Problematising participatory video with youth in<scp>C</scp>anada: the intersection of therapeutic, deficit and individualising discourses
Bibliographic record
Abstract
This paper draws on critical discourse analysis to explore power dynamics in a participatory video project that took place in an alternative education centre in N ew B runswick, C anada. The paper addresses growing concerns at the paucity of critical scholarship devoted to participatory video research. Often championed for its democratic, critical and counter‐hegemonic potential, participatory video has steadily gained favour in academic, developmental and educational contexts. However, practitioners implementing participatory approaches often fail to engage with issues of power. This oversight has meant that taken‐for‐granted assumptions about participatory video have often gone unquestioned. Appreciating this concern, this paper explores how power operates through individualising and deficit discourses in participatory video work with youth and how these discourses might reinforce oppressive thinking, consequently adversely impacting those who participate. This critique accents the importance of challenging taken‐for‐granted assumptions about participatory video by showing how the method can be shaped by, and play into, marginalising discourses. For practitioners, this is a reminder that power operates through all research and educational practices – even those claiming to be participatory, critical and counter‐hegemonic. The paper adds to a growing body of scholarship that draws attention to complexities associated with participatory video and relocates it within the framework of critical participatory research.
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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 | 0.028 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.031 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".