Cartographies of Colonial Commemoration: Critical Toponymy and Historical Geographies in Toronto
Bibliographic record
Abstract
Everyday, I move across a cartography that tells me a story, one that I often don’t consciously listen to, but do learn from. This story, one of colonial dominance, lives on through the markings of place, particularly the toponyms, or place names. In this article, I seek to explore the role of these toponyms in telling a story of place, one that (re)writes my home, Toronto, as a colonized space, one whose geographic and historic intelligibility is made possible through the inscription of place-names that commemorate the European centre. I demonstrate how the banality of colonial geography works in its powerfully subtle ways by taking the reader on an imaginary subway ride, one that travels across a series of toponyms that highlight how the city recites, inscribes and promulgates a story of colonial presence in a largely obscured but simultaneously hyper-visible way. I argue that such colonial story telling through toponymy is a crucial site at which to engage critically.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.032 | 0.049 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".