Circumventing Protocol and Building Collaborative Histories: A Conversation on <i>Freedom Tours</i> with Tania Willard, Cheryl L’Hirondelle, and Camille Turner
Bibliographic record
Abstract
In 2017, artists Cheryl L’Hirondelle and Camille Turner collaborated to stage Freedom Tours , two performative interventions in Canadian National Parks. The work was commissioned by Partners in Art for LandMarks2017/Repères2017 , a nationwide public arts project across twenty national parks, featuring seven curators and twelve artists. The occasion was the 150th anniversary of Canadian confederation, though, as the LandMarks curators made clear, “a hundred and fifty years is not a long time,” if you consider that there are “marked mammoth bones […which] suggest that the first humans inhabited Turtle Island over 28,000 years ago.” Freedom Tours took the form of two participatory interventions emphasizing Haudenosaunee, Anishinaabe, and Black histories in the territory: a guided boat tour at Thousand Islands National Parks and an intergenerational walking tour or procession at Rouge National Urban Park. In 2024, we met with curator Tania Willard and artists Cheryl L’Hirondelle and Camille Turner over zoom to discuss the frictions and the sparks that arose from this project. What follows is a distilled version of that conversation.
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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 | 0.082 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.057 | 0.061 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.013 | 0.025 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".