Participatory Action Research and Knowledge Dissemination in Virtual Photovoice: Methodological Insights
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the methodological spread of virtual photovoice, alignments to and potential advances for the participatory action research (PAR) and knowledge dissemination (KD) components of in-person photovoice are poorly understood. Detailing the PAR and KD processes, practices, and products drawn from a virtual photovoice study examining men’s experiences of and perspectives about equitable intimate partner relationships, the current article offers three thematic findings. The first theme Processes and pragmatics for selecting representative photographs describes adapting established analytics of preview, review, and cross-photo comparisons to categorize and select images from a large collection of participant-produced photographs ( n = 714). Specifically, detailed are the reconciling of researchers deciding which images and accompanying narratives to include guided by PAR principles. Theme 2, Democratizing and disrupting in-person PAR with virtual focus group polls (VFGPs) , chronicles participant voting through Zoom to collectively decide and subsequently discuss their favorite photographs. While anonymity for the poll was democratizing in terms of participant equality for voting on the photographs, connecting men virtually from diverse locales could differentiate cultural norms. The third theme KD pledges and pitfalls with online photovoice exhibitions details the potential benefits and challenges for reaching diverse end-users. Evident was the importance of marketing and media for driving traffic to the online exhibition, and the centrality of interactivity for fostering engagement to build and adjust photovoice e-health interventions. With virtual photovoice continuing to grow in popularity post COVID-19, this article offers important methodological lessons for adapting and advancing components of in-person PAR and KD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.277 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it