Re-approaching community development through the arts: a ‘critical mixed methods’ study of social circus in Quebec
Bibliographic record
Abstract
Community arts projects have long been used in community development. Nevertheless, despite many liberatory tales that have emerged, scholars caution that well-meaning organizations and artists may inadvertently become complicit in efforts that distract from fundamental inequities, instrumentalizing creative expression as a means to transform potentially dissident youth into productive and cooperative 'citizens'. This article examines how social circus - using circus arts with equity-seeking communities - has been affecting personal and community development among youth with marginalized lifestyles in Quebec, Canada. Employing a 'critical mixed methods' design, we analysed the impacts of the social circus methodology and partnership model deployed on transformation at the personal and community level. Our analysis suggests that transformation in this context is grounded in principles of using embodied play to re-forge habits and fortify an identity within community and societal acceptance through recognizing individual and collective creative contributions. The disciplinary dimension of the programme, however, equally suggests an imprinting of values of 'productivity' by putting marginality 'to work'. In the social circus programmes studied, tensions between the goal of better coping within the existing socioeconomic system and building skills to transform inequitable dynamics within dominant social and cultural processes, are navigated by carving out a space in society that offers alternative ways of seeing and engaging.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".