Initiating Participatory Action Research with Older Adults: Lessons Learned through Reflexivity
Bibliographic record
Abstract
La recherche-action participative (RAP) apporte une perspective intéressante pour la recherche abordant l'exclusion et l'inclusion sociale des personnes âgées. Les exemples et réflexions sur la RAP impliquant des personnes âgées sont rares, en particulier à l'étape de l'initiation de la recherche, lorsque l'action participative cyclique est mise en place. Dans cet article, nous décrivons le démarrage d'un projet de recherche-action participative avec des personnes âgées et analysons la concordance entre ce processus et les principes clés de la participation, ainsi que son arrimage aux structures de recherche typiques. Les résultats soulignent les tensions entre le développement de relations de plus long terme et les demandes de financement préparées dans de courts délais. Cette étude montre comment les conceptions traditionnelles de la recherche peuvent influer sur la création de partenariats équitables et met en évidence la nécessité d'élaborer des lignes directrices en matière d'éthique et de publications qui traitent explicitement des approches participatives. Ces observations clés pourront être appliquées pour utiliser les potentialités de la recherche-action participative, qui consiste à aborder les enjeux importants à travers un travail collaboratif et une approche équitable intégrant les personnes les plus affectées. Participatory action research (PAR) is well suited to research that aims to address social exclusion and inclusion in older age. Illustrations of and reflections on PAR with older adults are scarce, particularly the initiation stage, which sets the stage for the cyclical participatory action that follows. In this article, we describe the initiation of a PAR project with older adults and reflect on the alignment of this process with key participatory principles and fit within typical research structures. Findings point to the tensions between developing relationships over time and time-sensitive calls for funding, how traditional conceptions of research can influence creating equitable partnerships, and the need for development of ethical and publishing guidelines that address participatory approaches. These key insights can be applied to help achieve the potential of PAR: to address issues of concern by collaboratively and equitably working with the people most affected.
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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 | 0.231 | 0.189 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.010 | 0.040 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.006 | 0.022 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".