Bibliographic record
Abstract
In Toronto in the summer of 2017, during a season of flooding and heightened Canadian nationalism, two processional performances honoured the land and water’s sustaining ecology. Freedom Tours, a multi-site performance by the artists Cheryl L’Hirondelle and Camille Turner, was part of the LandMarks2017/Repères2017 project, in which artists created interventions in Canada’s national parks. Freedom Tours featured an alternative boat tour of the Thousand Islands National Park highlighting Indigenous and African-diasporic histories and futures, and a procession through Scarborough’s Rouge River Urban National Park in which local youth were invited to speak to Mother Earth. The Toronto Island Fire Parade, a community lantern procession with a puppet and shadow performance by Shadowland Theatre, continued its long-running participatory tradition, but without a culminating bonfire on the beach. The parade welcomed visitors from the city to celebrate the power of water, and offered thanks to the community for its mutual aid and resilience after the spring floods. Linking these two projects together allows for a deeper understanding of their contrasting ecologies and choreographies of assembly, which gather humans and other creatures into renewed relation, inviting gratitude to the land and water—to Mother Earth.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.022 | 0.016 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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".