Empowering younger residents living in long-term care homes as co-researchers
Bibliographic record
Abstract
We draw on our research, our lived experiences of disability and the grounded expertise of disabled persons living in long-term care (LTC) homes as co-researchers, to illustrate the value of disability-led participatory research. Our approach to a co-designed collaborative project on young adults living in LTC highlights the benefits of research that centers the lived realities of disabled people. Points of interestResearch and knowledge about disabled people living in long-term care (LTC) homes routinely excludes the perspectives of the people who live there; this is especially true for younger residents living in LTC.This article shares information about a study on promising approaches to residential LTC for people under 65 years of age that was co-led with care home resident researchers.The study design provided opportunities and supports to encourage meaningful engagement, such as training and access to research assistants.Resident co-researchers brought lived expertise and experiential insights that enriched the research process and knowledge produced, and that supported them in their own disability advocacy work.Inequities persist when budgets fail to consider and address barriers to residents’ full participation in all aspects of the 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 | 0.030 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".