Bibliographic record
Abstract
This photo essay offers a brief introduction to the hybrid curatorial/collaborative project oh-oh Canada, which I launched in Ottawa on Canada Day, 2016, as a performance art action at Parliament Hill. oh-oh Canada alludes to the way Canadians enthusiastically consume a set of narratives that characterize the nation as “peaceful, welcoming, and benevolent; a country built through diplomacy” and asks that we/they consider what is missing from these accounts. It does so through the free distribution of a line of “unsettled” maple sugar candies created by artists Adrian Stimson, Cecily Nicolson, Lisa Myers, Peter Morin, Cheryl L’Hirondelle, David Garneau, Michael Farnan, and myself. Given away at patriotic celebrations and other community events, the candies inject overlooked narratives into public and domestic spaces, practices selective commemoration, and the individual bodies of members of the public. Through a short description, Artist Statements, and images of the launch and the candies themselves, this essay situates oh-oh Canada as an intervention into the primacy of dominant narratives that shape the nation’s “preferred memory” in the contours of a settler colonial mindset.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.015 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".