Mixed identity is an identity: embracing the people involved in research partnerships
Bibliographic record
Abstract
INTRODUCTION: Patient and public involvement (PPI) in health research has gained prominence, with patients and public actively shaping research priorities, study design and knowledge translation. While the benefits and challenges of PPI are well documented, less attention has been given to the complexity of navigating multiple identities as research team members. Often, patients and public, academics and clinicians share many of the same goals and occupy overlapping roles, yet research structures rarely acknowledge or accommodate this fluidity. This commentary explores how shared identities of patients and public, academics and clinicians shape research partnerships, challenging conventional boundaries by questioning whether patients and public can also serve as academics or clinicians and vice versa. METHODS: This commentary is written from an interdisciplinary perspective, where insights are synthesised from existing literature, empirical knowledge and lived experience. The authors critically examine the intersection of patient and public, academic and clinician identities and discuss the implications for research partnerships. Recurring points of tension, including questions about the suitability of partnerships and the complexities of identity, are explored. The discussion considers how members of research teams navigate privilege and shared responsibility within collaborative settings. DISCUSSION: Although PPI aims to foster inclusivity, research partnerships often confine patients and public, academics and clinicians to rigid titles, overlooking the multidimensional identities of those involved. To advance research, practice and advocacy, it is foundational to embrace one's authentic self while recognising the full complexity of team members. Every individual brings a unique perspective and lived experience, and together, a research team shares the collective responsibility to produce rigorous, quality research that strengthens the body of evidence.
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 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 | 0.080 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.032 | 0.099 |
| Scholarly communication | 0.035 | 0.040 |
| Open science | 0.004 | 0.034 |
| Research integrity | 0.016 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 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".