Employee Turnover Data for Selection Algorithm Research

Ryan D. Zimmerman authored a paper titled 'Reducing voluntary, avoidable turnover through selection', which is associated with a dataset on the Papers with Code platform. The dataset likely contains variables related to employee selection, turnover, and organizational outcomes. Its specific size, structure, and content are not detailed in the available metadata.

Use Cases

• Training a model to predict voluntary employee turnover based on selection criteria (inferred from domain, verify after download)
• Evaluating the impact of a genetic algorithm on personnel selection outcomes (inferred from domain, verify after download)
• Analyzing factors contributing to avoidable staff attrition in organizations (inferred from domain, verify after download)

Strengths

• Published on the Papers with Code platform, linking research to data.
• Associated with a specific academic paper by a named author, providing research context.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count, column definitions, and sample data are unknown, limiting suitability assessment.
• License is listed as 'closed', which may restrict usage.

Provenance

Source

Papers with Code