The many roles of people with lived experience and how these can be better supported within integrated care policy and implementation: a world cafe discussion.
Bibliographic record
Abstract
Introduction: This workshop will explore the many roles that people with lived experience of health and social care can play in shaping the vision, planning and implementation of integrated care and consider what supports would enable them to fulfil these roles. Why are you conducting a workshop? Whilst it is widely accepted that integrated care policy and programmes should be based on the needs and interests of people with lived experience of health and social care and their communities, this is rarely achieved in practice. The workshop team have led two international projects regarding co-production within integrated care ( ‘citizen leader research’ by the Universities of Birmingham, Leiden and Toronto and the Changemakers project within Transform). A common issue identified is that people involved in such activities are asked to take on different roles – for example as a champion, ambassador, advocate, partner, advisor, connector, or leader – with the nature of these roles affecting the expectations of them and the identities that they adopt. We would like to run a workshop to give participants an opportunity to explore what is meant by these roles, how people can be supported to do so effectively, and how organisations and professions can provide a receptive context. Who is it for? The workshop is for people with lived experience of health and social care (including family carers) and professionals, policy makers, managers and academics who are committed to co-production as the basis of integrated care. What are you going to do? 8 minutes introduction & overview of the roles that people with lived experience play (as identified in the projects) 5 minutes response from WHO based on their meaningful engagement framework 2 minutes explanation of the engagement exercise 40 minutes (or ideally longer if we are able to have a 90 minute session) world café discussion 5 minutes summary feedback from each table How are you going to engage with the audience? Participants will have opportunity to move around the world café table – each one will focus on a different role that people take on. A facilitator will remain at each table to encourage discussion on the nature, support, and context for such a role. The discussion will be visually recorded to enable participants to build on what has come before to enable a rich and diverse conversation. How are you going to summarize the take home messages?There will be short feedback from each table on main points discussed – the facilitation team will then write up the discussions into a short and accessible summary which will be shared through social media, integrated care networks and relevant WHO routes.
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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 | 0.057 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.032 | 0.035 |
| Scholarly communication | 0.025 | 0.040 |
| Open science | 0.006 | 0.036 |
| Research integrity | 0.020 | 0.031 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".