Toronto’s Not-So-“Smart” City: Dismantling the Tech Utopia & Building Stronger Communities
Bibliographic record
Abstract
This thesis critically analyzes the dominant discourse, actors, and technologies associated with the Sidewalk Toronto smart city project to uncover and resist the potential dangers of the unregulated smart city. Drawing from gray and scholarly literature alongside four semistructured interviews and three action research methods, this research shows that smart cities and technologies are the latest iteration of corporate power, exploitation, and control. Imbued with neoliberal, colonial, and positivistic logics, the smart city risks further eroding democracy, privacy, and equity in favour of promoting privatization, surveillance, and an increased concentration of power and wealth among corporate and state elite. While the publicized promise of the smart city may continuously shift to reflect and co-opt oppositional narratives, its logics remain static, and its beneficiaries remain few. Applying a social justice-oriented lens which connects critical theory, postmodernism, poststructuralism, intersectional feminism, and anticolonial methodologies is crucial in reconceptualizing “smartness” and prioritizing public good.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".