation text.
- Apply principal-agent theory to real-world audit data as described in the study.
Strengths
- Includes complete inter-coder comparison documentation, which supports methodological transparency.
- The dataset is described as 'complete' for the underlying study.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- Harvard Dataverse
- Collection Method
- Extracted for a study on governance failure and performance auditing.
- Freshness
- Last updated 2026-06-18 04:02:16; freshness should be verified.