Connecting relational wellbeing and participatory action research: reflections on ‘unlikely’ transformations among women caring for disabled children in South Africa
Bibliographic record
Abstract
Participatory action research (PAR) is a form of community-driven qualitative research which aims to collaboratively take action to improve participants’ lives. This is generally achieved through cognitive, reflexive learning cycles, whereby people ultimately enhance their wellbeing. This approach builds on two assumptions: (1) participants are able to reflect on and prioritize difficulties they face; (2) collective impetus and action are progressively achieved, ultimately leading to increased wellbeing. This article complicates these assumptions by analyzing a two-year PAR project with mothers of disabled children from a South African urban settlement. Participant observation notes, interviews, and a group discussion served as primary data. We found that mothers’ severe psychological stress and the strong intersectionality of their daily challenges hampered participation. Consequently, mothers considered the project ‘inactionable’. Yet, many women quickly started expressing important individual and collective wellbeing transformations. To understand these ‘unlikely’ transformations, a feminist relational account, in particular, that of relational wellbeing, proves essential. We reflect on the consequences of these findings for the dominant PAR methodology and operationalization, and propose to sensitize future PAR with marginalized women by employing relational wellbeing as an overarching ontological awareness.
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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 | 0.049 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.043 | 0.069 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.004 | 0.030 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".