Supervision and Organizational Resilience: Considerations for Staff Retention in Child Welfare Agencies
Bibliographic record
Abstract
Objectives: This paper presents results from a mixed methods online survey on factors related to child welfare professionals’ experiences with supervision, considered within the framework of organizational resilience. Methods: This analysis presents results from 543 child protective service (CPS) professionals in the United States. Results: About a quarter of these child welfare professionals currently held supervisory roles. Comparisons of those without supervisory roles indicate higher mean ratings on perceptions of support and care from those not currently in supervisory roles, while those currently in supervisory roles reported higher mean ratings on perceptions of potential growth and promotion. Outcomes including intention to stay in child welfare, satisfaction with position, and salary were significantly associated with positive supervision components. These professionals’ qualitative responses highlight a need for consideration of supervision approaches that reflect trauma-informed components and that foster organizational resilience. Implications: Implementation of these critical supports for child welfare professionals may have lasting impacts on the well-being of children, youth, and families.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".