MétaCan
Menu
Back to cohort
Record W1985882034 · doi:10.5130/cjlg.v0i0.1096

Defining a Canadian approach to municipal consolidation in major city-regions

2009· article· en· W1985882034 on OpenAlexaffabout
Jim Lightbody

Bibliographic record

VenueCommonwealth Journal of Local Governance · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical and Economic history of UK and US
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsConsolidation (business)Metropolitan areaRestructuringPoliticsMandateCorporate governancePolitical scienceLocal governmentPublic administrationElement (criminal law)Political economySociologyGeographyBusinessLawEconomicsManagement

Abstract

fetched live from OpenAlex

Where there is a central government with an exclusive mandate over municipalities, along with a state executive structure using the Westminster model, then the consolidation of squabbling municipalities within metropolitan boundaries becomes a distinct possibility A general model of municipal restructuring for the Canadian metropolis is more widespread than the superficially unique circumstances of each case might suggest. The thinking here is informed by Clarence Stone’s urban regime model, which helps to clarify what influences constituted the political tipping point for central government action. The paper focuses primarily on the Toronto and Montreal city-regional municipal consolidations at the end of the last century. It is argued that the decisive element in setting the stage for significant change lay in the pervasive influence of corporate Canada in generally shaping provincial political discourse. What has not previously been of much interest for investigators is the matter of direct consequences for the low politics of city-regional governance. As will be seen, they were both tangible and considerable.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.214
Threshold uncertainty score0.911

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.006
Science and technology studies0.0210.025
Scholarly communication0.0110.003
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.036
GPT teacher head0.298
Teacher spread0.262 · 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 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

Citations3
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueCommonwealth Journal of Local GovernanceSame topicPolitical and Economic history of UK and USFrench-language works237,207