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Record W3150226060 · doi:10.60082/0829-3929.1405

The Better Local Government Act versus Municipal Democracy

2021· article· en· W3150226060 on OpenAlexaffvenueabout
Simon Archer, Erin Sobat

Bibliographic record

VenueJournal of Law and Social Policy · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsYork University
Fundersnot available
KeywordsLocal governmentDemocracyPublic administrationPolitical scienceBusinessLawPolitics

Abstract

fetched live from OpenAlex

IN AN ERA MARKED BY THE RISE of "illiberal democracies," the rule of law we thought we knew is being tested.Courts have been asked to engage with the expanded and extraordinary use of executive and parliamentary powers everywhere-most recently in the United Kingdom (on the use of the executive's prerogative powers to call elections against the will of Parliament) and the United States (on the legality of executive orders by the President).Locally it has taken the form of interference by the provincial government of Ontario in municipal elections, including the threat of invoking the "notwithstanding clause" in the Charter of Rights and Freedoms to shield such interference from effective constitutional oversight.This special volume of the Journal of Law and Social Policy examines and contextualizes these acts of interference.On 27 July 2018, the Honourable Doug Ford, newly elected Progressive Conservative Premier of Ontario, announced that his government would introduce legislation to reduce the size of Toronto City Council from forty-seven to twenty-five ward seats.This, despite the fact that the 2018 municipal election period had already begun on 1 May 2018 and was well underway; that voting day was scheduled for 22 October 2018; and that the City had recently undertaken an extensive, four-year public consultation on ward boundaries, which resulted in City Council increasing the number of wards from forty-four to forty-seven.Ignoring the requirements of the City of Toronto Act, 2006, 1 the government had not previously consulted the City, provided notice about this drastic change, or even campaigned on the issue before being elected the month before.It is helpful to note that the City and Province (under the former provincial government) had previously worked out a compromise for determining the structure and process of local government.This negotiation of jurisdiction was enacted in the City of Toronto Act, 2006: there would be a lengthy process to determine ward boundaries (taking into account "effective representation" principles developed for the purpose of section 3 democratic rights under the Charter) and a requirement that both the City and Province consult on any changes.The ward boundary review process began in 2013 and concluded in 2017, following several rounds of community consultations, many committee and Council meetings, and significant changes to the city's governance model. 2 The City of Toronto's lengthy and detailed ward boundary review process was upheld on review by the Ontario Municipal Board.3 Yet the City's long-laboured decision was over-ridden by a former City councillor (now Premier) who apparently believed from the start of the City's review that the ward boundaries should simply match federal and provincial electoral boundaries.On 30 July 2018, the provincial government introduced Bill 5, the Better Local Government Act, 2018 (Bill 5 or the Act), for first reading in the Legislative Assembly of Ontario. 4 The Bill would amend the City of Toronto Act, 2006 (Schedule 1), the Municipal Act, 2001 

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.205
Threshold uncertainty score0.408

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.017
Scholarly communication0.0110.006
Open science0.0010.005
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0190.003

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 head0.030
GPT teacher head0.351
Teacher spread0.321 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2021
Admission routes3
Has abstractyes

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