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Record W219059023

Toronto Ten Years after amalgamation/Toronto Dix Annees Apres la Fusion Municipale

2009· article· en· W219059023 on OpenAlexvenueaboutno aff
Harvey Schwartz

Bibliographic record

VenueCanadian Journal of Regional Science · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceLocal governmentDecentralizationHumanitiesPublic administrationLawArt
DOInot available

Abstract

fetched live from OpenAlex

Abstract This paper reviews what has happened to the City of Toronto 10 years after it was amalgamated. From 1995 to 2003, the Ontario Government made a number of major changes in the way that its municipalities were governed and financed. Some municipalities were forced to amalgamate despite the opposition of their residents. The government also redistributed certain responsibilities of the province to the municipalities through the Local Services Realignment Programme (LSRP). The process is called disentanglement. Since the LSRP led to the cost of many of the shared-cost programmes being shifted to the city, the programme can also be termed downloading. Other major changes include the use of market value for property tax assessment and the provincial government control of education funding for the local school boards. Resume Dans cet article, on examine ce que s'est passe a la Ville de Toronto dix annees apres la fusion municipale. Entre 1995 et 2003, le Gouvernement de l'Ontario a introduit plusieurs changements majeurs dans la facon dans laquelle ses municipalites furent gouvernees et financees. Certaines municipalites furent contraintes a subir une fusion, meme si leurs residents etaient contre. Le gouvernement a egalement redistribue certaines responsabilites de la province vers les municipalites. Ce processus visait une separation plus claire entre la province et les municipalites. Mais le resultat de cette transformation etait que les municipalites ont du assumer les couts de plusieurs programmes qu'autrefois etaient partages--une decentralisation des responsabilites sans un transfert des finances. D'autres changements majeurs incluent l'utilisation de la valeur du marche pour l'evaluation de la taxe sur le foncier and le controle par le gouvernement provincial du financement pour les commissions scolaires locaux. ********** This paper reviews what has happened to the City of Toronto 10 years after it was amalgamated. From 1995 to 2003, the Ontario Government made a number of major changes in the way that its municipalities were governed and financed. Some municipalities were forced to amalgamate despite the opposition of their residents. The government also redistributed certain responsibilities of the province to the municipalities through the Local Services Realignment Programme (LSRP). The process is calleddisentanglement. Since the LSRP lead to the cost of many of the shared-cost programmes being shifted to the city, the programme can also be called downloading. Other major changes include the use of market value for property tax assessment and the provincial government control of education funding for the local school boards. The Organization of Local Government Municipalities, their residents, provincial governments and academics have been concerned with the costs and benefits of a large unified city or megacitycompared with many small and diverse municipalities within a large metropolitan area. The concept of amalgamation involves the voluntary or forced merger of smaller local governments with a larger municipality to forma large metropolitan area. If the municipalities had the power to make their own decisions, theoretically they would select the size of government that would produce municipal goods and services at the lowest possible cost. They could also take advantage of economies of scale through joint buying with other municipalities. Many municipalities within a large urban area may also stimulate competition among the municipalities and this provides a strong incentive to keep costs down. Since different municipalities produce different packages of services and taxes, Tiebout argued that the residents could improve their economic welfare by selecting the municipalities where the services and taxes best fit their preferences (Tiebout 1956: 416-424). Determining the needs and desires of residents in small municipalities is less costly than in large municipalities because there are fewer residents for each elected official. …

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.283
Teacher spread0.270 · 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 teacher head, not a consensus.

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

Citations4
Published2009
Admission routes2
Has abstractyes

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