Pushing the Limits of Participatory Video: Exploring Transgressive Voices through Researcher-Participant Minor Video-Making as a Non-Representational Practice
Bibliographic record
Abstract
Abstract This article inquires into participatory researchers’ ‘representational’ practices in relation to sharing power with minority participants through collaborative video-making processes. The author argues that there is a limit to attaining such a political and ethical end because a ‘representational’ logic seemingly operates as the theoretical and methodological underpinning for participatory video, which undercuts its ability to represent the voices of collaborators. This article takes into account Shannon Walsh’s (2014) emphasis that “if participatory video is to be a significant method within a project for social change, we must push its limits, and its politics” (p. 140). This article does so by drawing on a ‘non-representational’ approach (Vannini, 2015) and the concept of ‘transgressive voices’ (Jackson & Mazzei, 2009). The author discusses his experience with Deleuze-inspired ‘minor video-making’ as a relational and affective practice in which participants, tangible and intangible research objects and environments, and the researcher himself became relationally entangled to falsify any predetermined essentialized identity and to compose a powerful new body. In the unfolding of transgressive voices in the specific liminal space or moments during the minor video-making, the author ‘intensively and immanently reads’ (Masny & Cole, 2012) the entanglements during storyboarding, rehearsing, shooting, and editing.
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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 | 0.020 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.028 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| 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".