Meeting in the middle: experiences of citizenship in community-engaged psychosis research
Bibliographic record
Abstract
Purpose Previous research has highlighted the importance of engaging people with lived experience (PWLE) in the knowledge creation process. However, diverse approaches to engagement exist. In addition, tensions remain in community-engaged research (CER), including how to address structural inequalities in research settings. This study aims to consider how CER interacts with citizenship within and beyond the research context. Design/methodology/approach This study discusses the authors’ experiences as a majority-PWLE of psychosis research team in Canada, including successes and challenges the authors experienced building their team and navigating research institutions. This study also reflects on the authors’ pathways through citizenship, prior to and during the research process. This study discusses divergent models of CER and their applicability to the cyclical process of citizenship and community participation. Findings Relationships between academic and peer researchers developed organically over time. However, this study was limited by structural barriers such as pay inequality and access to funding. The authors recognize that there are barriers to full citizenship and acknowledge their resources and privilege of being well supported within their communities. Team members built on a foundation of citizenship to access participation in research. This led to opportunities to engage in community spaces, and for PWLE to participate in research as partners and leaders. This study also found that citizenship is a way of giving back, by building a sense of social responsibility. Originality/value Academic and peer researchers can reflect on the authors’ experiences to build more inclusive research teams and communities by using a citizenship approach to research participation.
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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 | 0.144 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.007 |
| 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; a candidate call from one teacher head, 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".