Working With Photo Installation and Metaphor: Re-Visioning Photovoice Research
Bibliographic record
Abstract
The proliferation of participatory visual methods (PVMs) in applied research has highlighted new ways of seeing and thinking about research. A core tenant of PVMs is the situated, collaborative, reflexive, and co-constructed nature of the work and resulting findings. However, as these methods gain popularity, there can be a disparity between how PVMs are theorized, imagined, and facilitated. Although the facilitated and reflexive nature of PVMs is generally understood by practitioners, researchers seldom report on pedagogical design of their projects, even though the facilitation of a method, and a researcher’s own lens and orientation to photography will influence the production and reading of images. To achieve greater congruence between paradigm and practice, it may be important to return to fundamental questions about the role of facilitation and the process of crafting and exhibiting images in photovoice in relation to one’s study aims. In this article, I explore the crafted role of image-making in the context of a photovoice project that asked stakeholders to visualize engagement in the local HIV sector. Participants created and exhibited 63 photographs and narratives that relied heavily on metaphor as a crafted strategy. They also created three site-specific photo installations. Through detailing our facilitated process, I illustrate how certain design elements (influenced by my pedagogical and theoretical orientations toward co-theorizing) created the necessary conditions for participants to visualize their ideas through metaphor and installation. In turn, the exhibited images and associated installations created new opportunities for synthesis, dialogue, and dissemination. I conclude with a theoretical discussion of the possibilities for taking a crafted and reflexive approach to image-making in photovoice studies.
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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 | 0.046 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.009 | 0.066 |
| Scholarly communication | 0.018 | 0.032 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".