Where The Sidewalk Ends: The Governance Of Waterfront Toronto’s Sidewalk Labs Deal
Bibliographic record
Abstract
In May 2020 Sidewalk Labs, the Google-affiliated ‘urban innovation’ company, announced that it was abandoning its ambition to build a ‘smart city’ on Toronto’s waterfront and thus ending its three-year relationship with Waterfront Toronto. This is thus a good time to look back and examine the whole process, with a view to drawing lessons both for the future of Canadian smart city projects and the future of public sector agencies with appointed boards. This article leaves to one side the gadgets and sensors that drew much attention to the proposed project, and instead focuses on the governance aspects, especially the role of the public ‘partner’ in the contemplated public-private partnership. We find that the multi-government agency, Waterfront Toronto, had transparency and accountability deficiencies, and failed to consistently defend the public interest from the beginning (the Request for Proposals issued in May of 2017). Because the public partner in the proposed ‘deal’ was not, as is usually the case in smart city projects, a municipal corporation, our research allows us to address an important question in administrative law, namely: what powers should administrative bodies outside of government have in crafting smart city policies? In Canada, the comparatively limited Canadian scholarly work regarding urban law and governance has mainly focused on municipal governments themselves, and this scholarly void has contributed to the fact that the public is largely unaware of the numerous local bodies that oversee local matters beyond municipal governments. This paper hones into the details of the WT-Sidewalk Labs partnership to understand the powers and limitations of WT in assuming a governmental role in establishing and overseeing ‘smart city’ relationships. It ultimately argues that WT has not been – nor should it be – empowered to create a smart city along Toronto’s post-industrial waterfront. Such tasks, we argue, belong to democratic bodies like municipalities. An important contribution of this paper is to situate the evolving role of public authorities in the local governance literature and in the context of administrative law.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.023 | 0.022 |
| Scholarly communication | 0.022 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".