Child Welfare Supervisor Training and Worker Retention Data from a Midwestern State

A federally funded training initiative in a Midwestern state aimed at improving child welfare worker retention. The paper by Miriam J. Landsman of the University of Iowa describes a collaborative program where all state child welfare supervisors helped identify content, develop competencies, and conduct self-assessments. The dataset likely contains information related to this program's implementation and evaluation.

Use Cases

• Analyzing the relationship between supervisor training programs and worker retention rates based on the program's evaluation mentioned in the description.
• Modeling factors influencing child welfare workforce stability based on the supervisor competencies and self-assessments described.
• Evaluating the impact of collaborative, supervisor-led content development on training program outcomes as described in the initiative.

Strengths

• Data originates from a federally funded, statewide initiative, suggesting a structured data collection effort.
• The program involved all child welfare supervisors in the state for content identification and self-assessment, potentially providing comprehensive supervisory perspectives.

Limitations

• Row count, column definitions, and sample data are unknown, limiting suitability assessment.
• Description metadata is limited; actual data quality and structure require manual inspection after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Miriam J. Landsman, University of Iowa

Collection Method

Likely collected through a federally funded child welfare training initiative and its evaluation.

Geography

A Midwestern state in the United States