Envisioning Democracy: Participatory Filmmaking with Homeless Youth
Bibliographic record
Abstract
This paper explores the democratic potential for participatory filmmaking with homeless youth, as well as the constraints and dilemmas associated with this visual method. Theorizing democracy through the work of Hannah Arendt and Pierre Bourdieu, the paper approaches democracy not as an end, but rather as a process that seeks to lessen social injustice. Bourdieu's work helps us appreciate, however, that this process is constrained by structures of inequality that shape access to the political dispositions that enable such engagement. Consistent with other research on low-income and marginalized young people, this study found that homeless youth engage with democracy through forms of community participation and mutual support, and are disinclined to orient toward liberal democratic structures such as voting and political parties, which they see as harmful or problematic. With a focus on one particular dilemma faced by the research team-namely, the question of how to make sense of and represent the issue of legalizing marijuana, which had been signaled by the youth participants as of primary political importance to them-the paper uses Arendt and Bourdieu to discuss how participatory filmmaking can help to expand the space of appearances available to homeless youth in Canadian society, and create a space at a shared table of understanding with middle class power brokers.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.024 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".