The Paradox of Amalgamation: An Analysis of Municipal Restructuring in Ontario
Bibliographic record
Abstract
In the mid 1990s the Progressive Conservative Government of Ontario implemented a series of policies that transformed the institutional relationship between the Province and its municipal subordinates. Such policies were designed to create a system that would be more streamlined, rational, and most importantly, cost-effective. To achieve these goals, municipalities across Ontario were consolidated on the assumption that larger municipalities would have the capacity to operate in a more cost-effective manner. Quite perversely however, the opposite effect has been observed as the costs of municipal operations have increased. . Taking such factors into account, this thesis examines the rational surrounding these policy decisions. More specifically, it seeks to answer the following question in the context of organization theory: In light of the empirical evidence that demonstrates that the perceived benefits of municipal consolidation are difficult to attain, why did the Government of Ontario choose to amalgamate municipal governments in an attempt to create a more cost-effective system of municipal governance? I argue that there are two main factors that can account for this policy decision. First, relevant policymakers did not possess the necessary expertise to impose major legislative and structural changes. Secondly, by not sufficiently engaging experts at the municipal level, policymakers placed themselves in a significant knowledge deficit problem. By taking these factors into account, we can begin to understand why this policy decision was taken. It is hoped that this research will contribute to the academic debate on the municipal restructuring policies of the former Progressive Conservative Government of Ontario. Much of the academic literature that has preceded this research tends to take a non-analytical approach. As such, very few theoretical explanations have been offered in an attempt to demonstrate why such a policy was adopted. This research demonstrates the importance of placing policy decisions in an analytical framework.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".