Towards a process model of supervision in social work– a bibliometric analysis
Bibliographic record
Abstract
Supervision plays a pivotal role in social work, ensuring ethical practices, professional growth, and the delivery of quality services. This study conducts a bibliometric analysis to explore the evolving conceptualizations and applications of supervision in social work. Using the Web of Science Core Collection, a search for studies with "supervision AND social work" in their titles yielded 246 works. Full bibliographic records were downloaded and analyzed using VOSviewer software. A co-occurrence analysis of all keywords, with a minimum occurrence threshold of one, identified 89 keywords relevant to the topic. Excluded terms included regional and cultural-specific terms such as "England," "Ontario," and "Maori concepts," to maintain a focused and universal scope. The analysis revealed several thematic clusters encompassing clinical supervision, external supervision, crisis management, and child welfare supervision, among others. Notable themes include the intersection of supervision with burnout, cultural competence, and outcomes, highlighting its complex nature. The study emphasizes the significance of supervision frameworks tailored to diverse contexts and professional roles within social work. The findings contribute to the development of a process model for supervision, offering insights for researchers, educators, and practitioners to enhance supervisory practices. By identifying critical trends and gaps, this bibliometric analysis provides a foundation for future investigations aimed at refining supervision processes in social work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.021 | 0.083 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".