Relational Equity: Co-creating values and a protocol for engaging patients across the canadian primary care research network
Bibliographic record
Abstract
Context: Values and protocols for engaging patient-partners and community members in patient-oriented research are frequently focused on recruitment and on-boarding. However, relational equity, which is “something that is carefully cultivated and preserved by those who desire to influence others”, is crucial for the retention of patient-partner members over time and the establishment of trust between community members and the other Network partners. Objectives: 1. To describe relational equity and why it is important to the members of the Pan-Canadian Patient Council of the Canadian Primary Care Research Network (CPCRN). 2. To identify and name the values co-created by the CPCRN’s Pan-Canadian Patient Council, along with a protocol for the establishment of relational equity across the CPCRN. Design: The overall design was informed by the integration of community-based participatory research and transformative action research. This approach facilitated the process of co-creation of identified issues to the forefront while utilizing the strengths and contributions of the community. Setting and Participants: The members of the CPCRN Pan-Canadian Patient Council while employing a protocol of relational equity. The protocol included establishing relational equity through various talking circles with a facilitator who guided the virtual discussions. Intervention(s): The co-creation of values and a protocol of relational equity was developed by the Pan-Canadian Patient Council will be introduced to other members and committees of the CPCRN. Results: The Pan-Canadian Patient Council has met at least once a month to co-create the structure and activities of the Patient Council. A dialogue about values, facilitated by a member of the Patient Council, created an opportunity to build trusting relationships which, in turn, will drive transparency and an opportunity for co-creation within and external to the CPCRN, as well as ensure a culturally safe environment. The CPCRN Executive Director and several researchers provided guidance and support for the process. Conclusions: The co-creation of the governance structure for the Pan-Canadian Patient Council brought together the members in a way that addresses the potential power imbalances within and external to the Patient Council.
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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 | 0.261 | 0.223 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.023 | 0.013 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.007 | 0.013 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.041 | 0.009 |
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".