Personnel Supervision and Management
Equity and data-based supervisory practice
Use equity-focused and data-based supervision practices to make defensible decisions and reduce bias in staff development and oversight.
How this shows up in scenario questions
- 1Identify equity concerns in supervision.
- 2Use data to adjust supervisory practices.
- 3Choose fair performance criteria.
Common misconceptions
- Assuming identical treatment is always equitable.
- Using subjective impressions as sole performance data.
- Ignoring cultural context in supervision.
Distractor patterns
- Apply inconsistent standards.
- Make promotion or discipline decisions without data.
- Ignore supervisee feedback.
Related terms
equitydata-based supervisionsupervisory decisionsbias in supervision
Related practice prompts
Evaluate treatment integrity before changing a plan.
A BCBA reviews data showing an increase in aggression after a new intervention began. Direct observation shows staff rarely prompt the replacement response and deliver reinforcement inconsistently. What should the BCBA do next?
Use behavioral skills training for staff performance deficits.
A technician can describe a discrete-trial teaching procedure but makes errors during live sessions. Which supervision strategy best addresses the performance deficit?
Match supervision intensity to risk and staff competence.
A new staff member is assigned to implement a plan for repeating questions that includes safety procedures. What is the best supervision approach? The supervisor is deciding what feedback to give before the next session.