Democratizing Participant Engagement of Marginalized Communities in Chronic Pain Research: Crafting a Way Forward
Bibliographic record
Abstract
Increasingly, the value of meaningful collaboration with people with lived experiences of inequities is being recognized by researchers and funding bodies; we refer to this as Participant Engagement (ParE). There is currently no universally accepted framework for ParE and collaboration often excludes structurally marginalized populations despite the prevalence of chronic disease in these communities. This presentation aims to identify how we can draw on critical social science approaches to modify conceptualizations of engagement to better reflect the needs and knowledge of those living with chronic pain who have been marginalized by structural oppression and shift our focus from individuals to communities. The multi-disciplinary speakers of this symposium, who are senior, mid-career, and trainee researchers, will call attention to how the quality of chronic pain research can be enhanced and contribute to social and health equity in policy and care. Our team are members of a national Partnership supported by the Social Science and Humanities Research Council (SSHRC) in Canada to explore this issue (PEPR). We will discuss how a meaningful shift in conceptualization and practice yields a potential to reframe how certain conditions/diseases are normatively understood, thereby leading to the democratization of research and health for the benefit of people living with chronic pain and marginalization. Participants will be offered an opportunity to build their knowledge and critical thinking through a sustained and sequential focus on various aspects of this topic: equity, diversity, and inclusion as applied to ParE; a historical and sociological overview of patient engagement; the need to revise existing methodologies; and expanding notions of “who counts”.
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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 | 0.301 | 0.204 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.034 | 0.101 |
| Scholarly communication | 0.039 | 0.062 |
| Open science | 0.007 | 0.082 |
| Research integrity | 0.016 | 0.030 |
| Insufficient payload (model declined to judge) | 0.007 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".