Integrating participatory action research and photovoice as mixed methods: Synergies, tensions, and implications for social work
Bibliographic record
Abstract
This article examines the integration of two qualitative research methodologies, namely Participatory Action Research (PAR) and Photovoice (PV), to explore their synergies, tensions, and implications for social work. While both methodologies are rooted in participatory, subjectivist-objectivist, and transformative-emancipatory frameworks, they differ in their objectives, methods, and levels of participant involvement. PAR focuses on challenging power structures and promoting systemic change through collaborative community actions. PV prioritizes the use of visual narratives to influence policy and public opinion. Methodologically, PAR follows iterative cycles of action and reflection led by community members, while PV emphasizes individual storytelling. Integrating these approaches thoughtfully can leverage their strengths to foster both individual and collective transformation.
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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 | 0.218 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.011 | 0.047 |
| Scholarly communication | 0.027 | 0.027 |
| Open science | 0.004 | 0.029 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".