Crossing together towards implementing landscape connectivity : best practices along the Meadoway
Bibliographic record
Abstract
Urban development represents a fundamental threat to the viability of the functional ecological networks from which humans derive ecosystem services. As urbanized areas continue to grow and intensify, they fragment landscapes removing the connective green tissue capable of supporting a healthy and biodiverse ecosystem. Yet in many cities across North America and beyond, linear adaptive re-use parkland projects are transforming the landscapes of cities by reintroducing functional green spaces through the conversion of abandoned or underutilized utility corridors into greenways for the restoration of habitat, recreation, public transit, and art. In Toronto, the recently announced development of the Meadoway in Scarborough represents one of such opportunities to [re]connect human and wildlife habitat to and within each other along its 16-kilometre length. Planning for a new linear adaptive re-use parkland represents a ‘wicked problem’ with no clear solution, only better or worse responses learned through the continued re-evaluation of these responses and by grounding them in their place-specific conditions. This project integrates lessons learned from case examples of linear adaptive re-use parkland projects from across North America to consider the impacts these new amenities have generated on surrounding land uses and the communities that inhabit them. Applying these key lessons to the policy and physical landscape of the Meadoway provides an opportunity to unpack the various strengths, weaknesses, opportunities, and threats associated the redevelopment of this landscape, articulated through three study areas. Using a mixed-methodological approach of case study and policy analysis paired with site observation, this study provides recommendations to the Toronto and Region Conservation Authority, the Weston Foundation, and the City of Toronto, all key development stakeholders of the Meadoway, to inform the implementation of the project’s goals and highlight key areas that should be considered given precedents from similar projects. Overarching recommendations highlight the need to consider: the various physical, temporal, and social understandings of connectivity; the land use changes associated with the introduction of a new greenspace amenity; and the imperative to meaningfully consult and collaborate with communities along the Meadoway to understand how this space can support their growth and vitality. Ultimately, learning from these key areas may provide useful context to future development of other hydro corridors in the Greater Toronto Area.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".