In Support of Sustainability: Teaching Future Circus Artists in Québec
Bibliographic record
Abstract
This qualitative-interpretative research presents the experiences and observations of thirteen circus artists around the concept of professional sustainability, as they have come to understand it in their careers. All thirteen had worked with me as their teacher in circus discipline classes during their post-secondary education at the École nationale de cirque (ENC). They graduated from the school’s three-year professionalizing program between the years of 2011 and 2021. In semi-directed interviews, they spoke of their personal understandings of sustainability following years of professional experiences. They related their experiences of autonomy support within the learning environment we shared in classes. The observations and memories of these circus artists, taken in dialogue with my reflexive analysis of own teaching behaviors, demonstrate an alignment between balanced career longevity and self-determination theory (Ryan & Deci, 2000). The professionalizing education of circus artists today as performers, creators and athletes demands preparation not only for immediate employment, but also for long-term health and artistic growth. Circus artists creatively adapt to employment instability, variable working demands-conditions, injury and repetition. Autonomy-supportive physical and creative learning environments within a high-performance professionalizing circus education can facilitate the development of intrinsic motivation, which will allow them to persist in a career in circus arts. Keywords: Circus education, autonomy support, career sustainability, Québec circus, performing arts pedagogy
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".