The health social work competency rating scale: development of a tool for education and practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Integrating contextual competency frameworks into health social work education and practice can bolster student training and staff supervision strategies. This article describes the iterative development of a Health Social Work Competency Rating Scale (HSWCRS), generated using a competency framework tested through simulation and an iterative research process with healthcare social workers. A modified Delphi method consisting of an e-mail questionnaire, two discussion meetings, and two rounds of classroom-based testing were employed to develop and refine the scale with the participation of clinicians, students, and researchers. The HSWCRS is designed to convey the core competencies required for single-session social work consultations in a healthcare setting by assessing formal elements (such as introduction, validation, cultural inclusiveness, client centredness), use of self (such as self-awareness, positionality), and an overall assessment of knowledge and skills. This scale adds to the competency-based education literature in social work by offering a guide to assess and measure key healthcare social work competencies in a range of educational environments, and has the potential to guide practice in educational and practice settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 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) | 0.000 | 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 it