Keeping MANDELA alive: A qualitative evaluation of the MANDELA supervision framework four years on
Bibliographic record
Abstract
Four years after the development of the MANDELA model by Prospera Tedam, an independent evaluation of its effectiveness was conducted in 2014 with 45 social work students and 6 practice educators. The framework was incorporated into the University of Northampton (UN) Social Work Practice Learning Handbook as a recommended practice placement supervision tool for use by students and practice educators. This article summarises the process, findings and recommendations arising from the evaluation. The project sought to evidence the justification for the model’s continued use in social work practice placements. Though the intended audience for this publication are primarily social work students and practice educators in practice placement settings, the model’s underpinning ethos as a strengths based anti-oppressive tool and its unique attributes as a framework that proactively promotes and permits in-depths discussions on pertinent issues of difference, life experiences, individuality and diversity would be of benefit to any university lecturer and other stake holders in the fields of health and social care. The model can also be adapted and used in field education in countries such as Australia, New Zealand, Canada, South Africa and the USA and in other countries where cultural and ethnic diversity in higher education is resulting in differential experiences and outcomes for students from minority backgrounds.
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.
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 | 0.053 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".