The Spit Represented: Imagined Natures of the Leslie Street Spit and Emerging Aesthetic Ideals on Instagram
Bibliographic record
Abstract
From a wasteland to an urban wilderness, Tommy Thompson Park (commonly referred to as “the Spit”) is the culmination of various landscape narratives and visions of nature. Built from the rubble of Toronto’s early city-building initiatives, the 5km long peninsula is a product of shifting environmental values and socio-political processes. As a landscape in flux, there is a need to understand aesthetic preferences and the landscape character of the Spit. Publicly available photographs on social media have increasingly been used as a proxy for recreational values, preferences and to gauge visitor behaviour (Hamstead et al., 2018; Jim & Chen, 2006; X. P. Song et al., 2020; Wood et al., 2013). This method supports the shift away from technocratic, expert-based approaches to understanding landscape preferences, towards a more placebased understanding of the everyday situated experience, while enabling more collaborative local landscape planning processes. In this research, landscape preferences are identified through the coding of frequently occurring image attributes and the rate of occurrence serves as an indicator of aesthetic appreciation. Key findings demonstrate a balanced appreciation for socalled natural and urban features. The photos of Lake Ontario and Toronto’s skyline resemble a relatively homogenous photographic composition that constitutes the bulk of visual representation. Images of Toronto’s skyline portrays an idealized waterfront city. In looking out towards the urban centre, it positions the Spit outside of the city, engendering particular affective responses and perceptions that limit understandings of the urban, economic, and socio-ecological entanglements that have created it. This is problematic for post-industrial natures that are deeply enmeshed within urban processes, which require contextually attuned responses, and for promoting narratives that exclude the negative and unscenic impacts of the “urban engine” (Coelho, 2018). The prevalence of images that depict water either as the focal point or in the background, suggests access to Lake Ontario is highly valued and contributes to the Spit’s imageability. Other viewpoints that are oriented toward the urban skyline and those with unimpeded views of the lake are highly appreciated and could inform future park management plans. The prevalence of wildlife imagery affirms the Spit’s important role in habitat creation. It also alludes to the power of nonhuman actors (especially birds) in shaping the relationship between humans and the environment, in both attracting people to the Spit and inspiring its protection. The results confirm the landscape is multivalent and offers insight into aesthetic preferences of the Spit. This research complements existing work by the Rubble to Refuge Project, a joint endeavor with the Toronto Region and Conservation Authority (TRCA) and York University that responds to the pressing need to understand human uses with the Spit.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".