MétaCan
Menu
Back to cohort
Record W4206750118 · doi:10.22215/etd/2021-14752

A Critique of Smart Cities: Sidewalk Labs’ Project in Toronto

2021· dissertation· en· W4206750118 on OpenAlexaffabout
Samuel Lewin Evans

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsCarleton University
Fundersnot available
KeywordsCommodificationNeoliberalism (international relations)InterurbanScrutinyPoliticsWork (physics)Competition (biology)Smart cityPublic administrationPolitical scienceSociologyEconomyEngineeringPolitical economyInternet of ThingsEconomicsLaw

Abstract

fetched live from OpenAlex

The term 'smart city' has become a popular buzzword in urban politics, but it has not received enough critical scrutiny given the enthusiastic adoption from many scholars, governments, and corporations.This thesis contributes to broader efforts to critically analyze the concept.My work will provide a post-mortem analysis of a now canceled smart city project in Toronto, Canada.Even though the project will not be completed, there is ample material for an analysis of the project as a representation of what an 'actually-existing' smart city would look like as a comprehensive project.My thesis argues that the Toronto project (and many other projects) are organically linked to the politics and economics of accumulation of what scholars have called "urban neoliberalism."To do so, I examine the relationship between this project and interurban competition, capitalist accumulation and commodification, and privatization and corporate control.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0290.023
Scholarly communication0.0120.004
Open science0.0020.005
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.010
GPT teacher head0.260
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

Explore more

Same topicSmart Cities and TechnologiesFrench-language works237,207