Why study power in digital spaces anyway? Considering power and participatory visual methods
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
In this article, we interrogate notions of power in relation to three participatory visual methods: drawing, photovoice, and making cellphilms (videos made on cell phones). In particular, we address power from the perspectives of Foucault, Freire, Giroux, and hooks in a consideration of the power structures operating in and around participatory visual research. We seek to understand the power dynamics that operate in participatory visual research—particularly in relation to digital media. In so doing, we foreground the notion of power in a discussion of a workshop on participatory visual methodologies that we conducted as part of a graduate student conference. Since participatory visual research artifacts can be both created and disseminated through digital spaces, this work offers implications for researchers working in this field. We conclude that more theoretical work needs to be done to enable us to articulate more fully the power dynamics at play in participatory visual research.
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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