Speaking to Monuments and their Ghosts: Performance Art as Ephemeral Knowledge Sharing
Bibliographic record
Abstract
Talkin Back to Johnny Mac is a performance series that I curated in response to the 200th birthday celebrations for John A. Macdonald held in Kingston, Ontario in 2015. Many of the 2015 performances that examined and intervened in the Prime Minister’s ongoing memorialization took place at his statue in Kingston. In 2021, the statue was removed by the city after many requests from community members. I returned to the site of the statue in October 2025 with a new performance series in order to explore the ways in which the site had changed since the removal of the statue, and the ways in which it had stayed the same. This essay explores the performances by artists David Garneau, Leah Decter, Peter Morin and Jimmie Kilpatrick in 2015 and 2025 as a way to consider the colonial narratives that continue to be present at the site of the statue, and the ongoing importance of performance to create spaces for critical and community-oriented interventions.
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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.078 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".