Before and after Nature: Temporality and Landscape in Toronto’s Early Urban Greenspace
Bibliographic record
Abstract
In this thesis, I explore the ways cultural constructions of nature and its temporal valences are represented and employed in the design, use, and development of urban greenspace. This arises from a broader interest in the ways the nature/society distinction has been produced alongside the environment-making, world-ecological process of capital accumulation. Parks, as nature in the city, foreground tensions between nature and society. They are developed, maintained, and designed with specific representations of nature in mind. In this sense, they can act as an index for shifting images of nature, or what Jason W. Moore would call historical natures. I have chosen to focus on the emergence of parks in Toronto during the 19th century using Allan Gardens as my primary case study. I approach it as landscape to pay particular attention to how images of nature constructed, employed, and practiced in the development and use of the site. Allan Gardens proves to be an interesting case study in the history of urban greenspace due to its relation to the global flows of science, power, and capital inculcated in botanical gardens, as well as its relation to settler-colonial commemorative exercises that utilize the temporal valences of nature to place indigenous peoples in a pre-history of Toronto’s development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".