What difference does the Adult Support and Protection (Scotland) 2007 make to social work service practitioners' safeguarding practice?
Bibliographic record
Abstract
Purpose This article seeks to explore the difference that adult support and protection legislation may have made to work with adults at risk of harm in Scotland. Design/methodology/approach The article is based upon findings of a joint academic and practitioner qualitative research project that interviewed 29 social service practitioners across three local authorities. Findings The legislation was seen as positive, giving greater attention to adults at risk. Views about the actual difference it made to the practitioners' practice varied, and were more likely in new rather than ongoing work. Three differences were noted: duties of investigation, protection orders and improved shared responsibility within the local authority and across other agencies, but to a lesser extent NHS staff. Overall it gave effective responses, more quickly for the adults at risk. Whilst the law brought greater clarity of role, there were tensions for practitioners in balancing an adult's right to autonomy with practitioners' safeguarding responsibilities. Originality/value The paper demonstrates that a dedicated law can improve safeguarding practice by clarifying the role of social work practitioners and the responsibilities of other agencies. The right to request access to records and banning orders were seen as valuable new measures in safeguarding adults at risk. As such the study from the first UK country to use dedicated adult safeguarding law offers a valuable insight for policy makers, professionals and campaign groups from other countries, which might be considering similar action.
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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 | 0.009 | 0.026 |
| 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 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".