Circus, In Crisis: Examining Care and Community in Circus Training
Bibliographic record
Abstract
This paper is about care through kindness in recreational circus practice. I offer care as a category of relational kindness, where the connectivity of intimacy and trust construct modes of “being held” that do not – particularly in times of the Covid-19 pandemic – necessitate physical presence, but instead emotional support, healing, and accountability. Kindness and care are in this conceptualization how we relate to and treat ourselves, as well as our environment, and others. When in a crisis that distinctly necessitates isolation and distance our modes of care necessarily shift with our relationship to space and surroundings, requiring new forms of virtual spotting that are as much about safety practices for our physical bodies, as they are about strategies for supporting our mental health. Refusing a simplistic or romanticized attribution to care in crisis, this article moves to critique how care and kindness can be taken up and appropriated towards neoliberal aims that mask, rather than address systemic inequities. Through personal reflections on circus practices during the pandemic, alongside performance analyses and critical considerations of norms in the circus industry, I explore care and kindness as it mutates and adapts through our relationships with others, ourselves and the spaces we traverse.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.062 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.003 | 0.007 |
| 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".