Bibliographic record
Abstract
What’s Safe is an ongoing response to Toronto’s social distancing measures. It is a dance score documented cinematically in Trinity Bellwoods Park, with movements inspired by Deepa Iyer’s framework (Mapping Our Roles in Social Change Ecosystems, 2020) and Jay Pitter’s open letter to Canadian urbanists (A Call to Courage, 2020). The project was conceived, performed, and captured by the authors of this paper. The two dancers, our second and third authors, engage in creative problem-solving by facing the reality of socially-distant grounds for play and suggesting a different type of productivity, one which is conducive to individual and social growth. The movements are then captured by our multimedia creator (or fourth author), while our artist-researcher (first author) curates and provides critique throughout. The final project considers artistic practice in response to social change as informed by (un)productivity. It uses productive imagination (e.g., play, improvisation, creative problem-solving) to investigate parameters of safety (e.g., surveillance, control, space). Through the dancers’ improvisations, we attempt to navigate these tensions and better position ourselves in relation to our current socio-geographical circumstances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.028 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".