From participants to partners: advancing consumer involvement in transformative research
Bibliographic record
Abstract
This study explores how participatory research, involving consumers as co-researchers, can improve research quality, equity, and accountability. Systemic barriers, limited training, and resource constraints often hinder effective consumer involvement in research, particularly for those experiencing marginalisation and vulnerability. The study examines how participatory research can strengthen consumer involvement in research, build individual agency, and create positive societal impact. Through two qualitative co-design sessions using the LEGO® SERIOUS PLAY® methodology, the study conceptualises the Research Partnership Model for Transformative Impact. This model highlights the challenges faced by researchers and consumers, identifies gaps in expectations, capabilities, well-being outcomes, and calls for stronger university policies, better support, and collaborative strategies to foster more inclusive and equitable research.
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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 | 0.152 | 0.122 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.024 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.003 | 0.043 |
| Research integrity | 0.005 | 0.007 |
| 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".