The Evelina Resolution Project: the story of a UK children's hospital's programme to resolve conflicts with families
Bibliographic record
Abstract
When a consultant paediatrician at the Evelina London Children's Hospital made a phone call to a mediator one Friday afternoon in 2012 asking for help to manage an escalating conflict between a family and the health professionals treating their daughter, neither knew that their meeting would lead to the development of the first conflict resolution and mediation training programme in a National Health Service children's hospital. The Evelina Resolution Project has gained international recognition for training health professionals to recognise and manage conflicts between families and health professionals. In this presentation, the doctor and the mediator describe how one case led to a programme of change which is now being trialled in 4 specialist UK children's hospitals with the aim of supporting families and health professionals to have conversations without conflict.
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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 | 0.014 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.024 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.014 | 0.037 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".