Working Towards the Promise of Participatory Action Research: Learning From Ageing Research Exemplars
Bibliographic record
Abstract
Within research addressing issues of social justice, there is a growing uptake of participatory action research (PAR) approaches that are ideally committed to equitable participation of community members in all phases of the research process in order to collaboratively enact social transformation. However, the utilization of such approaches has not always matched the ideal, with inconsistencies in how participation and action are incorporated. “Participation” within various research processes is displayed differently, with the involvement of community members varying from full participation to their involvement as simply participants for data collection. Similarly, “action” is varyingly enacted from researchers proposing research implications for policy and practice to the meaningful involvement of community members in facilitating social change. This inconsistency in how PAR is utilized, despite widespread publications outlining key principles and central tenets, suggests there are challenges preventing researchers from fully embracing and enacting the central tenets of equitable participation and social transformation. This article intends to provide one way forward, for scholars intending to more fully enact the central tenets of PAR, through critically discussing how, and to what extent, the principles of PAR were enacted within 14 key exemplars of PAR conducted with older adults. More specifically, we display and discuss key principles for enacting the full commitment of PAR, highlight a critical appraisal guide, critically analyze exemplars, and share strategies that researchers have used to address these commitments. The critical appraisal guide and associated research findings provide useful directions for researchers who desire to more fully embrace commitments and practices commensurate with enacting the promise of PAR for equitable collaboration and social transformation.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
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 | 0.197 | 0.175 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.019 | 0.072 |
| Scholarly communication | 0.033 | 0.048 |
| Open science | 0.006 | 0.027 |
| Research integrity | 0.012 | 0.036 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".