Rhetoric vs. reality in social work supervision: the experiences of a group of child care social workers in <scp>E</scp>ngland
Bibliographic record
Abstract
Abstract Whilst the contribution of good supervision to high‐quality social work practice is widely recognized, research exploring practitioners' experiences of supervision is surprisingly limited. Set within the context of the supervision framework for employers of social workers in England, this small‐scale survey, using an extended questionnaire, examined the experiences of supervision of a group of child care social workers. The aim was to find out what aspects of supervision worked well and where there was room for improvement. The findings suggest that whilst the majority of employers had appropriate supervision policies in place, day‐to‐day practice varied enormously, frequently falling well short of national standards, with the quality of supervision often depending more on the characteristics of the supervisor and the agency context than the needs of the worker. Supervision sessions typically focused predominantly on case management, with much less attention paid to the worker and opportunities for them to reflect on their practice. Only a quarter of the social workers in this survey could be considered to be satisfied with their current supervision, with a much higher proportion clearly dissatisfied.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".